The first quarter of 2026 had broad-based selloff of public SaaS companies. More than $1 trillion decrease in market cap from the public software sector stalwarts was fueled by a pervasive bearish sentiment about the future of software investing. Coined the “software megaddon,” the “SaaSpocalypse,” the “SaaS collapse”, and many other clever names by pundits, this was a major value reset for a broad swath of SaaS and software companies. According to software entrepreneur and insightful software blogger Nicolas Bustamante, the S&P 500 Software & Services Index of 140 companies fell 20% YTD in 2026.¹ Long a sector bell weather holding, Microsoft’s stock has gone from $555/share in the trailing 12 months to $356/share in March 2026 for a 36% decrease. Microsoft exceeded a $4 trillion market cap on July 31, 2025 versus $2.75 trillion in April 20–27 despite slightly beating EPS and revenue in their 2Q265 earnings.

It is widely accepted that the public markets have taken an extremely bearish position on the prospects for SaaS and software companies due to the unprecedented rate of innovation and adoption of AI. Recent well-read articles such as Citrini Research’s “The 2028 Global Intelligence Crisis” are predicting an economic doomsday scenario where AI drives massive job losses for well-paid white collar knowledge workers which dries up consumer spending and drives an economic death spiral. While many SaaS and software companies who were still valued at their 2021 peaks were long overdue for a major reset, we don’t ascribe to a pessimistic view that “AI will eat Software” and view it as click-bait to monetize the attention economy. The AI juggernaut is driving important structural changes to many industries occurring in real time.

Based in Palo Alto, CA I am a Partner on the Clear Ventures IT VC investment team. The Clear Ventures portfolio has holdings in emerging technology companies AI software, AI/data center infrastructure, and intelligent enterprise / enterprise AI. Our investors asked us for our perspective on the recent SaaS and software market correction. This blog post was originally written in response to our client’s questions, but we thought it may have utility to the broader technology community. In the article that follows we address three key topics; 1) the drivers for the 1Q26 ($1T)+ SaaS and software sector reset; 2) the impact of AI on the future of the SaaS software industry and on knowledge work in general; 3) forward-looking predictions on where the opportunities will be found.

The context for my perspective is ~ three decades working with and for frontier technology companies in Silicon Valley across many technology transition cycles, especially my daily work as a Partner on the IT VC investment team at Clear Ventures. Clear Ventures is both an investor in AI and (importantly) active AI practitioners that run our business on captive AI innovations each day. Over the past half decade the Clear team has quietly built a captive agentic-AI native “VC operating system” called ClearConnect that drives big-data analytics-based automation through key elements of our daily workflow.

Part 1: Drivers of the Recent ($1T) SaaS and Software Value Reset

The market cap of many stalwart SaaS companies took a beating in 2026. The sequence of events was swift and brutal:

• January 29, 2026: Fears of AI disruption fueled one of software’s worst days in years. SAP fell more than 15% after its cloud backlog and 2026 forecast missed expectations. ServiceNow dropped about 11% despite a beat-and-raise, while Microsoft fell 10%, wiping out more than $350 billion in market value on concerns about slower cloud growth and massive AI spending. The S&P 500 Software & Services Index fell 8.7%.²
• January 30, 2026: Anthropic expanded Claude Cowork with 11 open-source plugins for roles including legal, sales, finance, marketing, and data analysis. Cowork was included in Claude subscriptions starting at $20/month.³
• February 3, 2026: Markets connected the dots. Bloomberg described the selloff across software, financial services, and asset-management stocks as a $285 billion rout in a single trading day. Thomson Reuters fell nearly 18%; RELX (parent of LexisNexis) dropped 14%; FactSet fell 10.5% (the stock had fallen from a ~$20B peak to under $8B); and Wolters Kluwer dropped about 13%, with other information-services names also hit hard. Jefferies’ Jeffrey Favuzza called it the “SaaSpocalypse,” describing the selling as “very much ‘get me out’ style.”⁴
• February 5, 2026: Anthropic released Claude Opus 4.6, highlighting stronger long-running agentic performance and how it could work with agent teams. By that point, Reuters reported that the S&P 500 software and services index had lost about $1 trillion in market value since January 28, underscoring how quickly the selloff had deepened.⁵
• February 25, 2026: Not to be outdone by Anthropic, Perplexity.AI releases “Computer”, an agent-based system that manages multiple AI models and can interact with compatible software tools to solve problems autonomously based on an initial prompt. This is yet-another sign that AI is quickly expanding beyond simple conversations or isolated tasks. AI platforms like Computer are now acting like digital assistants capable of multi-step workflows. By using a combination of 19 AI models, the system can move from an initial problem-solving prompt through research, writing, and analysis to deliver a final product with minimal human input.
• 1Q26: Open source package OpenClaw experienced unprecedented adoption in 2026, becoming one of the fastest growing opens-source AI projects in history. OpenClaw is a “claw agent” or autonomous AI agent. OpenClaw saw a 925% monthly increase in traffic from February to March 2026, reaching oer 27 million monthly visitors. It quickly surpassed 2 million monthly active users (MAU). The key drivers are heavy adoption in China via integration into leading local platforms like WeChat, Baidu, Tencent, and Alibaba. OpenClaw operates as an autonomous agent that can connect to messaging apps (Telegram, WhatsApp) to handle tasks such as scheduling, research, and email management independently. According to Google Gemini, approximately 65% of OpenClaw users are in the enterprise sector, with high adoption in finance for productivity automation. Apple has seen a surge in demand for Mac Minis that are being used as dedicated hardware to run their own “virtual employees”.
• March 13, 2026: Stanford University’s Scaling Intelligence Lab released OpenJarvis — an open-source framework for personal AI agents that runs entirely on-device. It provides shared primitives for building on-device agents, efficiency-aware evaluations, and a learning loop that improves models using local trace data. The goal is simple: make it possible to build personal AI agents that run locally by default, calling the cloud only when truly necessary. This is notable because it addresses the security concerns of agentic AI systems that require a user to cede huge amounts of control over their identity to a “brain” that runs elsewhere and is controlled by a 3rd party. The contagion spread beyond software into alternative asset managers. Apollo, Blue Owl, Carlyle, KKR, Ares, and Blackstone all came under pressure as investors started to focus on private-credit exposure to software. Bloomberg reported that Barclays estimated BDCs had about 20% of their loan books tied to software, making it their single biggest sector exposure. If AI was about to compress SaaS economics, the credit behind those businesses suddenly looked riskier too.⁶ A bearish cloud has formed over the private equity (PE) industry, as many large PE firms have substantial holdings in legacy software companies that have an existing revenue stream, but are not growing and are at real competitive risk of being left behind by “AI-native” companies with next generation capabilities.
• April 4, 2026 In response to the OpenClaw phenomenon, effective April 4, 2026, Anthropic restricted Claude.ai subscribers from using their flat-rate plan limits to power third-party agent frameworks like OpenClaw. A single OpenClaw instance can consume $100 to $1,000+ in equivalent API costs per day. Anthropic was effectively subsidizing heavy power users through its flat-rate subscription model. This highlights the capacity for agentic AI systems to consume massive amounts of IT resources if allowed to operate unchecked.

Why the current “AI Bubble” may not be a bubble at all. We are well beyond any doubt that AI is a foundation technology for the next generation of successful software (and hardware) companies. It is creating a point-in-time opportunity to disrupt previously unassailable franchise companies with “clean sheet” agentic AI-native solutions. The amount of money being spent on data center capital expenditure in support of AI workloads is unprecedented. But, unlike many past bubbles this is being funded by operating cash flows by some of the most profitable businesses the world has ever seen. The 2026 guidance from hyperscaler cloud service providers is telling. Alphabet/Google committed $180B in capex. Amazon committed $200B. Meta committed $115B to $135B. Microsoft spent nearly $30B in Azure capex in a single quarter. Where past “bubbles” were fueled by VC dollars, SPAC financing, or unsustainable market cap/sales ratios from money-losing businesses the global AI data center arms race is being funded from cash off the balance sheets of market leaders that is derived from real demand and judged by public markets on real results. There are pockets of investment activity that may prove to be irrational exuberance though. According to Crunchbase,1Q26 global investing in VC-based emerging technology companies his a record $297B, up 2.5x over $118B in 4Q25. This was driven by $188B in just four mega-financing rounds: $122B OpenAI, $30B Anthropic, $16B Waymo, and $20B xAI.

Contrary to the flood of apocalyptic reports from the past month, the recent ($1T)+ SaaS and software market reset does not in any way imply the global software opportunity is shrinking. The contrary is true. Blackstone’s Nadeem Meghji recently published a report showing that AI services and software revenues grew from $800M in 2023 to $4.4B in 2024 to $29.8B in 2025, with a doubling to $68.7B forecasted for 2026. If accurate this is one of the fastest ramps in history for any new technology.

We expect there to be a mass transfer / re-allocation of market cap from legacy technology companies that fail to re-engineer their products and operations with an AI-native approach to those that do. Some large and rich technology companies (i.e. ServiceNow) seem likely to make this transition successfully as they have been working on it for many years now. Many will not and are at risk of displacement by nimble and cost-effective AI-native teams with AI-native approaches.

The Clear Ventures team’s research predicts a 3dB increase in opportunity for AI-native frontier technology companies over the next decade. Much of the opportunity for tomorrow’s category leaders is likely to come from today’s mid-market software companies with $100M to $2B in annual revenue from “point products” that were built prior to the Agentic AI innovation flywheel kicked into high gear in 2024 (more on this later).

Opportunity for VC-backed technology companies thrives on scarcity. There are ~30M to 45M software developers in the world (depending on students and adjacent fields i.e. data science are counted), a tiny percentage of the ~8.3B global population. The number of true “AI experts” and data scientists is even smaller still. University enrollment numbers in CS with an AI concentration are at all-time highs to meet the moment. Despite this broad-based demand, free floating anxiety among software developers seems to be on the rise about AI adoption driving down demand through efficiency gains. The trepidation at the individual contributor developer level are indicative of systemic changes that are creating valid headwinds for the existing SaaS and software success playbook. These don’t mark the end of shareholder value creation with SaaS and software investments by any means. They do represent a fundamental reset on how commercial success is likely to be achieved from software innovation. Some of these changes are not being broadly discussed in the media and trade press but are discussed below.

The Rational Fears

Seat-based revenue is mechanically shrinking. When a SaaS customer cuts 15% of its workforce, it cancels 15% of its licenses. As SaaStr’s Jason Lemkin put it: if 10 AI agents can do the work of 100 sales reps, you don’t need 100 Salesforce seats anymore — you need 10. That’s a 90% reduction in seat revenue for the same work output.⁷

Build vs. buy has structurally shifted. A competent developer working with Claude Code or Codex can now replicate the core functionality of a mid-market SaaS product in weeks — not perfectly, not with every edge case handled, but well enough that the CIO reviewing a $500K annual renewal starts asking the question. The credible threat of an internal build has changed every enterprise software negotiation.

Private credit exposure is real. Apollo cut its software exposure nearly in half during 2025. Software EBITDA multiples have been cut in half, affecting the collateral value of loans backing SaaS LBOs.⁸

Growth rates have been declining since 2021. Public SaaS growth rates have declined every single quarter since the 2021 peak. The market was pricing in re-acceleration that hasn’t materialized. Strip out price increases from recent SaaS earnings, and the organic growth picture looks far worse than headline numbers suggest. The AI disruption narrative gave investors permission to reprice what was already, in many cases, overvalued.⁷

The Irrational Fears

“SaaS is dead” is wrong. Nobody is building a homegrown CRM in Replit to replace their Salesforce instance. As Lemkin points out: shipping a v1 is maybe 2% of the work. Systems of record — core ERP, financial systems, compliance infrastructure — have switching costs that are orders of magnitude higher than workflow tools. The question is pricing power, not existence.⁷

The internal contradiction. Bank of America’s Vivek Arya published a widely cited note calling the sell-off “internally inconsistent.” The SaaS selloff relies on two mutually exclusive scenarios: that AI capex will deteriorate to the point of weak ROI and unsustainable growth, while simultaneously AI adoption will be so pervasive and productivity-enhancing that long-standing software workflows and business models become obsolete. Both cannot be true at once.⁹

Incumbents are not passive. The historical disruption model says incumbents resist new technology and die slowly. What’s happening now is different. Incumbents can’t resist because they can’t afford to. Boards demanding answers are forcing aggressive AI adoption. Salesforce, for example, reported 29,000 Agentforce deals with ARR jumping to $800M (+169% YoY) in its Q4 FY2026 earnings.¹⁰ The companies most threatened by AI have become AI’s most aggressive adopters.

Not all SaaS is equally exposed. The sell-off hit everything indiscriminately. But there is a meaningful difference between a workflow tool whose primary value was its interface and a system of record with deep regulatory integration, proprietary data, and high switching costs. That indiscriminate repricing creates opportunity for investors who can distinguish the structurally impaired from the temporarily mispriced.

The capabilities of AI are often being hyped and overstated — It is important to recognize that AI is computation, not cognition as is typically defined in a sentient being i.e. a human. The fear and excitement about AI are currently at a fever pitch. Every new day brings a bevy of headlines about his AI is going to obsolete humans. In 2025 Apple Research released an important paper called “The Illusion of Thinking” to tether this debate back in reality. Many people today believe public foundation models such as Anthropic, ChatGPT, and Gemini solve problems by “reasoning”. When they give a bad answer to a prompt the public thinks AI is bad at thinking. Such a sentiment is possible only with a fundamental lack of understanding of how AI works. Even the name “Artificial Intelligence” is confusing, as it is not artificial and it is not intelligence. It is math — specifically statistics, linear algebra, and probability theory.

When we give a generative AI foundation model like ChatGPT a problem, it does not break it down logically like a human does. AI classifies source data into groups with similar attributes. It searches its training data for similar patterns. If AI finds a match, it reproduces a pattern. If it does not find a direct match, it searches for partial matches from similar queries and stitches them together to produce something rather than nothing. AI does not have a sense of being correct or incorrect, only statistically plausible text to respond to a query based on memorized training data. There is no thinking happening. End users worry about AI being wrong, giving the wrong answer. The real danger isn’t AI being wrong because there is no sense of right or wrong in an AI generated output. There is no reasoning, no self-awareness of failure, no logical steps to produce an answer. There is tonly statistically plausible text.

As problems become more complex AI’s success rate plummets at producing what an informed person would consider to be a correct answer. The likelihood of finding a clean match when AI searches its training data decreases sharply with complexity of task. AI simply gives up quickly as task complexity grows, or even worse, stitches together a bunch of partial matches into a seemingly coherent but unusable response. The Apple research shows that humans do the opposite to overcome the obstacles posed by complex tasks. We allocate more cognitive resources as problems get harder, and when they exceed our capacity we seek out other human experts to bolster our shortcomings. We slow down, challenge our understanding and seek. We to clarify the problem statement. We explore alternatives. We “think outside the box”. AI does the opposite. It generates fewer pattern matching attempts when it comes up empty handed and gives up or mashes together fragments from partial matches.

Users of AI need to be wary of the results that they receive. MIT researchers have recently mathematically proven that certain public AI foundation models are demonstrating “AI sycophancy” — meaning a tendency to agree with users is triggering a “delusional spiral” where AI bots are prioritizing user agreement, resulting in rational people gaining false confidence in incorrect results. The MIT researcher’s paper on arXiv warns this feedback loop can result in models acting like echo chambers rather than reliable and objective tools.

The next major leap is autonomous intelligence — where AI stops following plans created by humans and starts rewriting them. Opinions vary widely (from years away to never) on a realistic timeline for autonomous intelligence.

Part II: The Impact of AI on the Future of SaaS and Software

Two dimensions of change are unfolding simultaneously: the technology of how software is built and deployed is being fundamentally re-architected, and the business models by which software is consumed and monetized are being disrupted. Both create strengths, weaknesses, opportunities, and threats for current players and new entrants alike.

How Software Technology and Development Is Changing

Compound AI systems and agentic AI are displacing monolithic software — It was just three years ago when OpenAI launched ChatGPT. The explosive adoption has been historically significant, but it didn’t initially have a noticeable effect on the market caps of established SaaS vendors. Indeed, many SaaS vendors were quick to adopt LLMs to provide a natural language interface to their existing applications. What changed was the shift from single models to compound systems. UC Berkeley CS Professor and Databricks founding CTO Matei Zaharia identified this in February 2024: state-of-the-art AI results are increasingly obtained by compound systems with multiple components, not just monolithic models.¹¹ In the second half of 2024 Stanford’s Andrew Ng popularized the term “agentic AI” to describe the next evolution — AI agents that autonomously plan, reason, use tools, and take multi-step actions to achieve goals. The term “agentic” by Ng was adapted from human psychology research from the 1970s, where a person who had “agency” over their lives can act and complete tasks on their own behalf. Although Ng is credited with coining the term, it is Zaharia et.al. that described how agentic AI systems are functionally being built today.

The distinction matters. Generative AI is a tool for creation; Agentic AI is a system for execution of increasingly complex tasks. A compound AI system can be built from an ensemble of task-specific agents, where each agent can be optimized, evolved, and scaled independently. This represents a fundamental disruption to traditional SaaS and software which has historically hard-coded human workflows to address specific enterprise use cases.

The rapid adoption of agentic AI over the past 2 years represents a major threat to traditional SaaS in part because it is purpose-built to allow complex problems to be solved that require accessing many SaaS platforms by a new “meta-layer” above any one SaaS vendor’s field of view. Consider a simple case of enterprise sales. Today a sales professional may interact with applications i.e. calendaring/scheduling, contact databases, customer relationship management systems, pre-sales call research and meeting preparation tools, in-sales call note takers, post-sales call action item trackers, and many others. A lot of time is spent by the sales professional doing manual data entry into these SaaS applications. An agentic AI system can be now built that acts like a virtual workforce for the sales professional. Agents for Clari, Gong, InsideSales, Salesforce and other SaaS apps in the sales software stack can be built to automate much of the “grunt work”. This does not obsolete the modern enterprise sales professional, but re-engineering their workflow with agentic AI has the potential to dramatically increase their productivity. The same agentic AI opportunity for fundamental workflow automation to increase productivity exists for many other knowledge worker types.

The Clear Ventures captive agentic AI-based ClearConnect VC operating system is giving the Clear team productivity superpowers every day related to sourcing of gifted founders for new investments, as well as sales acceleration, talent acquisition, and follow-on financing assistance for existing investments. Our use of traditional monolithic point software products has dramatically reduced as our agentic AI stack has continued to improve over the past several years.

Codifying business logic with human coding is becoming old school — SaaS companies have spent the past three decades capturing how humans think and work to increase productivity in specific vertical industry sectors (i.e. legal, finance, insurance, manufacturing) and/or horizontal enterprise functional areas (i.e. sales, engineering, finance, product management, corporate development). AI LLMs shift the task of understanding how humans work from interviewing them to using machines to observe them over time. AI can “learn” how to do high-value human knowledge worker tasks by watching humans do that task for a while, then collapse the human labor content to complete the task via automation. The concept of “markdown skills” and “markdown files” are collapsing months of human coding by experts to weeks or days of observation with modest input by non-coder workers. It is increasingly common for “AI-in-the-loop” systems to monitor human workforce interactions by analyzing emails, Slack channels, meeting transcripts, document review comments, and other channels. This observation-based approach to train AI systems democratizes the proprietary expert knowledge that many SaaS vendors built their businesses on.

Organizing and making searchable public data is a core competency of AI LLMs and no longer a differentiator — The list of SaaS leaders is long that built franchises by taking public domain files and making them dramatically easier to derive business value from. The SaaS era systematically went through the known universe of public data sets, built domain-specific parsers, and formulated meta-data tagging schemes to unlock valuable insights for business users. Examples include court filings and legal briefs, patent databases, public company regulatory filings, financial statements and quarterly reports, press releases, and public/pseudo-public resume data. Ever since Google first published their seminal paper on “transformers” in 2017 and gave birth to the current generative AI LLM arms race, frontier models have been learning how to parse public datasets as training sets. Generations of SaaS company effort into custom data parsers to increase the utility of specific types of documents (i.e. SEC filings, patent databases, case law, real estate listing databases) is now an intrinsic capability of an LLM. This spells serious trouble ahead for public data curation companies.

As Bustamante observes from a decade of building vertical software (first at Doctrine, a leading European legal information platform, and now at Fintool, an AI equity research platform competing with Bloomberg and FactSet): for many vertical software companies, the interface was most of the value. The underlying data was licensed, public, or semi-commoditized. What justified premium pricing was the workflow built on top of that data. Model Context Protocol (MCP) — a standardized way for AI agents to discover and use tools across systems — is accelerating this by eliminating the integration friction that once preserved switching costs. MCP is to agentic AI what REST APIs were to the SaaS era.¹

How Software Business Models and Consumption Are Changing

The traditional SaaS per-seat revenue model is under threat by AI — A hallmark of the nearly three decades of SaaS prosperity have been the relatively predictable revenues from per-seat pricing and consumption models. SaaS leaders i.e. Salesforce sell their product suite with tiered pricing based on the number of active users/seats purchased. Agentic AI is decoupling work from seats. In an agentic AI world, many tasks will be executed by AI agents rather than humans. If AI agents are performing the work of 100 sales reps, you no longer need 100 Salesforce seats. Agentic AI-native solutions often abandon per-seat pricing and instead charge based on resource consumption (i.e. number of “tokens” consumed to perform a task or do a computation) or even outcomes. A reduction in SaaS per-seat licenses means a reduction in SaaS revenues.

There is an important structural difference here that deserves close attention: the unit economics of AI-native companies are fundamentally different from traditional SaaS. Traditional SaaS companies have very low incremental costs to add new users and historically operate with 70–80% gross margins. AI-native companies often see consequential increases in compute for inference and storage as they service new users, with gross margins in the 25–40% range. Unlike SaaS where the marginal cost of an additional seat is de minimis, AI-native consumption models carry real and growing costs that scale with the complexity of the tasks being performed. The success of this transition is not yet proven at scale. The implications for gross margins, unit economics, and ultimately valuations in AI-native businesses are not yet fully understood — and investors who don’t appreciate this structural difference are making a mistake.

SaaS vendors will need to rethink pricing models for the AI-driven automation era that is now upon us. With seat-based pricing, marginal usage per user is relatively low, so infrastructure costs stay predictable. But machine-to-machine traffic from AI agents will scale far faster than human usage, driving significantly higher compute, networking, and storage demand.

The real challenge is not just policing access — it’s re-architecting the economics of SaaS for a world where software is increasingly consumed by machines rather than humans. There are two main ways AI agents can access those services:

1. Web interface automation / scraping: Platforms like LinkedIn or PitchBook require login and closely monitor behavior (rate limits, bot detection, session patterns). So usage tracking is still feasible.
2. APIs / MCP-style integrations: This is where the industry is clearly moving. PitchBook, CoreSignal, and others are increasingly exposing APIs where pricing can be usage-based (queries, records) rather than seats. That model works naturally with AI agents.

Our expectation is a hybrid transition: human UI access will remain seat-based pricing; AI agents will move toward metered API / consumption and usage-based pricing.

LinkedIn is a bit unique because it still positions itself as a social network. But since much of its economic value now comes from recruiting and sales data, it would not be surprising to see agent-specific pricing tiers emerge over time.

As is the case with most modern agentic AI-based systems, ClearConnect is already mostly usage-based where we access, consume, and pay for third party data sources based on what we use.

The world is tired of paying exorbitant professional services fees for software customization and implementation — Some SaaS and software giants have long differentiated their enterprise products based on customizability. This has spawned large professional services companion industries doing enterprise-specific implementations of leading packages i.e. Salesforce for customer relationship management, SAP for enterprise resource planning and supply chain automation and Workday for HR and benefits administration. Once an enterprise user has invested the blood and gold to do a custom implementation of any mission-critical business function the switching costs increase dramatically. We believe the opportunity is large to reduce SaaS and software total cost of ownership by using agentic AI tools to automate lifecycle maintenance, migration, upgrades, audits, regulatory compliance, and customization over time. Clear II portfolio companies Kognitos and Tessera Labs are examples of agentic AI-based “Services-as-Software” companies.

SaaS learned interfaces and UI innovations can be replaced by AI natural language — “Data companies” i.e. Bloomberg, LexisNexis, PitchBook, and FactSet built their franchises by codifying human workflows into proprietary UIs, training end users on their layout and shortcuts, and leveraging their incumbency as the familiar “cockpit” for entire industries i.e. finance, legal, regulatory. The advent of AI-based natural language processing hides the complexity of learning a proprietary UI for each SaaS vendor. A financial analyst simply has to tell an LLM agent what they seek in their natural language rather than learn the idiosyncrasies of each vendor’s interface. When a natural language query replaces a trained user’s muscle memory, the SaaS UI ceases to be a moat and becomes a liability. There are many waves of computer science innovations that hide UI complexity that was once seen as a workforce differentiator. Just as the icon-based Apple UI obsoleted the need to learn how to navigate autoexec.bat file, a config.sys file, or a UNIX shell’s command line interface, the simplicity of a natural language interface weakens the need to learn unique UIs for many SaaS vendors. We expect AI-native public data querying capabilities i.e. Anthropic Legal to offer strong alternatives to entrenched SaaS comparables.

The value of building and accessing proprietary datasets will grow dramatically in the Agentic AI era — For many years now, the Clear LPs have heard us espouse the strategic value of making investments in AI-native software companies that could access and/or create proprietary data sets as a source of sustainable competitive advantage. The fear that “AI will replace all software” misses the point. AI-native companies with proprietary data, deep workflow integration, and regulatory complexity are more defensible than the horizontal SaaS they’re replacing — not less. A company with ten years of proprietary operational data training its models is not replicable in weeks by an agentic coding tool. The moat is the data, the workflow depth, and the regulatory clearance — not the code. In Bustamante’s words: “The companies that survive this transition are the ones that moved from ‘we organize public data better’ to ‘we own data you can’t get anywhere else.’”¹ There is an arms race in process to protect sensitive corporate data assets from the prying eyes of public LLMs. We expect this to accelerate, which bodes well for Clear portfolio companies such as Concentric.AI that address the pressing need for data access control and data leakage prevention.

SaaS vendor disintermediation from the end customer by third party agentic AI reasoning layers is a real threat — AI-native next-generation software companies have the potential to “hollow-out” SaaS incumbents that are often today’s “system of record” by hiding their complexities behind an intelligent reasoning layer that reduces lifecycle costs. SaaS vendors who built their systems for human end users will have to re-architect them for machine-to-machine communications and next-generation reasoning. This is a fundamental re-platforming challenge that many incumbents will struggle to execute while simultaneously defending their existing business.

The Losers

Traditional contract software development body shops. Companies whose entire business model is predicated on billing for human knowledge worker labor hours need to be re-tooled to an AI-first, AI-everywhere workflow. When agentic AI tools can accomplish in hours what once took teams of developers weeks, the per-hour billing model collapses. TCS sank 6% and Infosys fell 7% on the February 3 selloff alone — the market is already pricing this in.⁶

Traditional enterprise systems integrators and implementors. Multi-year, multi-million-dollar implementation projects are being compressed by AI-native platforms from years to weeks. The $500B+ global IT services market built on SaaS implementation labor is facing structural compression.

Existing SaaS and software vendors who cling to the notion that their legacy UI is a source of competitive differentiation (many). As natural language interfaces replace trained user muscle memory, the proprietary UI ceases to be a moat. As Bustamante observes, vertical software companies spent armies of designers and customer success managers maintaining interfaces that were the product. That entire cost center is being absorbed by a chat interface.¹

Anyone that relies on organizing public data that is in the strike zone of foundation models. The franchise value of custom data parsers for public datasets (SEC filings, patent databases, case law) has been structurally impaired. FactSet dropped from a ~$20B peak to under $8B. The market is telling us what it thinks about public-data moats.

PE-backed SaaS companies underwritten at aggressive multiples on the assumption that “annual recurring revenue” would remain annual and recurring. Apollo cut its software exposure nearly in half during 2025. The contagion from the February selloff into alternative asset managers — Apollo, Blue Owl, Carlyle, KKR, Ares, and Blackstone all came under pressure — demonstrated that the credit markets understand this risk. Bloomberg reported that BDCs had about 20% of their loan books tied to software, their single biggest sector exposure.⁶

The Winners

The future of SaaS and software belongs to companies that can deliver automation with business value, enrich data assets with context and meta-data to enable actionable insights, protect proprietary data assets, and ultimately enable autonomous reasoning and problem-solving without constant human intervention. As described above, the toolkit for accomplishing these lofty business automation goals is evolving at an unprecedented pace.

The high rate of change presents a classic “innovator’s dilemma” for existing SaaS and software vendors. Some will adapt, but many will not. Small, elite teams of AI-native talent will have a once-in-a-generation opportunity to leapfrog today’s market-leading SaaS and software vendors.

Bustamante’s framework, drawn from a decade of building vertical software, is useful here. Five traditional moats are being dismantled: learned interfaces, encoded workflows, search over public data, talent scarcity, and bundling. But one moat is being strengthened: proprietary data. Companies that own data nobody else can access — built through years of domain-specific operations in regulated industries — are more defensible in an AI-native world, not less.¹ The winners will also include those building the physical infrastructure the AI economy runs on, those creating “services-as-software” platforms that replace human-intensive consulting with intelligent automation, and those capturing the new AI budget that is being redirected from legacy SaaS spend.

How ClearConnect Embodies the Best Practices of the AI Winners

Given Clear Ventures’s unique position as both an AI investor and an AI practitioner running our business on ClearConnect, our promising agentic AI-native portfolio companies, and above all our hybrid team of technology VC investment professionals and AI software development experts, the Clear team is well positioned for continued success in these opportunity areas for years to come. Importantly, the combination of ClearConnect, Clear Portfolio Services, and initiatives such as our Clear Venture Fellows program have planted many hundreds of relationship seeds with gifted founder-level talent for differentiated deal flow.

The Timeline

Many SaaS companies were trading at generous circa-2021 15–20x market cap/sales multiples because they had a confluence of attractive factors: multi-year contracts; high customer retention; high gross margins; the perception of customer “lock-in” by being the system of record for the customer’s data; end-user lock-in from a user base trained in their UI/UX; meaningful Q2Q and YoY revenue growth. As discussed above, foundation LLMs are purpose-built so the model itself is the parser. However, change will take time. Multi-year SaaS ARR contracts will need to run their course. AI-native challenger companies that start with a clean slate will need to prove they can meet stringent enterprise adoption criteria at meaningful scale. Just like those that have come before them, the enterprise adoption cycle will challenge new entrant AI-native vendors to justify shifting budget from the current suite of SaaS vendors to the new entrants.

We predict much of the early “experimental recurring revenue” (ERR) that is transitioned from incumbent vendors will not transition to true “annual recurring revenue” (ARR) for a variety of reasons. Many AI-native new entrants will surely fail as incumbent SaaS vendors enrich their own offerings with new agentic AI capabilities. And as noted above, new AI-native entrants will contend with a fundamentally different gross margin structure (25–36% vs. 70–80% for traditional SaaS) that will challenge their ability to scale profitably. Still, many of today’s SaaS vendors will find that their AI enrichment efforts are insufficient to overcome the structural advantages of AI-native challengers with no legacy cost structure to protect. We expect the most acute disruption to unfold over a 3–5 year horizon, concentrated in horizontal workflow tools and data aggregation businesses, with the most durable value creation occurring in the infrastructure layer and in vertical AI companies operating in regulated, data-rich, or physically-grounded domains.

Part III: Where the Opportunities Are for the Clear Portfolio

We see the opportunity for the existing and future Clear Ventures portfolio across three layers: 1) the vertical AI applications in data-rich and regulated industries where proprietary data is the moat, 2) the “services-as-software” platforms that replace human-intensive consulting with intelligent automation, and 3) the physical infrastructure that the AI economy runs on.

The Vertical AI Layer: Proprietary Data as a Moat

These Clear Ventures portfolio companies have proprietary datasets as a source of sustainable competitive advantage:

• AICrete (founding investor) uses agentic AI to build a proprietary dataset of end-to-end concrete and aggregate manufacturing parameters (very sensitive) that enables the next level of industrial process control. Their AICreteOS platform serves 220 plants with three years of proprietary AI training data built through deep industry collaboration. AICrete also expanded into hardware with AggSense, an AI-powered sensor that uses computer vision to analyze particle size distribution and moisture content in real time.
• Cynch.AI (founding investor) uses agentic AI to build a proprietary dataset of tax filer data (very sensitive) to dramatically increase the productivity of a human tax preparer from ~50 returns per year as an industry-wide productivity benchmark to ~140 returns per year in 2025. Their core AI platform “Abacus” ingests millions of proprietary tax documents and financial statements to build a nuanced understanding of their business customer’s most sensitive captive information. While public LLMs will certainly ingest public domain tax code documents at the local, state, and federal level, we don’t see this information ever being made available to public foundation models i.e. OpenAI or Anthropic. Cynch is also pursuing a novel growth model: acquiring client books from retiring CPAs and scaling them through AI-driven modernization.
• Evidently.com (founding investor) has built Clinical Data Intelligence that processes vast patient records — thousands of clinical notes, lab results, imaging, and external data — creating comprehensive patient profiles paired with a specialized medical knowledge graph. Evidently delivered a 0.1 Case Mix Index increase at University of Iowa Health Care within four weeks, 30–80% reductions in chart review time across major academic medical centers, and $44M in projected annual reimbursement recovery for a major health system.
• Fabrix.AI (Series A investor) uses agentic AI to build a proprietary dataset spanning many hundreds of IT systems for next-generation observability, infrastructure monitoring, event correlation, and crisis mediation. While Cisco acquired Splunk for log analytics, their system is not an agentic AI-native approach. Fabrix.AI has closed ~$13M of TCV through the Cisco co-sale channel, where Cisco has closed ~$140M in matching TCV due to the Fabrix.AI ability to access many disparate IT systems, ingest their configuration and event data, enrich this with situational meta-data, and do cross-platform analytics.
• Wherobots (founding investor) provides a cloud-native Spatial Intelligence platform for scalable spatial analytics and GeoAI, built on Apache Sedona (which their founders created), delivering 20x faster performance and 40% lower costs for industries from insurance to telecom to agriculture. With 62 million Sedona downloads and customers including Amazon Maps, Wherobots is creating a data moat in the physical world that foundation models alone cannot replicate.

Additional Clear portfolio companies with strong proprietary data moats include Concentric AI (seed investor) — autonomous data security addressing the new attack surface created by agentic AI), GEn1E Lifesciences (seed investor) — clinical-stage AI-powered drug discovery with FDA Fast Track designation, and Vori (founding investor) — AI operating system for independent grocery and retail.

The “Services-as-Software” Layer

• Espresa (founding investor) started life as a traditional enterprise SaaS vendor pioneering culture benefits management. While started before the agentic AI wave, they have quickly embraced an “AI Everywhere” corporate strategy that is paying massive dividends on productivity and scalability. The point of origin for this transformation is the whiteboard at the Clear offices during a strategic planning session with the company’s leadership.
• Lilt (Series B investor) has built an AI-powered enterprise translation platform combining proprietary LLMs with human linguist expertise across 100+ languages. Intel achieved 40% cost reduction with doubled content volume; Lenovo saw 50% cost savings and 60% faster timelines.
• Tessera Labs i(founding investor) os an agentic AI-native company giving enterprise software implementation, customization, and migration teams super-powers. Their vendor-agnostic platform compresses ERP transformation timelines from years to weeks and reduces costs by more than half across SAP, Salesforce, Workday, and Oracle, with enterprise-grade governance for regulated industries.

IT Infrastructure Layer: Deep Tech for the Datacenter and AI Infrastructure Stack

Regardless of which macro scenario plays out — soft landing, hard landing, or worse — the datacenter buildout continues. Data centers captured more than 20% of global greenfield FDI in 2025, with total AI infrastructure capex projected to approach $1 trillion by 2030. Hyperscalers have committed $150–200 billion per quarter in capex. Even in the most bearish scenarios, the infrastructure layer is evolving to meet growing demand.

IT infrastructure was used for human-to-human communications (e.g. the global public switched telephonie network), then for human-to-machine communications (e.g. consumer Internet and mobile services), and next for machine-to-machine communications (e.g. agentic AI systems access SaaS platforms as the system of record).

Just as “video broke the Internet” with Netflix consuming 70% of the Internet backbone bandwidth for streaming services to obsolete the physical DVD, the agentic AI-based automation epoch will spawn unprecedented IT resource consumption from machine-to-machine traffic. The wealth created by AI flows to the owners of compute. That is the layer we are focused on.

Memory and Compute Optimization — Clear portfolio company MEXT develops Predictive Memory™, the first AI-powered software solution that delivers DRAM-class performance at flash-level costs — enabling 2–4x greater effective memory capacity or up to 50% lower costs for memory-intensive workloads, without requiring hardware changes or application modifications. As the marginal cost of AI inference collapses, the companies that make it cheapest to run win.

Cooling and Thermal Management — At 30–70 kW rack densities — where AI workloads are pushing today — liquid cooling has gone from “nice to have” to an existential requirement. Only roughly 20% of datacenter operators are currently prepared for high-density AI racks. Brownfield retrofits, direct liquid cooling, immersion systems, and two-phase fluids represent a decade-long upgrade cycle across every major datacenter in the world. Clear portfolio company Frore Systems is a pioneer in advanced thermal technologies and recently became Clear’s first portfolio company to cross a $1B valuation, closing a Series D at $1.6B post-money valuation. Frore has two breakthrough products. AirJet® is the world’s first solid-state active cooling chip for consumer, industrial, and edge devices. LiquidJet™ is a direct-to-chip liquid cooling coldplate for AI data centers that delivers 2x higher hotspot power density, 50% greater cooling efficiency, and 4x lower pressure drop compared to legacy cold plates — while maintaining drop-in compatibility with existing infrastructure. The technology has demonstrated superior performance with NVIDIA’s Blackwell Ultra GPUs and is positioned to support future chips exceeding 4,000W. This is not a software feature. It is mission-critical next generation physical infrastructure that the AI economy cannot run without.

Networking and Optical Interconnects — At extreme rack densities, the bottleneck shifts from compute to data movement. Clear portfolio company Arrcus develops high-performance networking software including the ArcOS network operating system and ACE-AI platform for AI-optimized data center fabrics, enabling hyperscale performance for distributed GPU clusters with AI-optimized telemetry, lossless Ethernet/RoCEv2 support, and cloud-native encryption. Silicon photonics, optical interconnects, and high-bandwidth memory fabrics are genuinely hard engineering problems with massive TAMs. NVIDIA has committed $4 billion to photonics suppliers Coherent and Lumentum, signaling that the hyperscaler ecosystem is betting on optical interconnects as the next critical layer. Clear portfolio company Avicena develops microLED-based optical interconnects under its LightBundle™ technology, delivering ultra-low-power Tbps-scale links — outperforming electrical interconnects in energy efficiency, density, and latency.

Our Position

We are not SaaS investors. We are deep tech investors. We back companies building the next generation of AI-native companies that matter in data-rich verticals where the competitive moat is real, and in durable software and physical infrastructure that the AI economy runs on — chips, cooling, networking, memory optimization, AI security, etc. The current market dislocation is creating the conditions under which we do our best work.

Clear practices what this blog preaches. ClearConnect — our captive agentic AI-based VC operating system — is itself a compound AI system built from an ensemble of task-specific agents. It powers our sourcing, customer discovery, talent acquisition, and fundraising research workflows every day. We believe no other firm in the VC asset class has made this level of investment in captive AI infrastructure, and it gives us a structural advantage in identifying, evaluating, and supporting the companies in this letter.

Clear Ventures is purpose-built to help gifted founding teams build technology ccompanies that matter. We believe the adoption and proliferation of AI-based innovation at all layers of the IT stack — from materials | devices | systems | infra software | application software — represents a historically significant opportunity. We are entering into the most important early-stage investment environment we have seen in a decade. While pundits are saying “AI is eating software” and “software is dead,” we think the IT VC opportunity related to Enterprise AI, Physical AI, and High-Performance IT infrastructure will grow substantially through aggressive AI adoption. If you have spent your days preparing to build tomorrow’s market leading and it is now time to bet on yourself, we look forward to discussing how we can help you build a great company.

Sources

¹ Bustamante, N. “10 Years Building Vertical Software: My Perspective on the Selloff.” LinkedIn, February 2026. https://www.linkedin.com/pulse/10-years-building-vertical-software-my-perspective-nicolas-bustamante-foczc/

² Reuters. “US software stocks slide after SAP, ServiceNow results fuel AI disruption fears.” January 29, 2026. https://www.reuters.com/business/us-software-stocks-slide-after-sap-servicenow-results-fuel-ai-disruption-fears-2026-01-29/

³ Reuters. “AI concerns pummel European software stocks.” February 3, 2026. https://www.reuters.com/business/media-telecom/ai-concerns-pummel-european-software-stocks-2026-02-03/

⁴ Bloomberg. “‘Get Me Out’: Traders Dump Software Stocks as AI Fears Take Hold.” February 3, 2026. https://www.bloomberg.com/news/articles/2026-02-03/-get-me-out-traders-dump-software-stocks-as-ai-fears-take-hold

⁵ Reuters. “Global software stocks hit by Anthropic wake-up call on AI disruption.” February 4, 2026. https://www.reuters.com/business/media-telecom/global-software-stocks-hit-by-anthropic-wake-up-call-ai-disruption-2026-02-04/

⁶ Reuters. “Global software stocks hit by Anthropic wake-up call on AI disruption.” February 4, 2026. https://www.reuters.com/business/media-telecom/global-software-stocks-hit-by-anthropic-wake-up-call-ai-disruption-2026-02-04/ ; Bloomberg. “Private Credit’s Massive Software Bet Is Bigger Than It Appears.” February 13, 2026. https://www.bloomberg.com/news/articles/2026-02-13/private-credit-s-massive-software-bet-is-bigger-than-it-appears

⁷ Lemkin, J. “The 2026 SaaS Crash: It’s Not What You Think.” SaaStr, January 30, 2026. https://www.saastr.com/the-2026-saas-crash-its-not-what-you-think/

⁸ SaaStr. “SaaS Markets Have Crashed in 2026. But Is Private Credit the Even Bigger Risk?” https://www.saastr.com/saas-markets-have-crashed-in-2026-but-is-private-credit-the-even-bigger-risk/

⁹ Fortune. “The tech stock free fall doesn’t make any sense, BofA says in rebuke to investors.” February 4, 2026. BofA analyst Vivek Arya note. https://fortune.com/2026/02/04/why-saas-stocks-tech-selloff-freefall-like-deepseek-2025-overblown-paradox-irrational/

¹⁰ Salesforce Q4 FY2026 Earnings Release. February 25, 2026. Agentforce ARR $800M (+169% YoY), 29,000 deals. https://www.salesforce.com/news/press-releases/2026/02/25/fy26-q4-earnings/

¹¹ Zaharia, M. et al. “The Shift from Models to Compound AI Systems.” Berkeley AI Research Blog, February 2024. https://bair.berkeley.edu/blog/2024/02/18/compound-ai-systems/

Note: All market data cited reflects publicly available sources as of March 2026.

As we close out 2025, we want to extend our gratitude to the founders, operators, and LPs who continue to inspire everything we do at Clear Ventures. Thank you for your trust, your partnership, and your relentless pursuit of what’s possible.

Despite a challenging environment for the VC asset class — marked by limited liquidity events and compressed valuation gains — we are pleased to report consistent financing success across the Clear portfolio. Over the past five quarters, our companies completed 14 follow-on financings and closed 3 new investments, a testament to the inspiring efforts and resilience of our founders and teams. We’re equally proud of our Fellows and community partners, whose work continues to advance early-stage innovation.

ACTIVE PORTFOLIO NEWS

Fundraising Announcements

Cynch AI | $9M Growth Round

Cynch AI has raised $9M to accelerate its AI-native approach to tax automation. Built to address the growing shortage of CPAs, Cynch applies deterministic, non-hallucinatory AI to automate complex tax workflows while preserving trusted advisor-client relationships. The platform enables accounting firms to operate with greater accuracy, efficiency, and scale, reducing manual effort without sacrificing compliance or reliability. This funding will support Cynch AI’s acquisition-led expansion and continued development of its AI infrastructure as it works to modernize tax and accounting services for underserved businesses.

Opsera | $20M Series B

Opsera has raised $20M in Series B funding to accelerate its AI-powered approach to DevOps orchestration. The company’s unified platform enables software engineering teams to automate toolchains, streamline deployment pipelines, and unlock deep visibility into the health of their code and infrastructure. This new funding will help expand Opsera’s AI capabilities, enabling smarter automation and proactive insights at scale. With growing traction among enterprises seeking to enhance release velocity and governance, Opsera is proving to be a key player in the future of intelligent DevOps.

Kognitos | $25M Series B

Kognitos has raised $25M in Series B funding to expand its pioneering approach to business automation. With a mission to make automation as intuitive as conversation, the company enables teams to build and manage workflows using plain English, eliminating the need for code or complex interfaces. As organizations look for smarter, faster ways to improve productivity, Kognitos is reshaping how automation is created, scaled, and understood across the enterprise.

Swift Navigation | $50M Series E

Swift Navigation has raised $50M in Series E funding to expand the reach of its centimeter-accurate positioning platform, Skylark™. As the first cloud-based, ASIL-certified service for real-time GNSS correction, Skylark is redefining what’s possible in autonomy, robotics, and precision logistics. Powering over 10 million vehicles and devices globally, Swift enables high-integrity navigation at scale, 100x more accurate than traditional GPS.

Avicena | $65M Series B

Avicena Tech has raised $65 million in Series B funding to scale production of its groundbreaking LightBundle optical interconnects, bringing the total capital raised to $120 million. With demand for energy-efficient, high-bandwidth solutions soaring across AI data centers and disaggregated memory systems, Avicena’s microLED-based interconnects offer a transformative alternative to traditional electrical and laser-based links. Their platform delivers superior performance in terms of bandwidth density, power consumption, and scalability, positioning the company at the forefront of sustainable infrastructure for AI and next-generation computing. This milestone marks a critical step as Avicena moves from innovation to production.

Cartesian Kinetics | Seed Extension

Cartesian Kinetics Inc has closed a seed extension round to accelerate the rollout of its retrofit-first robotics platform for warehouse automation. Their flagship solution, Carte+, enables operators to automate existing warehouse infrastructure without the disruption, cost, or lead time of greenfield builds, delivering up to 5X throughput improvements, a 50% reduction in picking costs, and ROI in under 2.5 years. With over 22,000 warehouses in the U.S. still operating manually, Cartesian is targeting a $14 billion+ market opportunity by making high-density, high-throughput automation accessible to facilities of all sizes.

Frore Systems Introduces LiquidJet, Coldplate for AI Data Centers

Named to EE Times’ Top 100 Startups in Silicon, Frore Systems continues to push the boundaries of thermal innovation. At the Open Compute Project (OCP) Summit in October, Frore Systems unveiled LiquidJet, a revolutionary direct-to-chip liquid cooling solution built for the next generation of AI data centers. This builds on the proven success of AirJet, most notably showcased at CES 2025 with an iPad Pro demonstrating 53% higher performance. AirJet Mini Sport was also recognized as a CES Innovation Awards® Honoree. We’re proud to be long-term partners to Frore Systems.

Other Milestones

• AICrete modernizes concrete production with AICreteOS
• Arrcus announced a $67M investment from Fujitsu and an exclusive Japan partnership, advancing global AI and 5G/6G networking infrastructure development
• Atmosic Technologies appoints Ali Foughi as CEO, leveraging his 30 years of expertise to drive the company’s next phase of innovation and growth
• Avicena honored at ECOC 2025 for the Most Innovative Hybrid PIC/Optical Integration Platform
• Avicena Tech appointed Marco Chisari as CEO, bringing deep semiconductor and investment experience to scale its LightBundle™ technology, while co-founder Bardia Pezeshki transitions to CTO following their $65M Series B
• Concentric AI secures new patents on semantic categorization and user behavior analytics
• Concentric AI received two awards — Most Innovative Technology and Best Booth — at the Innovate Cybersecurity Summit in Nashville
• Concentric AI won the 2025 SC Award for Best Data Security Solution thanks to its Semantic Intelligence platform
• Espresa was named a Top Vendor in both Employee Recognition Software and Lifestyle Spending Accounts to kick off Q2
• Espresa was awarded Gold for Technology Department of the Year at the 2025 Stevie® Awards and once again recognized by Shortlister as a top vendor for Lifestyle Spending Accounts and Employee Recognition
• Evidently launched Ask Evidently, the first AI chat interface for clinicians, enabling smarter, real-time access to clinical data intelligence across U.S. health systems
• Fabrix.ai named a Value Leader in the EMA Radar™ Report
• GEn1E Lifesciences Inc. announced the appointment of Dr. Francois Nader, MD, MBA, as Chair of the Board, bringing world-class leadership to their mission of developing precision therapies for inflammatory diseases
• MEXT introduced Predictive Memory, an AI-driven solution that instantly expands memory capacity 2–4X without new hardware or app changes, unlocking faster AI/ML training and analytics
• Opsera wins Best DevOps Automation Solution at 2025 Tech Ascension Awards, highlighting their Unified DevOps Platform’s efficiency and scalability
• Opsera wins recognition in the 2025 Built on Databricks Startup Challenge for its DevOps for DataOps solution
• Opsera won the 2025 CloudX Award in Cloud Application Platforms, underscoring its leadership in accelerating software delivery with trust and visibility
• VoriOS went live at Asian Food Center across 4 stores and 40 lanes in 30 days, showcasing its power as an AI-powered operating system for grocers to modernize and scale
• Wherobots partners with Databricks Unity Catalog to help enterprises scale geospatial AI

Acquisitions

Tignis | Acquired by Cohu

Tignis has been acquired by Cohu, Inc. (NASDAQ: COHU), marking a strategic move into the $2.6B semiconductor process control market. Tignis applies advanced AI/ML models to deliver real-time insights for manufacturing systems, helping fabs monitor, predict, and optimize tool behavior with unprecedented precision. This acquisition enables Cohu to integrate Tignis’ software-driven intelligence into its semiconductor test and inspection systems, offering customers a differentiated solution to improve yield and reduce downtime. The Clear team is proud to have supported Tignis from the earliest stages and congratulates the team on this exciting next chapter.

ChipStack | Acquired by Cadence

ChipStack has been acquired by Cadence, a global leader in electronic design automation. Founded in 2023, ChipStack set out to dramatically accelerate custom chip development with generative AI, reducing verification cycles by more than 70% across formal and simulation-based flows. Their technology quickly gained adoption from leading semiconductor companies, AI chip startups, and hyperscalers. Joining Cadence will help bring ChipStack’s AI-driven verification capabilities to a wider market while strengthening support for existing customers.

WHAT WE’VE BEEN UP TO:

This fall, we welcomed our 2025 class of Venture Fellows, 14 exceptional PhD candidates and post-docs beginning a six-month experience designed to connect top technical talent with aspiring founders across Silicon Valley. The Fellowship remains one of our most meaningful initiatives, and we look forward to introducing each Fellow to the Clear network in the months ahead.

Beyond the new cohort, the Fellows community continues to shine. Our team had a great experience at Stanford Founders Pitch Day this month, where Somnath Banerjee represented Clear Ventures (pictured above with Clear Fellow Francesco Marchioni). The room was filled with early-stage innovation, and it was especially inspiring to reconnect with leaders in the community. We also supported Stanford’s largest-ever Demo Day, organized by Clear Fellows Francesco Marchioni and Johnny Chang. We’re also celebrating past Fellow Austin Williams, who is developing waterproof cochlear implant materials at CMU and building SilkyAI, a startup helping households cook smarter and waste less.

Wishing everyone a joyful holiday season and a strong start to the new year. Thank you for being part of the Clear Ventures community.

Stay connected: LinkedIn | Medium

As we move into the second half of 2025, we remain inspired by the resilience, creativity, and momentum within the Clear Ventures community. In a time marked by both market uncertainty and rapid AI-driven transformation, it’s especially rewarding to witness our portfolio companies and Fellows not only navigating complexity but thriving in it.

We’re grateful for the opportunity to partner with such visionary founders, innovative teams, and steadfast LPs who share our belief in building lasting, category-defining companies. The progress in the first half of the year, across funding milestones, product breakthroughs, acquisitions, and global recognition, underscores the strength of that shared mission.

We’re proud to highlight just a few standout moments from the Clear ecosystem below, and we look forward to what the rest of the year brings. Thank you.

ACTIVE PORTFOLIO NEWS

Fundraising Announcements:

Opsera | $20M Series B

Opsera has raised $20M in Series B funding to accelerate its AI-powered approach to DevOps orchestration. The company’s unified platform enables software engineering teams to automate toolchains, streamline deployment pipelines, and unlock deep visibility into the health of their code and infrastructure. This new funding will help expand Opsera’s AI capabilities, enabling smarter automation and proactive insights at scale. With growing traction among enterprises seeking to enhance release velocity and governance, Opsera is proving to be a key player in the future of intelligent DevOps.

Kognitos | $25M Series B

Kognitos has raised $25M in Series B funding to expand its pioneering approach to business automation. With a mission to make automation as intuitive as conversation, the company enables teams to build and manage workflows using plain English, eliminating the need for code or complex interfaces. As organizations look for smarter, faster ways to improve productivity, Kognitos is reshaping how automation is created, scaled, and understood across the enterprise.

Swift Navigation | $50M Series E

Swift Navigation has raised $50M in Series E funding to expand the reach of its centimeter-accurate positioning platform, Skylark™. As the first cloud-based, ASIL-certified service for real-time GNSS correction, Skylark is redefining what’s possible in autonomy, robotics, and precision logistics. Powering over 10 million vehicles and devices globally, Swift enables high-integrity navigation at scale, 100x more accurate than traditional GPS.

Avicena | $65M Series B

Avicena has raised $65 million in Series B funding to scale production of its groundbreaking LightBundle optical interconnects, bringing the total capital raised to $120 million. With demand for energy-efficient, high-bandwidth solutions soaring across AI data centers and disaggregated memory systems, Avicena’s microLED-based interconnects offer a transformative alternative to traditional electrical and laser-based links. Their platform delivers superior performance in terms of bandwidth density, power consumption, and scalability, positioning the company at the forefront of sustainable infrastructure for AI and next-generation computing. This milestone marks a critical step as Avicena moves from innovation to production.

Cartesian Kinetics | Seed Extension

Cartesian Kinetics has closed a seed extension round to accelerate the rollout of its retrofit-first robotics platform for warehouse automation. Their flagship solution, Carte+, enables operators to automate existing warehouse infrastructure without the disruption, cost, or lead time of greenfield builds, delivering up to 5X throughput improvements, a 50% reduction in picking costs, and ROI in under 2.5 years. With over 22,000 warehouses in the U.S. still operating manually, Cartesian is targeting a $14 billion+ market opportunity by making high-density, high-throughput automation accessible to facilities of all sizes.

Acquisitions:

Tignis | Acquired by Cohu, Inc.

Tignis has been acquired by Cohu, Inc. (NASDAQ: COHU), marking a strategic move into the $2.6B semiconductor process control market. Tignis applies advanced AI/ML models to deliver real-time insights for manufacturing systems, helping fabs monitor, predict, and optimize tool behavior with unprecedented precision. This acquisition enables Cohu to integrate Tignis’ software-driven intelligence into its semiconductor test and inspection systems, offering customers a differentiated solution to improve yield and reduce downtime. The Clear team is proud to have supported Tignis from the earliest stages and congratulates the team on this exciting next chapter.

Other Noteworthy Highlights

Concentric AI

Concentric AI continues to gain recognition as a category-defining leader in data security, earning “Best Data Security Solution” at the 2025 SC Awards, multiple honors at the Innovate Cybersecurity Summit, and a featured mention in Gartner’s 2025 Market Guide for AI TRiSM. With their fifth patent granted and momentum building, Concentric AI remains one to watch.

Frore Systems

Frore’s AirJet Mini Sport was named a CES Innovation Awards® Honoree in the Computer Hardware category, with recent demos showing a 53% performance boost on iPad Pro devices. Their technology continues to set the bar for active thermal management in compact devices.

Avicena

Avicena was featured in IEEE Spectrum for its breakthrough LightBundle™ platform, which uses microLEDs to deliver low-power, high-bandwidth optical interconnects for AI data centers. The spotlight underscores Avicena’s growing role in shaping the future of AI infrastructure.

Fabrix.ai

Fabrix.ai rebranded and launched its Agentic AI platform for ITOps, earning a “Value Leader” distinction in the EMA Radar Report and recognition for CMO Shailesh Manjrekar as a Top 50 Global Thought Leader in Agentic AI. The company was also recognized in multiple Gartner research publications and recently hosted a successful, first-of-its-kind demo day showcasing its agentic AI capabilities.

Espresa

Espresa was awarded Gold for Technology Department of the Year at the 2025 Stevie Awards and named a Top Vendor in both Employee Recognition Software and Lifestyle Spending Accounts. Their new partnership with Headspace underscores their commitment to holistic employee well-being.

Evidently

Evidently’s Chief Product Officer, Dr. Kalie Dove-Maguire, was nominated as a 2025 Woman of Impact by the American Heart Association, a reflection of her leadership and influence in healthcare innovation.

GEn1E Lifesciences

GEn1E announced the appointment of Dr. Francois Nader, MD, MBA, as Chair of the Board, bringing world-class leadership to their mission of developing precision therapies for inflammatory diseases. The company has made remarkable progress on its lead therapeutic compound, GEn-1124, targeting acute respiratory distress syndrome (ARDS) advancing from early discovery to Phase 2 in just 2.5 years with seed capital and non-dilutive support from BARDA. GEn1E is also advancing its oral formulation for chronic care, with Phase I trials set to begin soon.

Acante

Acante launched the first-ever AI copilot for data access governance on Snowflake, setting a new standard for secure, scalable enterprise data compliance.

Atmosic Technologies

Atmosic teamed up with AONDevices to unveil an AI-powered, energy-harvesting remote for the smart home, and appointed Ali Foughi as CEO to lead their next stage of growth in ultra-low-power wireless innovation.

Mext.AI

Mext.AI has launched its new website and blog series, offering a fresh perspective on solving modern memory challenges from multi-tier architectures to AI-driven prediction.

WHAT WE’VE BEEN UP TO

It’s been an exciting few months of connection, collaboration, and continued learning. Clear Ventures Partner Rajeev Madhavan joined a panel at TechCon SoCal 2025, sharing his perspective on why deep operational experience matters in early-stage investing. We were also thrilled to hear former DeepTech Fellow Merve Cerit featured on the Wide Walls podcast, where she discussed her Stanford research on AI and mental health. And at Stanford’s largest-ever Demo Day, Clear Fellows helped organize and pitch among a talented group of founders, showcasing the kind of community-driven innovation we’re proud to support.

Thank you for being part of the Clear Ventures community. As we head into the second half of the year, we’re energized by the momentum across our portfolio and grateful for the support that makes it all possible. Wishing you a restful and inspiring end of summer — we look forward to what’s ahead!

Stay connected: LinkedIn | Medium

As we head into the closing days of 2024, the Clear Ventures team would appreciate a few moments of your time to share our year-in-review perspectives. If you read no further, please know that your friends at Clear Ventures wish you and all those that you hold dear a joyous holiday season and a prosperous new year.

The holiday season provides us with a welcome opportunity to reflect upon the many things that we are grateful for. We are deeply grateful for the extraordinary founders, inspiring portfolio company teams, and supportive limited partners who make our work of helping emerging technology companies win so enjoyable and rewarding. We consider it a privilege and a gift to be empowered to help emerging technology company founders and their teams win.

It is no secret that 2022 to 2024 has been less than ebullient for venture-backed emerging technology companies. Despite the market headwinds, we are pleased to report that all of the Clear Ventures funds produced positive Total Value to Paid in Capital (TVPI) growth for the sixth consecutive year. Inspired efforts across our portfolio companies resulted in a 50% growth YTD24 in the cumulative gains for the Clear Ventures funds when compared to YE23. This continued success, even amidst limited VC market growth, was powered by strong commercial progress across our active portfolio companies which drove 22 successful follow-on financing rounds since last summer. The Clear team also added 4 new portfolio companies in 2024 that we are very excited about. While these companies are still in stealth mode, we look forward to sharing more about them as they publicly disclose their plans.

Active Portfolio News

AICrete $5M Seed

The Clear Ventures team is thrilled to partner with AICrete as they lead the charge in advancing industrial technology. With this investment, AICrete plans to expand its AI-powered AICreteOS platform, enhance customer support, and launch an AI-driven hardware sensor aimed at revolutionizing production while improving quality control, sustainability, and cost-effectiveness in concrete manufacturing. With research roots in the UC Berkeley Computer Science department, AICrete is combining leading-edge AI and computer vision technology with deep vertical industry expertise to automate and optimize the end-to-end workflow for the global concrete industry. The massive global concrete manufacturing is ripe for a technology refresh cycle. AICrete has quickly established itself as a category-leading company that is commanding 6- and 7-figure contracts from some of the world’s largest and most respected concrete industry multi-national companies.

Cynch AI $25M Series A

Cynch AI is officially out of stealth mode and has closed a $25M Series A. Their neuro-symbolic AI technology is redefining how small business owners get tax and financial advice. The early results speak for themselves. They have served thousands of clients and achieved a seven-digit run rate in just their first year of operation. The Cynch leadership has quickly amassed a formidable team of AI experts and tax/audit/accounting experts with extensive experience at extreme scale at industry leader. Cynch AI was a fantastic fit with Clear’s “AI+X” investment strategy, where X is deep industry domain expertise. The Cynch captive AI platform is enabling tax preparation workflow automation that is giving their team of tax preparers superpowers which directly translate to economic benefit to the thousands of business customers they are already serving.

Evidently $15M Series A

Evidently has secured $15M in Series A funding to improve healthcare provider efficiency, care quality, and reimbursement. Founded by Dr. Feng Niu, whose previous venture Lattice was acquired by Apple to re-write Siri for Internet scale, Evidently addresses fragmented healthcare data with its cognitive AI platform. Acting as an AI resident, the platform synthesizes complex patient data into actionable insights. Beyond providing medical practitioners with expert clinical decision support, Evidently is using AI to understand and optimize the end-to-end workflow required to deliver patient care. Evidently is already making a substantial, highly measurable, positive impact on the top and bottom line at leading health systems such as the University of Iowa.

Wherobots $21.5M Series A

Wherobots has raised $21.5M to transform geospatial data analytics. Founded by the authors of Apache Sedona — a widely adopted open-source geospatial compute framework with over 40 million downloads, Wherobots has launched the industry’s finest fully managed cloud platform to make geospatial analytics at Internet scale easier and more cost effective than ever before. The Wherobots team continues to push the boundaries of what’s possible in modern data and AI ecosystems. Learn more here. Wherobots has been a satisfying collaboration for the Clear team. Like Evidently above, the investment was thesis driven and proactively sourced.

Concentric AI $49M Series B

Concentric AI is addressing the data security and posture management challenge faced by intelligent enterprises. Their platform uses AI to catalog critical data across various storage locations, automatically identifying and securing sensitive information in both structured and unstructured data across on-premises and cloud environments. It has been impressive to us to see Concentric grow from a concept and a bold idea by the founders into a robust growth engine with marquee customers across the world and across industry segments. In 2024 whenever Concentric was compared side-by-side with the various alternatives they consistently left with the order. This recent Series B financing is an important acknowledgement of a hard job well done. It has been great for us to see Concentric transition from an evangelical founder-led early sales campaign to a robust reference deployment sale by an exceptionally skilled sales and marketing team.

Frore Systems $80M Series C

Frore Systems has raised $80M in Series C funding to commercialize its innovative AirJet active thermal management/cooling devices, including the newly introduced waterproof AirJet Mini Sport. Designed for space-constrained devices like smartphones, the AirJet offers efficient cooling in extremely space constrained environments by removing heat from processors at speeds of up to 124 mph, while also addressing issues like the boundary layer that traditional fans struggle with — all without generating noise. The AirJet Mini Sport, with its IP68 rating, enables compact devices such as smartphones and action cameras to achieve up to 80% performance boosts while remaining dustproof, waterproof, and silent (learn more about their new product release). Frore Systems began volume shipments of their generally available products in 2024. The current customer base promised to deliver large growth in 2025 and beyond.

Arrcus $30M Series D Extension

Arrcus, a leader in hyperscale networking software, has secured a $30M investment to expand its platform and accelerate growth. The funding will support the Arrcus Connected Edge (ACE) platform, which provides high-performance, scalable, and flexible networking solutions for data centers, 5G, edge, and multi-cloud environments, with a focus on AI and compute-intensive workloads. The financing was led by Nvidia. It has been great for us to see the collaboration with Nvidia make great strides in bringing high performance networking to their AI data center solutions.

Other Milestones

Ospera x Databricks Partnership

By integrating Opsera’s Unified DevOps platform with Databricks cutting-edge Data Intelligence capabilities, they are ushering in a new era of AI/ML-powered software delivery, driving faster, safer, and more intelligent deployments across industries.

GEn1E Publication in the Journal of Pharmacology and Experimental Therapeutics

GEn1E’s work brings new hope for precision therapies targeting inflammatory and autoimmune diseases. Their approach to modulating kinase pathways pushes the frontiers of immunomodulatory therapeutics to enhance patient outcomes.

Atmosic Unveils the Ultra-Low-Power ATM34/e System-on-Chip

This latest chip in Atmosic’s ATM series is compatible with Zigbee, Thread, and Matter, enhancing smart home and IoT interoperability. Prioritizing sustainability, the ATM34/e delivers exceptional performance while reducing energy consumption.

An Introduction to Some of our New Investments

Vori is the only modern B2B operating system for the grocery industry. Their technology seamlessly connects data across the food supply chain, streamlining operations for grocers and suppliers while democratizing food supply access. Led by Brandon Hill (CEO), Tre Kirkman (CPO), and Rob Pinkerton (CTO), Vori’s leadership team combines visionary strategy with technical expertise to transform how the grocery industry operates. Learn more here.

CloudFabrix is revolutionizing IT operations with its Modern AIOps Platform and Robotic Data Automation Fabric (RDAF), which unifies observability, AIOps, and automation to deliver enriched, actionable data across operational and analytical systems. By empowering IT and business leaders with AI-driven insights, CloudFabrix accelerates decision-making, IT planning, and autonomous operations. Led by a team of seasoned innovators, including CEO Raju Datla, CloudFabrix combines deep expertise in AI, data automation, and IT strategy to drive transformative results for its clients.

New stealth startups…will be announced soon!

Welcoming Tina Cho to the Clear Family

Tina joins us as an Associate. She will focus on identifying investment opportunities and providing operational support to portfolio companies in areas like talent acquisition, go-to-market strategies, and fundraising. With an impressive background in product marketing and growth roles at high-growth startups, Tina brings a wealth of experience in early-stage technology venture investing and emerging technology company building. Tina’s prior experience as a product leader at Kustomer (acquired by Meta for $1B) is a great fit for Clear’s commitment to be measurably helpful to the founders who choose to work with as an invited guest in their entrepreneurial journey. Read why Tina chose to join Clear Ventures here.

What We’ve Been Up To In 2024

The Clear Ventures team has hosted a variety of networking and speaking events in 2024, fostering a dynamic and collaborative investment ecosystem to support innovation and growth.

Clear Ventures Hosted Events:

Sponsor of Stanford Young Alumni Event

We were thrilled to sponsor the Stanford Young Alumni event and to reconnect with so many friends. It was an inspiring evening filled with dynamic discussions about the future of Stanford and the announcement of the new president, Jonathan Levin.

Spring CxO Social

This year, we hosted our Spring CxO Social in San Francisco, bringing together technology executives, researchers, startup founders, venture investors, and security professionals to exchange ideas and foster collaboration.

AI Unleashed: Shaping a Trustworthy Tomorrow

In April, we hosted “AI Unleashed: Shaping a Trustworthy Tomorrow” at UC Berkeley, where over 150 technologists, founders, and researchers gathered to discuss AI Safety, focusing on open-source initiatives, academic-industry collaboration, and AI alignment.

Starting a Company as a First-Time or Immigrant Founder

In March, we hosted the “Starting a Company as a First-Time or Immigrant Founder” event, featuring a panel of experts including Kumar C. of Opsera, Parham Aghdasi of AICrete, and Rajeev Madhavan of Clear Ventures. The event focused on key legal frameworks and strategies for startup success, offering valuable insights and lessons for first-time and immigrant founders.

Chris Rust: Building Great Companies in the AI Epoch

Clear Ventures Partner Chris Rust spoke at LEAP24 in Riyadh, Saudi Arabia, sharing insights on building successful companies in the AI era, including strategies for identifying high-growth markets and creating compelling visions. His keynote presentation, part of the “Developing Disruptors” segment, emphasized the key role of venture capital and angel investors in driving tech innovation. He greatly enjoyed this special opportunity to spend time in this dynamic and fast moving area.

Rajeev Madhavan: Fostering Collaboration between USA & India for Semiconductors

Clear Ventures Partner Rajeev Madhavan was a featured speaker at the iChips event with TiE Silicon Valley and the VLSI Society of India. The “Fostering Collaboration between USA & India for Semiconductors” panel highlighted our semiconductor investments in Atmosic Technologies, Avicena Tech, and Frore Systems, showcasing innovative advancements in battery-free IoT, optical interconnects, and thermal technology.

Special Shoutouts

CxO Council

Clear has created a dedicated Council of C-Suite technology executives to provide valuable insights and support to our portfolio companies, focusing on business models, go-to-market strategies, and key introductions. A big thank you to the 2024 CxO Council for an incredible year of collaboration!

Clear Fellows

We want to give a big shoutout to both the Spring and Fall ’24 Clear Ventures DeepTech Fellows. This six-month program is designed to connect high-performing PhD candidates and post-docs with aspiring company builders from top universities and tech companies in Silicon Valley. Both cohorts brought incredible passion, ideas, and a collaborative spirit that truly elevated the Fellowship.

A “CLEAR” Vision for 2025

As we close out an incredible 2024, we’re already looking ahead to what’s next. Stay connected by following us on LinkedIn for updates, insights, and announcements. And here’s to a new year filled with transformative opportunities, groundbreaking innovation, and shared success for you and your ventures!

How would you describe working at a startup? Dynamic is one idea, although I don’t think a single word can do the experience justice.

When I first stumbled upon the startup world, I was a fresh Yale graduate with zero practical skills. I had an unsettling deer-in-the-headlights look that permanently froze in place once I realized that our co-founder would be traveling all the time, and I would have to Google what my job was.

Six more years in the so-called startup trenches, and I began to get a better sense of what makes a startup successful and less anxiety-provoking to work for. Call it Stockholm Syndrome, but each startup felt like it was teaching me an important truth about life, and this kept drawing me back to startups.

Are VCs Supernatural?

Yet, despite all that I learned, getting the next round of funding remained a complete mystery. In my mind, VCs were mythical creatures who descended from heaven and graced you with their presence only when the stars aligned. It puzzled me to think that something so essential to a business’s survival could be that elusive.

This all changed when I began my MBA at UChicago Booth. As part of the PE/VC Lab class, a crash course on VC fundamentals, I had the opportunity to meet the Clear Ventures team and get hands-on experience from the other side of the table. And it didn’t take long for me to realize that Clear was the place I wanted to build my post-MBA career.

Reason #1: The Team

Clear’s founding partners, Chris Rust and Rajeev Madhavan, are founders themselves, and it shows. I’ve seen them offer sage advice that only someone who’s been through the wringer can give, whether it’s negotiating a financing round with a new investor, keeping employees motivated while bouncing back from a tough quarter, or navigating shifting macroeconomic conditions. I have seen firsthand how critical co-founder leadership is to a company’s long-term success, and Chris and Rajeev exemplify the kind of leadership that inspires confidence.

The rest of the Clear team is equally impressive. My colleagues are not only incredibly smart and accomplished but also kind and collaborative. I love that, in a way, Clear feels like a startup itself — everyone wears multiple hats and is tied together by the mission of supporting the brightest technical founders of our time.

Reason #2: Game-Changing Technology

Another reason I chose Clear is because of Clear Connect, our proprietary AI tool that helps founders in ways I have not seen other VCs replicate. Many funds are hands-on, but Clear takes it a step further to systematically amplify key growth drivers like talent acquisition, sales, and follow-on financing. This isn’t just a buzzword; it’s a tangible, results-driven approach that founders can rely on.

I have seen Clear Connect in action, helping portfolio companies hire talent across various levels and functions — from SDRs and VPs of Sales to Chief Product Officers and Directors of Engineering.

There have been multiple cases where we directly contributed to revenue, including generating 80% of a company’s first-year sales pipeline and helping CEOs identify and close lighthouse accounts.

That level of operational support makes a profound difference, especially for first-time technical founders.

What Will I Do At Clear?

I’m happy to report that my job here is way less ambiguous than my first. As an Associate, I focus on two key areas: new investments and portfolio services. I meet with founders who are driving innovation in deeptech, which basically means that I get to meet people way smarter than me all the time. Luckily, I became accustomed to that during my time at Yale, and although intimidating, it’s the best way to grow.

I also partner closely with founders in our existing portfolio to help them with talent acquisition, go-to-market, and fundraising. Drawing on my product marketing background, I will add new services to our offering such as messaging and positioning, sales collateral development, graphic design, and sales automation, addressing critical go-to-market needs during the early stages of company building.

Looking Forward

It’s an incredibly exciting time to be in venture capital. Every day brings a new AI model or breakthrough that fundamentally changes how we live and work. If you’re a founder building in the Bay Area, a VC in deeptech, or an herbal tea fan, say hello on LinkedIn!

About Tina, Associate at Clear Ventures

Tina is an integral member of Clear’s Investments & Portfolio Services team, where she identifies promising investment opportunities and collaborates with Clear’s in-house engineering team to support founders in talent acquisition, sales, and follow-on financing. Tina also plays a pivotal role in driving Clear’s ecosystem and marketing initiatives.

Tina brings a wealth of experience from her extensive background in product and growth roles at various high-growth, early-stage startups in New York, including ROOM (acquired by OFS) and Kustomer (acquired by Meta). At Meta, she worked as a product marketer on the Business Messaging team, developing go-to-market strategies for new products and offerings. Tina’s early-stage investing career began at Origin Ventures, where she specialized in vertical SaaS investments.

Originally from South Korea, Tina holds a BA in Political Science from Yale University and an MBA from the University of Chicago Booth School of Business.

The conclusion of the work year gave the Clear Ventures team a welcome opportunity to reflect upon the many things we are grateful for. Our gratitude goes out to the many gifted founders who chose to work with Clear Ventures as a founding investor, and to our investors who entrusted us with capital to invest on their behalf. Without further ado, our 2023 Annual Update:

Winning Active Portfolio

Despite the macro market headwinds this past year, 2023 has been ‘good-busy’ at Clear Ventures. We are pleased to share that Clear portfolio companies closed a dozen follow-on financing rounds in the second half of 2023. Every Clear Ventures fund is finishing 2023 with positive growth in the total value-to-paid in capital (TVPI) versus Year-End 2022.

This is the fifth year in a row that each Clear Ventures fund has seen the realized and unrealized profits grow nicely versus the prior year. The follow-on financing successes in 2023 were well-earned validation of the outstanding work done by our portfolio company teams. We invite you to read more about select fundraising announcements below:

• Arrcus snaps up $50M for a software-based alternative to costly network router equipment | TechCrunch
• Espresa Raises $23 Million Series A Funding to Transform Personal Benefits for Global Workplaces
• Opsera Announces Series A Plus Round to Power New Generative AI Initiatives
• Kognitos raises $20M to help businesses automate back-office processes | TechCrunch

An Introduction to Our New Investments

Chkk

Chkk has emerged from stealth mode! Keeping clusters up and running is critical for DevOps teams. Chkk was founded to ensure the resilience of your Kubernetes infrastructure. With 3 founders (Awais Nemat, Fawad Khaliq, and Ali Khayam), 15 employees, and a remarkable $5.2 million seed investment, they are thrilled to be launching and making their platform generally available. Read more.

Cynch.AI

Cynch.AI is a vertical SaaS company that leverages AI to deliver workflow automation for the tax, accounting, and audit industries. This massive $300B-a-year revenue industry operates on legacy client-server software applications and spreadsheets and is ripe for a technology refresh cycle. Dr. Nigel Duffy founded Cynch; Nigel earned a Ph.D. in CS from UCSC and is a highly regarded AI expert with over 6,000 citations of his refereed journal publications. Before Cynch.AI, Nigel spent the past half-decade as the AI CTO of Ernest & Young, where he built a 300-engineer AI team from the ground up.

New Stealth Startups…

…will be announced soon!

Portfolio Company Milestones

AICrete Milestones: One Year In! In under a year, the AICRETE team has: Completed 14 successful proof-of-concepts with concrete producers across 10 US states and achieved an average savings of $2.64 per cubic yard of concrete. Reduced CO2 by an average of 40 lb per cubic yard. Optimized over 1.1 million cubic yards of concrete. Avoided 22,855 tons/yr of CO2 — equivalent to removing 4,614 cars from the roads or adding 24,725 acres of US forest! And the cherry on top? Seven leading ready-mix companies have joined AICrete’s Founder’s Club, pioneering the future of concrete operations. View their LinkedIn video here.

“We are thrilled to witness the rapid adoption of Arrcus, Inc.’s networking solutions in Japan for 5G and data center routing and switching built on our industry-leading ArcOS platform,” said Shekar Ayyar, Chairman and CEO of Arrcus. “As we continue to revolutionize networking infrastructure, our focus remains on delivering cost-effective and highly performant networking solutions.” Learn more.

Atmosic won another award, beating the new Bluetooth silicon released by Silicon Labs (BG27) and the new Wi-Fi 6 chip from Nordic. They did this with the ATM33…The Elektra Award is a prestigious electronics industry recognition celebrated in the famous London Grosvenor House Hotel. See the award video here.

Atmosic Technologies’ energy-saving technology is now in Samsung’s GalaxySmartTag2. The newest version of the Tag now offers a longer range, enhanced security, and significantly longer battery life! We’re excited to see where Atmosic’s technology goes next.

Nick Dutton, Senior Director of Product Marketing at Atmosic Technologies, joined Ryan Chacon on the IoT For All podcast to discuss some of the following IoT hot topics: Low-power IoT, reducing battery waste, improving sustainability, and competing in IoT. Watch here.

Concentric AI has won the prestigious Sinet16 Innovator Award. Sinet16 recognizes the 16 most innovative cybersecurity companies globally, and Concentric’s cutting-edge approach to data security posture management and access governance has earned them this well-deserved honor. Their deep learning technology is a game-changer, automating sensitive data discovery and risk mitigation.

Concentric AI Founder, Karthik Krishnan, joined host Paul Shomo on the Genealogy of Cyber Security podcast to explore the frontiers of generative AI, large language models, and their applications to data security. This is a great episode to listen to if you ever wonder what data you have, where your data is, and who’s accessing it. Listen here.

Evidently is thrilled to introduce their newest team member, Kalie Dove-Maguire, MD, who will be their Chief Product Officer! Learn more about Kaile here.

Frore Systems has been hard at work creating the newest way-too-cool electronics. Their efforts have not gone unnoticed; they were recently highlighted by TheVerge, Tom’s Guide, and Macworld.

The AirJet Mini has been selected as one of the Golden Award winners in this year’s Best Choice Award 2023. Congratulations to the Frore Systems team on this achievement! More here.

Forbes shared an excellent summary of Frore Systems’ impressive year. Congratulations on all the big wins so far. Read here.

The Flash Memory Summit presented the Frore Systems team with the Most Innovative Startup Award. Congratulations to Seshu Madhavapeddy and the entire team on the well-deserved recognition of success!

In January, Gen1E hired Dr. Sham Dholakia as their chief medical officer. Sham leads clinical development and comes to the company as a highly accomplished transplant surgeon, trained at the University of Oxford. Sham most recently served as the CMO of CareDx.

Congratulations to the Kognitos team on the exciting Self-Service and Human Language Interpreter 2.0 launch! This is the team’s biggest product release to date and it takes all the technical hurdles out of business process automation. “The goal is to bring this power to a billion business users. That’s our end goal and that’s our vision,” says Founder and CEO Binny Gill. Read more here.

Congratulations are in order! Opsera has been spotlighted by Tracxn as one of the “Minicorns” in emerging DevOps startups of 2023. Can’t wait to see what 2024 has in store for this impressive team.

Opsera welcomed Patty Hatter as President and Chief Operating Officer this year. Patty brings experience to help scale and grow the Opsera DevOps platform among enterprise engineering teams. Learn more about Patty here.

Gopi Prashanth, Founder of Fit Hub (powered by Spyn), has an incredible journey to share — from discovering AmazonGo to transitioning from Agritech and E-Commerce to becoming a Fitness Platform Founder. Listen to his guest appearance on The Tech Factor Podcast to learn more about Gopi, entrepreneurship, how he’s revolutionizing fitness through Generative AI, and his experiences as a serial investor.

As a busy tech entrepreneur and father, Gopi Prashanth experienced the struggle of finding time for workouts and meditation. That’s why he founded Fit Hub (powered by Spyn). It’s an AI-powered chatbot that creates personalized fitness and meditation routines based on your preferences and limitations. Learn more here.

Exciting news coming from Wherobots.ai HQ. They’ve launched SedonaDB, a “full-fledged cloud database platform designed from the grounds up to support spatial analytics and AI on data at any scale.” Read more on their blog.

Wherobots is growing! Maxime Petazzoni joined their team as the new Head of Engineering. Read more about Maxime here.

Clear Ventures Team Updates

For the last couple of years, Clear Ventures has quietly built out ClearConnect — the world’s first AI-based, VC Operating System (VCOS). ClearConnect uses leading-edge data science to algorithmically empower the Clear Ventures team to provide portfolio companies with highly differentiated access to qualified customers for sales acceleration, outstanding talent sourcing for recruiting success, and process management for follow-on financing success.

Developed as a strategic catalyst to help gifted technical founders win in DeepTech investment areas such as AI, intelligent enterprise, and vertical SaaS, ClearConnect is setting a new standard for VC portfolio value-add. In July the firm was pleased to announce several promotions to deserving team members Noor Kamruddin, Zach Poley, Somnath Banerjee, and Khalig Howard. You can read more about these responsibility changes here.

Join us in welcoming Ghita Houir Alami, our new AI Engineer, to the Clear Ventures family! Ghita is poised to make a significant impact at Clear, bringing a wealth of knowledge and experience in the field of artificial intelligence. She is playing a key role in shaping our operating system, ClearConnect, which leverages AI to make sense of vast amounts of data, enhancing our decision-making processes and providing valuable support to our portfolio companies. Together, we’re on a mission to empower founders and drive innovation! Read why Ghita decided to join Clear Ventures here.

Somanth became a valuable addition to Clear earlier this year, assuming the role of Partner and Head of Data Science. Since his arrival, he has made a remarkable impact on our team, and we are truly grateful to have him on board! Learn more about Somnath and his decision to join Clear Ventures here.

What have we been up to?

LLMs in Enterprise Event

In January, we hosted a group of 25 distinguished founders, industry practitioners, researchers, and technologists who are shaping the future of the Generative AI Space. We discussed topics such as: who are the gatekeepers to enterprise adoption of foundational models? And, what tools and technologies can be adopted to help stakeholders feel comfortable with security, compliance, and trust concerns?

AI Trust and Safety Event

The Clear team led a roundtable discussion on opportunity areas within AI Trust and Safety at the end of April.

Annual Summer Party

After a brief hiatus due to the pandemic, we were thrilled to revive our Annual Summer Party. This year’s event at Filoli Gardens boasted a fantastic turnout, and we hope to see all of you again for another unforgettable celebration in the Summer of 2024.

ClearConnect Series: InfoSec Meetup

At the end of August, the Clear team hosted an InfoSec meetup with CISOs, VPs of Cybersecurity, Directors of Enterprise Security, and PhDs as part of our ClearConnect Series. We opened with a keynote on applied cryptography for arms control from Neil Perry, a Hoover Institute Fellow and Stanford PhD student. Then, had roundtable discussion where we touched on security concerns in modern software systems, LLMs; and how they might represent vulnerabilities and enable good/bad actors in security contexts. Leadership from Acante, Blueteam.ai, Contextual.ai, and Concentric AI were in attendance to share more about the innovative solutions they are building to protect digital assets and core infrastructure, and they offered some fresh perspectives to the security leaders in attendance.

Spring and Fall Demo Days

We filled the office with excitement during our Spring and Fall Demo Days this past year. These showcases provided our community with a unique opportunity to witness the innovative startups crafted by our DeepTech Fellows, former employees, and friends of the firm. Entrepreneurs presented vertical AI applications, enterprise data management, digital health transformation, and mental well-being startups.

DeepTech Venture Fellows

Clear Ventures has hosted over 50 MS, PhDs, and Postdocs from elite schools such as UC Berkeley, Stanford, CMU, UW, and UCSD through our DeepTech Venture Fellowship program. Since the program’s start in 2022, Clear Fellows have produced 11 startups, raised $24.1M in VC Funding (pre-seed/seed), and earned leadership positions at NVIDIA, Google Brain, and MAIR Research Organizations. Our Fall 2023 cohort consists of 14 bright minds, and we are excited to get to know each of them!

Aspiring to be a Hub of Innovation

A highlight for the Clear Ventures team in 2023 has been the opportunity to have several portfolio companies working out of our Palo Alto office. The opportunity for us to get to know the capable startup teams at Acante, Concentric.AI, Evidently, Opsera, and others better while working out of the same space has been a very special experience.

Our team has gotten efficient at re-configuring our humble office for tech talks, meetups, classroom-style training, portfolio company business development events, and all manner of fun events to be measurably helpful. Having all of our furniture on wheels has proven to be useful!

From the Desks of Our Partners

• Traits of Founding Teams That Win — An IT VC’s perspective
• Why I Joined Clear Ventures: Supercharging Venture Capital with AI
• Revolutionizing Web Scraping: A Leap Forward with Multimodal Language Models
• Handy tips for LLM application developers
• How digital twin technology can bridge America's chip manufacturing gap
• The CHIPS Act Helps the Wrong Companies

Interested in why we have invested?

• Why Clear Invested in Wherobots: The Cloud Platform for Geospatial Data and AI
• Traditional RPA — A Wasted Effort?
• Why We Invested in Frore Systems? Making Moore’s Law Scale!

We wish you and all those that you hold dear a happy, healthy, and prosperous new year.

Keep up to date with us! LinkedIn.

In my lifetime, I’ve been fortunate enough to develop a strong perspective on technology, culture, and entrepreneurial innovation. I grew up in Morocco and, thus far, have lived on three different continents! However, being here, in the San Francisco Bay Area/Silicon Valley, is a truly exceptional experience for any technologist.

Undoubtedly, this is the best place on earth to be involved in the AI field. While getting my MS in applied mathematics and machine learning from UC Berkeley, I was part of numerous communities focused on frontier technologies and entrepreneurship. Participating in these groups allowed me to meet with people with impressive technical skills and an unrivaled pioneering spirit.

In the past 24 months, I have seen the profound potential of AI in reshaping industries: from healthcare, where AI-driven diagnostics are spotting illnesses with unparalleled accuracy, to finance, with algorithms successfully predicting crowdfunding campaigns’ success. At Clear, I now witness firsthand how AI-driven solutions fuel our venture investment practice and our portfolio companies’ success. Playing a crucial part in our collective efforts around research, tool development, and innovative problem-solving approaches is so exciting.

In joining Clear Ventures as an AI Engineer, I became part of a mighty, fast-paced, and innovative development team, leveraging the latest AI technologies to build our Venture operating system, ClearConnect. That said, I am not just working as a traditional Engineer; this role has allowed me to be part of a team of experienced Venture Capitalists revolutionizing their industry through a unique data-driven approach, participating in diligence calls, reading the latest papers, and delivering value to our companies and LPs.

Clear is truly transforming venture capital through its work on the first AI-powered Venture Capital Operating System. Disrupting traditional manual Venture Capital investors’ workflows, we leverage AI to make sense of vast volumes of data. This approach allows us to make informed internal decisions and keep up with the litany of work spilling out of the country’s best research labs.

I am overjoyed with how the tools we are developing delight the Clear Ventures portfolio management teams. Giving them superpowers to support efforts around hiring, finding customers, and raising additional funding.

This opportunity at Clear Ventures offers me the best possible learning experience following my graduation from Cal Berkeley and Ecole Polytechnique, as it lies at the strategic intersection of VC, product development, AI, and startup incubation. I’m thoroughly impressed by the product Clear has been developing and eagerly anticipate contributing to it. This experience gives me a sneak peek into the world of early-stage venture investment. It is an education on becoming a successful entrepreneur, which I hope to be in the not-so-distant future.

I’m deeply grateful to everyone at Clear who made this opportunity possible, and I feel honored to join such an inspiring team.

About Ghita Houir Alami

Ghita Houir Alami is an AI Engineer at Clear Ventures, where she works on integrating Large Language Models (LLMs) and AI capabilities into ClearConnect; Clear’s proprietary AI-powered venture capital operating system. Ghita is also responsible for helping drive increased access to customers, talent, and access to follow-on financing for Clear portfolio companies.

She developed her deep learning skill set from professional experiences and research projects where she was responsible for building, training, and evaluating vision and language models. Her computer vision knowledge was refined during stints as a researcher at a French startup Milvue, and the University of San Francisco, California (UCSF) Neurology Lab. Ghita’s NLP skills were honed while working on Alter, an LLM-based productivity application company she co-founded.

Her academic journey started with two years in a renowned scientific program in France, after which she was accepted to Ecole Polytechnique, France’s premier university in the fields of science, mathematics, and engineering. At Ecole, Ghita led several strategic initiatives and teams, managing an annual budget of ~one million euros.

Ghita holds a BS and an MS from Ecole Polytechnique in applied mathematics and data science, and an MEng from UC Berkeley, with a specialization in applied mathematics and machine learning.

Ghita has lived in 4 different countries across 3 continents and speaks 5 different languages. When she is not working, she enjoys spending time with her family and friends, reading, and listening to jazz music.

Unveils ClearConnect — The First Deep AI-Based VC Operating System

It is common knowledge that artificial intelligence (AI) and big data analytics are revolutionizing the world by giving individuals and enterprises new superpowers to accelerate their success. No industry is immune from this disruptive mega-trend. At Clear Ventures we believe the traditional word-of-mouth-based venture capital (VC) model is ripe for a technology refresh cycle as well.

For the past several years, Clear Ventures has quietly been investing heavily to build ClearConnect — the world’s first AI-based, VC Operating System (VCOS). ClearConnect uses leading edge data science to algorithmically empower the Clear Ventures team to provide portfolio companies with highly differentiated access to qualified customers for sales acceleration, outstanding talent sourcing for recruiting success, and process management for follow-on financing success. Developed as a strategic catalyst to help gifted technical founders win in DeepTech investment areas such as AI, the intelligent enterprise, and vertical SaaS, ClearConnect is setting a new standard for VC portfolio value-add. Today the firm is pleased to announce the following promotions to acknowledge excellence in early-stage deep technology venture investing, post-investment partnering via Clear Portfolio Services, and ClearConnect software development:

• Noor Kamruddin has been promoted to Partner, Investments and Operations.
• Khalig Howard has been promoted to Principal, Investments and Portfolio Services.
• Zach Poley has been promoted to Partner and Chief Technology Officer.
• Somnath Banerjee has been promoted to Partner and Chief Data Scientist.

According to Clear Ventures Founding Partner Christopher Rust, “Clear Ventures was founded with an unwavering commitment to cultivating top talent within the portfolio and within the firm. Having worked and collaborated with hundreds of people in the venture capital industry since joining Sequoia Capital in 1998, and later founding Clear in 2014, I have been fortunate to team up with some of the very best talent in the history of the VC asset class. At Clear, our team synergy, collaboration, and productivity bring joy to all that we do each day to help founders win. As demonstrated by Clear portfolio company Concentric.ai recently being named a 2023 top 10 AI company by CRN Magazine and Kognitos winning Ventana Research’s Prestigious Digital Innovation Award, Clear Ventures has been heavily focused on AI and DeepTech well before the current hype cycle. A key difference between Clear and others is we strive to help create opportunity rather than pick winners. We are investors in, and heavy users of, GenAI and LLMs. Our in-house use of generative AI and large language models are core elements of ClearConnect and Clear Portfolio Services. These well deserved promotions for Noor, Khalig, Zach and Somnath acknowledge their outstanding contributions to ClearConnect, Clear Portfolio Services, our portfolio companies, and our esteemed investors. Their efforts on sales acceleration, recruiting, and strategic planning have earned accolades from our portfolio company leaders.”

Investment Team and Partner Promotions

Noor has been promoted to Partner, Investments and Operations. She has been an active contributor to the Clear Ventures investment team sourcing, screening, and post-investment value-add since joining the firm in 2019. She is responsible for the Clear Ventures investments in Kognitos with former Nutanix Cloud CTO Binny Gill and Gen1E with Dr. Ritu Lal. She contributes broadly to the firm’s diligence and post-investment portfolio management efforts.

Khalig Howard has been promoted to Principal, Investments and Portfolio Services. He sourced Clear’s investments in Visla with former Zoom Chief Scientist Dr. Huipin Zhang, and Evidently AI with former Lattice/Apple and Alation founder Dr. Feng Niu. His measurable value-add across the Clear portfolio with qualified introductions to customers, talent for recruiting success, and follow-on financing efforts help the Clear portfolio reach its full potential each day.

Although Clear Ventures has been low-key about promoting its use of data science, Clear has built formidable captive software assets that turbo-charge its frontier technology VC practice. Just last quarter alone ClearConnect and Clear Portfolio Services sourced, screened, and helped close 19 of 35 key hires across the active Clear portfolio. One portfolio company alone secured over 40 customer meetings that were algorithmically sourced using ClearConnect.

Zachary Poley has been promoted to Partner and Chief Technology Officer. Zach is a highly skilled full-stack software engineer and architect with specialized expertise in skills-based people search. Zach’s seminal contributions to Clear’s internal software development efforts cannot be overstated.

Somnath Banerjee has been promoted to Partner, Chief Data Scientist. Somnath is a widely recognized data science guru who made substantial contributions to high-volume websites such as Pinterest and Walmart.com. Somnath has contributed key expertise on search, generative AI, and the use of large language models to take Clear’s internal software development efforts to the next level.

Rajeev Madhavan, Clear Partner, and Co-Founder said this about the promotions and Clear’s data-driven approach: “With the power of AI, we have the agility to quickly identify gifted talent, navigate markets with unprecedented foresight, and deliver results at a pace that hasn’t been possible before. Over the last half decade, we have repeatedly been the founding VC to gifted technology entrepreneurs. As we see it, AI changes everything and ClearConnect is our game changer. It will ensure we’re at the forefront of this as we push the boundaries of innovation and build a future that’s rewarding for our team, our portfolio companies, and the VC community at large.”

Engineering — A Data-driven Approach to Venture Investing

Data-driven strategies are becoming increasingly essential for investment decision-making. Founded by serial tech entrepreneurs, Clear has long recognized the need to understand and harness the power of data to identify emerging trends, uncover high-potential investment opportunities, and make informed, first-mover-advantage decisions for our portfolio companies.

According to Zach Poley, Partner and CTO, “Unlike other VC firms, we do more than just provide funding to startups. We help them build the company from the ground up — we’re writing software and engineering our own solutions to problems which enables us to streamline solutions to a more complex set of problems vs cobbling together a stack of off-the-shelf solutions. I’m thrilled to step into my new role as Partner and CTO. This is a golden opportunity to strengthen and harmonize our collaborative efforts, further fueling our innovative approach to developing the advanced tools and technology platforms that have proven instrumental in driving Clear and our portfolio’s success. The journey ahead is exciting. I look forward to harnessing cutting-edge technology solutions, not only to maintain our winning position in the marketplace, but also to catalyze unprecedented growth and prosperity.”

According to Somnath Banerjee, Partner and Chief Data Scientist: “I too am delighted to see Clear investing in technology and human capital to further support our portfolio companies and I’m honored to get a bigger role in this journey. I am extremely excited to get this opportunity to enhance the AI capabilities of the Clear engineering platform and can’t wait to see how it can help Clear and its portfolio companies achieve even greater success. By investing in our engineering team, leveraging data science and AI, we gain a deeper understanding of companies and individuals. AI provides a unique opportunity to expand our ability to process vast amounts of data, generate actionable insights that are crucial for portfolio companies to engage with their next customers or make critical hires.”

Investments in a Connected World — Making Economies Successful

Understanding market dynamics — and how quickly things can shift and evolve — can make a huge difference in a VC’s success rate. Data now shows that venture-capital-backed companies are a major catalyst for growth in our economy, spurring job growth eight times faster than the overall private sector.

According to Partner Noor Kamruddin, “Venture Capitalists make significant contributions to economies — just think of all the new tech that has now become pervasive in our everyday lives. With my background as an engineer, I’ve had a front-row seat to see how these advancements are changing our world. At Clear, we believe the role of the VC is even more critical today and I look forward to helping Clear play a pivotal role.”

About Clear Ventures

With $335 million of capital from a world-class investor base, Clear Ventures is a Silicon Valley venture capital firm that is purpose-built to help startup teams win in frontier technology and services. Founded by veteran company builders and venture investors Chris Rust and Rajeev Madhavan, formerly of Sequoia Capital and USVP and founders of five successful companies, Clear provides early capital, connections, and company-building insights to bold startup teams so their ideas can grow into market-leading companies.

Everything we do and everywhere we go on the internet today generates breadcrumbs of geospatial data. More than five billion people in the world use mobile devices to buy stuff, interact with friends, access healthcare and bank accounts, get directions, and much more. In fact, some 30 billion connected devices are generating upwards of 100 trillion spatiotemporal data records every year. The problem? About 97 percent of that data sits unused in enterprises, according to a study by Gartner. Wherobots, a Clear Ventures portfolio company, aims to change that situation.

From the Creators of Apache Sedona

Founded by Dr. Mo Sarwat and Jia Yu, the original creators of Apache Sedona, the company is democratizing the development and deployment of the geospatial data processing and analytics stack. The goal? The company wants to enable every organization to extract business value from data via spatial location and time.

Historically, geospatial data has been treated as a second-class citizen, forcing developers to use incumbent databases and infrastructure to make sense of this valuable data. According to Clear Ventures Partner Vijay Reddy,

“Users need fast time-to-value where they don’t have to worry about the hassle of cloud administration, workload scalability, and geospatial processing support/optimization. Wherobot’s AI-based, data analytics solution democratizes the development and deployment of geospatial data processing that could benefit use cases in industries such as logistics, location-based advertising technology, automotive, data-as-a-service, and more. It reinforces our investment thesis of investing in technologies that could have a big impact on modernizing infrastructure.”

Wherobots is developing a product that enables users to easily develop, test, and deploy in-situ geospatial data stack in the cloud or on-prem. Explains Co-founder Mo Sarwat,

“The issue is not just that data is big and available, but rather that enterprises can’t make sense of it without putting the data into context through geospatial location and time. This context allows an enterprise to ask the right questions and drive value from the data.”

Data: From the New Oil to New Currency of Business

A few years ago, the Economist Magazine declared that the world’s most valuable asset was no longer oil, but rather data. Years earlier British mathematician Clive Humby coined the “data is the new oil” phrase by saying that data, like oil, isn’t useful in its raw state. It must be refined, processed, and turned into something useful. Its value lies in its potential. Fast forward to today, and many believe that data is more valuable than oil. CIO.com makes the point that “data is the new currency of business.”

“All of this requires a data platform that treats space and time as a first-class citizen and can perform AI to drive greater insight and value for your enterprise,” explains Mo, who says they are developing a horizontal back-end technology that enables apps or use cases in a range of industries.

Huge Potential — Scale it for Big Data Applications

How big is the market potential? According to Geospatial World, the global geospatial market could reach $1.4 trillion in value by 2030.

According to Vijay, the adoption of Apache Sedona and the fact that the company was started by the original creators of Apache Sedona with a pull from enterprises made the investment in Wherobots highly attractive. Apache Sedona is a distributed spatial analytics platform that provides tools for working with massive amounts of geospatial data in a distributed computing environment — and has already received more than 12 million downloads.

With Apache Sedona, users can easily develop their geospatial data analytics pipeline and scale it to work with large volumes of geospatial data. As an example, it can be used in the automotive industry for applications including mapping and navigation, automotive safety and autonomous vehicles, and logistics and supply chain management.

According to Christopher J. Rust, Clear Ventures Founding Partner, “Our investment in Wherobots was thesis-driven and proactively sourced. The challenge of doing precision geospatial analytics on Internet-scale data sets is a huge unmet need and is directly relevant to our Intelligent Enterprise investment strategy. We were extremely impressed with the achievements of the Wherobots team. As the primary authors of the Apache Sedona project, they have distinguished themselves as global thought leaders in this area. We are grateful to Dr. Sarwat and Dr. Yu for the opportunity to join the Wherobots shareholder base.”

Says Mo, “The next wave of data companies will specialize in a specific aspect of data. At Wherobots, we’re a data company focused on geospatial location data. We are building the data infrastructure that’s going to enable the applications that will transform the world. And we do that by enabling organizations to drive value from data via spatial location and time.”

As hard-core technologists, Wherobots is bringing geospatial plus ‘X’ applications to the world.

Learn more about Wherobots, the data platform for geospatial analytics and AI.

The Wherobots Mission: Democratize the development and deployment of the geospatial data processing and analytics stack.

About Vijay Reddy

Vijay is a Partner at Clear Ventures, where he focuses on early-stage technology investments in AI + X, or AI applied to a specific industry or function. Prior to joining Clear Ventures, Vijay was a Partner at Intel Capital where he has been an early backer of leading AI and DeepTech companies including four unicorns and two IPOs that have raised more than $3.5 billion of capital and are currently valued at about $20 billion.

About Christopher J. Rust

As a founder and General Partner of Clear Ventures, Chris has more than 30 years of experience in management/business development, engineering, and operations and has been the lead investor in more than 35 companies. Prior to closing Clear Fund I in 2016, Chris spent 14 years as an early-stage technology investor at Sequoia Capital and USVP. He also spent 12 years in operating roles as a development engineer, network architect, and product manager.

Chris was a co-founder and Lead Architect of broadband access pioneer Roadrunner, now known as Time Warner Cable Internet. Roadrunner grew to 14 million subscribers, over $4 billion in 2015 revenue, and is the key driver of Charter Communication’s $56.7-billion acquisition of Time Warner Cable.

He earned a B.S.E.E. with distinction as a Massachusetts Board of Regents Honor Scholar and an M.S.E.E from the University of Massachusetts Lowell, and an M.S. Telecommunications Engineering and an M.E. Engineering Management from the University of Colorado, Boulder. While at the University of Lowell he was the recipient of the President’s Medal.

By Rajeev Madhavan, Co-Founder and Partner at Clear Ventures

Has robotic process automation (RPA) lived up to its hype? The RPA market has been booming as organizations are launching their digital transformation initiatives by using software robots or bots to automate routine and repetitive tasks such as data entry, data extraction, and invoice processing. RPA offers compelling benefits: it can boost productivity, efficiency, accuracy, security, customer service, just to name a few. With RPA, companies get to focus on what matters most, higher-value human work — the “bots” do the rest. The promise sounds great, but the reality is quite different.

Up to 30 to 50 percent of RPA projects fail, according to a study by Ernst & Young. And many fail on crucial deliverables: implementation time, cost savings, scalability, and the actual bot automation itself. These implementations often lack a clear strategy and vision and focus on automating specific tasks rather than the bigger picture.

RPA companies emerged from the consulting business as these companies were searching for ways to streamline business processes and reduce costs for their clients. They identified a clear need to use technology to automate repetitive and manual tasks, which led to the development of RPA. They essentially added a software script to automate certain routine, rules-based tasks, then added artificial intelligence (AI) to make the functionality easier, but these solutions are still fundamentally flawed. Consider this: for every dollar a company purchases in software, they may spend nearly 10X that amount to hire consultants/service providers to do the integration. [It is not uncommon for implementation costs to exceed software costs, especially for large complex systems] And when business logic changes — as it always does — they must invest even more in providers to do the automation.

Why do RPA projects fail?

Getting RPA projects right with current technology is difficult — and most companies simply underestimate the cost and complexities involved.

Ernst & Young cite reasons for failed RPA projects including not making RPA a business-led initiative vs IT-led; underestimating what happens after processes have been automated; treating robots as a series of automations vs. an end-to-end program; targeting the wrong processes or automating too much of a process; forgetting about IT infrastructure; and assuming RPA is all that is needed to achieve a great ROI.

But these projects also fail for the reasons below as well:

• The project requires too much complexity — many available RPA tools don’t handle complexity well, especially if there are too many steps required in the process. Forrester analyst Craig Le Clair recommends that traditional RPA be governed by the rule of fives: “No more than five decisions, no more than five apps, and no more than 500 clicks.” In other words, when you get beyond a certain level of decision complexity, the bots become very hard to maintain.
• The project fails to scale, which leads to isolated islands of automation with different departments using different bots, leading to inconsistencies and inefficiencies. Companies often get stuck after deploying only a few bots with up to 50 percent of RPA deployments initially failing. And bots face scaling issues when compared to API integrations — things like the complexity of processes being automated, number of applications and systems that the RPA bot must interact with are all factors.
• Other issues revolve around governance and RPA’s inability to deliver sufficient ROI; management issues once the digital workers are deployed to production; third-party issues because third-party interfaces aren’t uniform (bots are inflexible and don’t respond to variance); unrealistic expectations; shadow deployments; lack of buy-in from employees or resistance to the idea that bots are taking over their jobs — leading to lack of engagement/company culture issues; inability to handle change management, etc. Bots and consulting service teams are often seen as not aiding the business team or IT, but maintaining and managing them is seen as taking away resources.
• When problems occur or automation does not work as intended, the finger-pointing begins. And troubleshooting these issues in high-stress situations such as quarter closings can lead to rushed debugging and even more problems.

The market need

At Clear Ventures, we believe that RPA has not delivered on its promise. The market is ripe for a tool that will not just shift the problem from one department to another — say from finance to IT — but solve the enterprise automation issue and become more efficient with AI technology.

In looking at these challenges, Kognitos reasoned that instead of humans learning to use software, the software should learn to work with humans, giving humans the superpower needs to get their work done. Further, they asked; what if a solution could eliminate the issues that many enterprises today face with current RPA solutions?

• Remove the need for developers and services, thereby lowering total cost of ownership, enabling ever more complex processes to be automated with solid ROI.
• Remove the need for IT staff time to manage “bots.”
• Remove the need for learning yet-another new, complex tool.
• Leverage a tool that automates in plain English — natural language processing and large models applied to the core of the problem.
• Remove the fear that automation will fail — handle exceptions with intelligence like the best service providers can do.
• And allow automation of processes that traditionally were unfit to automate based on RPA best practices. Ultimately, be the Jarvis (Ironman assistant) for humans automating business processes!

Kognitos — addressing one of the biggest challenges businesses face today.

Enter Kognitos, founded by Binny Gill, who had an impressive eight-year run as a technology leader at Nutanix, the hyper-converged infrastructure company, eventually becoming its CTO for cloud services. Binny left Nutanix to start Kognitos based on a bold vision to make everyone a programmer. He created the company to address one of the biggest challenges businesses face today with automation — the lack of skilled personnel in automation. By enabling business users to describe even intricate processes such as invoice processing, insurance claims, credit card payment reconciliation, in English, Kognitos aims to radically accelerate the speed of innovation and time to value in businesses by reducing both the time and resources required to automate and maintain processes.

Kognitos is assembling a world-class team of enterprise sales leaders and process automation experts from leading customers or RPA solutions. The team is well-equipped to deliver on their promise of making everyone a programmer.

Further, Kognitos is working on enabling businesses to build their own personal “ChatGPT” for business process data that is private to the organization. In particular, the company’s solution will make processing data across multiple applications possible. This will ultimately unlock higher-level insights and over time improvements in business processes in a virtuous cycle of innovation and automation.

In early February, Clear Ventures led the oversubscribed $7.4 million seed round of financing for Kognitos, a pioneer in Generative AI for Automation using large language models (LLMs) such as GPT3 and ChatGPT, along with participation from Engineering Capital and Wipro Ventures, the corporate arm of Wipro. The company will use this funding to grow their marketing, engineering, and applied foundation model research functions.

“Current day automation tools require significant involvement of IT and service providers to use the no code/low code solutions. Kognitos has built a platform that allows the people who know and own business processes to combine business logic and Generative AI leading to rapid automation — all in English,” said Rajeev Madhavan, Co-Founder and Partner at Clear Ventures.

Kognitos is unlocking the power of AI for humanity with its generative AI platform — Koncierge. Says Binny, “Now every person will be able to use Generative AI for automating what they want — utilizing the English language. It’s time for computers to behave like humans, and humans to stop behaving like machines.”

Listen to Binny Gill discuss how LLMs like ChatGPT are making us all programmers, on the podcast AI and the Future of Work.

Learn more about Kognitos here and search for open positions in marketing, engineering, and in large language-model disciplines. The company is looking for UX/UI and staff engineers, and more.

About Rajeev Madhavan

Rajeev has been an angel investor since 1998 and co-founded Clear in 2016. Prior to that, Rajeev founded three successful startups in the semiconductor IP and Electronic Design Automation (EDA) space. The most recent, Magma Design Automation, became the fourth-largest EDA company in the world under his leadership.

Today, Clear Ventures has $335 million of capital from a world-class investor base and is an investor currently in about 25 active companies, 90% as first investors.