L7 | Enterprise Science Platform (L7|ESP®)
L7|ESP contextualizes data at the source, orchestrates workflows end-to-end, and makes AI actionable at scale.
the operational backbone of
modern life sciences
L7|ESP was built by scientists and engineers who understand that regulated life sciences have demands that generic software was never designed to meet. The platform unifies research, development, manufacturing, and quality into a single connected environment, with the data integrity, workflow orchestration, and AI-actionable foundation that GxP operations require.
purpose-built on industry 4.0 principles, designed for the agentic AI era
L7|ESP is developed on the foundational principles of Industry 4.0: connected systems, intelligent automation, real-time data, and seamless integration across scientific and manufacturing operations. These principles established the foundation. The agentic era demands something more, though: a platform where AI agents can operate reliably within regulated environments, grounded in structured, validated, contextually rich data.
L7|ESP is that platform.
Each layer of the architecture builds on the one below it: cloud infrastructure and ontology-driven data models at the base; workflow orchestration and applications in the middle; and business intelligence, AI, and agentic execution at the top.
Business value increases with every level.
L7|ESP platform components
L7|ESP is a modular platform built for how life sciences organizations actually operate: across teams, functions, systems, and partners. Each component addresses a distinct layer of the architecture, from data and process modeling to agentic AI orchestration, working together as a unified whole.
L7|MASTER®
DATA AND PROCESS MODELING
L7|MASTER is a foundational low code authoring tool used to define scientific data and process models as a single digital standard. It transforms static documents (spreadsheets, paper records, SOPs) into dynamic, executable digital models that can be governed, reused, and understood by both humans and AI systems.
L7|HUB®
CONTENT REPOSITORY
L7|HUB is a centralized repository for portable, standardized scientific content. It operationalizes FAIR data principles (Findability, Accessibility, Interoperability, and Reusability), enabling teams to share, reuse, and govern workflows, data models, and instrument connectors across the organization and across partners.
L7|INTELLIGENCE®
DATA INTELLIGENCE / EXPORT
L7|INTELLIGENCE is a strategic business intelligence framework that extracts and structures data captured during process orchestration, transforming it into query-optimized views and data products ready for operational and scientific analysis. Outputs can surface directly in external tools including Snowflake, Tableau, and Power BI, giving cross-functional teams the insights they need without leaving their existing analytics environment.
L7|SYNAPSE™
THE AGENTIC LAYER
L7|SYNAPSE is the agentic reasoning layer built on L7|ESP. It integrates foundation models into the L7|ESP environment as reasoning engines (assembling protocols, suggesting deviation responses, identifying anomalies), while the deterministic harness of L7|ESP ensures that every action that crosses a compliance threshold is validated before execution. The AI reasons. The harness enforces. Neither operates beyond its appropriate domain.
L7|SYNAPSE gives subject matter experts natural language and voice-driven access to the platform, grounded in the organization’s SOPs, governed data, and validated workflows. Responses reflect authorized access, actions are traceable, and autonomy is earned through accountability.
L7|EXCHANGE™
MULTI-PARTY ORCHESTRATION
L7|EXCHANGE enables disconnected organizations and partners to securely coordinate workflows across different legacy systems and applications. It is designed for the complex handoffs between sponsors, CROs, CDMOs, and manufacturing partners that define modern pharmaceutical operations. When the receiving organization onboards a process, it receives not just the data but the relational context that makes the data meaningful.
Estimated release date: 2027
L7 apps
L7|ESP includes a suite of best-of-breed applications designed to work together on a single unified platform. Each app is fully integrated with the platform’s workflow orchestration, data contextualization, and knowledge graph, so data captured in any app is immediately AI-actionable across the whole system. L7|ESP also connects with existing legacy systems, so organizations can adopt individual apps incrementally without replacing what already works.
L7 NOTEBOOKS
Secure, collaborative digital notebooks with reusable templates, role-based access, and seamless integration across the platform.
L7 LIMS
Sample management, experiment execution, and laboratory workflow orchestration in a single connected system.
L7 MES
Electronic batch records, Master Batch Record configuration, and GMP-compliant manufacturing execution for regulated environments.
L7 SCHEDULING
Resource scheduling and capacity planning synchronized across instruments, staff, and workflows in real time.
standard content + standard connectors
L7|ESP ships with a growing library of pre-built standard content (including workflows, data models, and analytics packages) and a wide range of instrument and software connectors covering sequencing, PCR, liquid handling, label printing, quantification, imaging, and more. Pre-built content is governed, versioned, and deployable via L7|HUB, reducing implementation time and accelerating time to value.
STANDARD CONTENT
L7|ESP is populated with a growing library of standard workflows, data models, and analytics packages.
STANDARD CONNECTORS
L7|ESP supports a wide range of instrument and software connectors across lab and manufacturing environments.
optimize the flow of molecules across your entire pipeline
a knowledge graph generated at the source
L7|ESP contextualizes data at the point of execution, capturing not just the raw values but the full set of relationships surrounding them: which instrument was used, which reagent, which personnel, under which protocol, at which site, producing which result, etc… As workflows run, these relationships are stored in a knowledge graph that models complex genealogies among entities (people, equipment, locations, processes, activities, materials, and outcomes).
The knowledge graph creates a semantic layer that allows cross-functional teams to query across departments, trace decisions back to their source, and surface insights that siloed systems cannot produce. It is also what makes data AI-actionable at the source, rather than requiring rounds of downstream cleanup, transformation, and tagging.
Life sciences organizations face a fundamental ontological challenge across the drug lifecycle. Each stage operates on different standards: GO and Cell Ontology in research, ChEBI and BAO in discovery, CDISC and MedDRA in clinical development, ISA-95 and ISA-88 in manufacturing, LOINC and AFO in quality control. L7|ESP standardizes ontological labeling at the point of data capture, using these industry-recognized standards across each relevant lifecycle stages.
resources
L7|ESP®
brochure
L7|SYNAPSE™
datasheet
L7|HUB®
datasheet
L7|INTELLIGENCE®
datasheet
L7|MASTER®
datasheet
L7 Notebooks
datasheet
L7 LIMS
datasheet
L7 MES
datasheet
L7 Scheduling
datasheet
L7 services
When you become a customer, you'll be granted full access to L7 UNIVERSITY, an incredibly rich library of proprietary content and training resources.
