The Operating System for Precision Science.
▹ Orchestrate + Automate Processes. Unify Data. ▹ Cut Lead Times. Reduce Operational Costs. ▹ Accelerate Science with AI-Actionable Data.
Frost Radar™ Identifies L7 Informatics as a Top Growth and Innovation Leader in Pharmaceutical and Biotech LIMS
Frost & Sullivan Frost Radar™ has named L7 Informatics a top innovator in Pharmaceutical and Biotech LIMS, 2025. The recognition highlights L7|ESP®’s role in creating AI-ready data through unified workflows and contextualized information, helping life sciences organizations accelerate research, manufacturing, and analytics with a digital backbone built for scalability and intelligence.
Fragmented systems are blocking your AI ambitions
Drug development is getting harder and more expensive. On paper, AI offers a genuine path forward, but most organizations are facing the same obstacle: the operational foundation needed to deploy AI at scale simply is not there yet. Disconnected systems, fragmented workflows, and data that cannot be contextualized at the source slow work down, drive up costs, and leave AI initiatives stuck in pilot mode.
10 years
That’s how long it takes, on average, to deliver new treatments, with inefficiencies dragging out every phase.
SOURCE · MCKINSEY
$2.67B
the average cost to develop a drug continues to climb, reaching $2.67 billion in 2025, and putting strain on R&D and manufacturing.
SOURCE · DELOITTE
95%
95% life sciences organizations have yet to realize AI as a competitive advantage.
SOURCE · MCKINSEY
The Platform · unify · contextualize · orchestrate
L7|ESP: the execution layer that makes AI actionable.
AI is only as powerful as the data behind it. In life sciences, fragmented systems, inconsistent ontologies, and disconnected workflows create a gap between AI ambitions and AI outcomes. L7|ESP closes that gap. The platform contextualizes data at the source, orchestrates end-to-end processes across research, development, manufacturing, and quality, and provides the unified operational foundation organizations need to run AI at scale.
L7|ESP is the execution layer and the digital backbone of regulated science. With platform components including L7|SYNAPSE, L7|MASTER, L7|HUB, L7|INTELLIGENCE, and L7|EXCHANGE, it delivers AI-actionable data, seamless orchestration, and cross-functional operational continuity at every stage of the scientific lifecycle.
L7|ESP layers over existing systems. No rip-and-replace required.
WHY L7|ESP
Why L7|ESP makes possible.
01 / Digital Unified Platform
L7|ESP connects and orchestrates lab and manufacturing workflows, contextualizing data at the source and making it AI-actionable across the scientific and operational continuum.
- Seamless integration: Works with instruments, equipment, and legacy systems.
- Data contextualization: Captures data at the point of generation, eliminating complex downstream transformations.
- Reduced IT overhead: Minimizes manual intervention and simplifies data management.
- Real-time insights: Transforms raw data into actionable intelligence without degradation over time.
- Adaptable in any IT landscape: Supports both legacy-heavy (brownfield) and newly established (greenfield) environments.
- More than a data lake: A fully digital unified platform with built-in LIMS, ELN, MES, Scheduling apps , and more.
02 / Compliance + AI-Ready
L7|ESP is built for GxP-regulated environments, including GLP, GCP, and GMP, structuring data at the point of execution to ensure integrity, traceability, and AI actionability by design.
- Complete audit trail: Captures instruments, reagents, media, and personnel for every experiment or process.
- Automatic data contextualization: Eliminates the need for complex ETL pipelines and siloed storage.
- AI-actionable foundation: Organizes data for seamless AI/ML training, including LLMs.
- Enhanced regulatory compliance: Simplifies audits, submissions, and root cause analysis.
- Single source of truth: Ensures structured, intact, and contextualized data for improved decision-making.
03 / Rapid Tech Transfers
L7|ESP streamlines internal and external tech transfers, accelerating time-to-market for drug products, biologics, and diagnostics.
- Seamless digital transfers: Eliminates process variations and the need to revert to paper.
- Unified data + processes: Ensures consistency across research, development, clinical trials, and commercialization.
- GxP-compliant: Maintains data integrity and harmonization throughout the product lifecycle.
- CRO/CDMO-ready: Enables smooth collaboration with external partners.
- Faster scale-up + commercialization: Reduces delays and inefficiencies in tech transfer.
04 / Portfolio Optimization
L7|ESP simplifies IT ecosystems, reducing costs and freeing resources for innovation.
- Eliminates redundancies: Orchestrates interactions across legacy systems, instruments, and equipment.
- Reduces IT complexity: Streamlines architecture to optimize resource allocation.
- Future-proof framework: Supports both monolithic and next-gen solutions.
- Phased system transitions: Enables seamless onboarding and retirement of technologies.
- Unlocks AI + ML potential: Frees budgets for transformative technologies like Gen AI , machine learning, and Agentic AI.
05 / Operational Excellence
L7|ESP unifies research, lab, and manufacturing operations, eliminating inefficiencies and enhancing visibility b y answering questions such as ‘What is the utilization of my lab resources? ”, “When will my test be completed? ”, or “What is delaying my batch release? ”
- End-to-end integration: Connects ELN, LIMS, MES, and Scheduling in a single platform.
- Optimized workflows: Replaces paper-based processes to improve efficiency.
- Material + capacity management: Ensures better resource utilization.
- Real-time operational insights: Provides answers to critical questions on test timelines, batch delays, and resource allocation.
- Smarter decision-making: Enhances visibility across Research, Development, and Manufacturing.
Simon Hughes
L7|ESP is an adaptable and customizable platform that streamlines process execution, provides a complete chain of study from sample to report, and enables management of complex workflows.
Mike O’Mara
The decision to deploy L7|ESP reflects our commitment to staying at the forefront of innovation in this dynamic field.
Dr. Jerome Ritz
We have many computer systems that do not talk to each other with a lot of paper in between each of these different systems. We looked for a system for two years and selected L7 for several advantages.
Ernie Bognar
L7|ESP provides a single platform to assure both control and compliance, while providing a seamless transfer of clinical operations to manufacturing operations.
Dr. Stephen Kingsmore
L7 plays a key role in our end-to-end automation of the patient journey - from order to clinical report.
Magi Richani
L7|ESP revolutionizes how we track plants, samples, and lineages, empowering our R&D endeavors with a consistent process that has already resulted in a 50% increase in efficiency.
Janet Bakeman
We chose L7|ESP as our central data platform as it allowed us to optimize internal data flow, implement FAIR data principles, integrate with the minimal set of four data applications, and accommodate our growing requirements to be more efficient and scalable.
From the blog
The Clinical Trial Paradox & The Pragmatic Middle Path: Unifying Biological Boldness with Enterprise IT Risk Management
Vasu Rangadass, President and CEO of L7 Informatics, and Ray Veeraraghavan, VP of Science and AI, examine the clinical trial paradox: pharma takes bold biological risks while IT often defaults to familiar, conventional systems. That divide stalls most life science AI initiatives. Their pragmatic middle path adds orchestration over existing systems instead of replacing them,…
Read: The Clinical Trial Paradox & The Pragmatic Middle Path: Unifying Biological Boldness with Enterprise IT Risk ManagementAI Governance Starts Before Agents Can Act
Agentic AI is entering regulated pharma workflows faster than the foundations beneath it can support. Vasu Rangadass, CEO of L7 Informatics, explores why governance depends on context, lineage, and traceability existing before agents act, and how a unified operational foundation turns governance into a natural outcome of execution.
Read: AI Governance Starts Before Agents Can ActOrchestrating the 98%: The Hidden Architecture of Trustworthy AI
A landmark analysis of a leading AI agent found that only 1.6 percent was the model. The rest was operational infrastructure. Vasu Rangadass explains why, in regulated science, that operational harness is where trust, economics, and durable advantage are built, and why the model was the least of the engineering.
Read: Orchestrating the 98%: The Hidden Architecture of Trustworthy AIMeet us in person
In the press
Lab Automation: Overcoming Operational Friction with L7 Informatics
Lab Manager examines how L7|ESP® 2026.1 helps precision science organizations reduce operational friction created by fragmented systems. The article highlights L7|SYNAPSE™ agentic AI, major computation speed improvements, advanced NOR and PAR operational modeling, and flexible deployment options. It also explores how a unified platform can connect laboratory, manufacturing, and data workflows with greater operational context…
Read: Lab Automation: Overcoming Operational Friction with L7 InformaticsL7 Informatics Unveils L7|ESP® 2026.1, Solidifying the Premier Agentic Operating System for Precision Sciences
L7 Informatics announced the general availability of L7|ESP 2026.1, solidifying the platform as the agentic operating system for precision science. The milestone release deploys the L7|SYNAPSE AI framework and its Seven chief agent, delivers major performance acceleration, and embeds NORs and PARs compliance modeling directly into manufacturing and asset management.
Read: L7 Informatics Unveils L7|ESP® 2026.1, Solidifying the Premier Agentic Operating System for Precision SciencesL7 Informatics Names Ray Veeraraghavan, Ph.D., Vice President of Science and AI
L7 Informatics has named Ray Veeraraghavan, Ph.D., Vice President of Science and AI. A former Quest Diagnostics executive who led the enterprise evaluation that selected L7|ESP, Veeraraghavan will drive L7|SYNAPSE Agentic AI adoption, lead scientific content strategy, and advise senior leadership at L7's most strategic enterprise accounts.
Read: L7 Informatics Names Ray Veeraraghavan, Ph.D., Vice President of Science and AIVasu Rangadass on Integrated Platforms for Regulated Industries
The Silicon Review features L7 Informatics and Vasu Rangadass, Ph.D., highlighting how L7|ESP helps regulated scientific organizations move beyond fragmented systems. The article explores AI-ready data, workflow orchestration, composable architecture, and the emergence of L7|SYNAPSE as an agentic AI layer for regulated scientific execution.
Read: Vasu Rangadass on Integrated Platforms for Regulated IndustriesRecent white papers
Active Knowledge Graphs: Why AI in Regulated Life Sciences Stalls Without Them
Most enterprise AI stalls in regulated life sciences because it runs on passive, retrospective knowledge graphs. This white paper introduces the active knowledge graph, generated by L7|ESP® at the point of execution, and shows how a neuro-symbolic architecture makes AI accurate, auditable, and AI-actionable across research, development, and GxP manufacturing.
Download: Active Knowledge Graphs: Why AI in Regulated Life Sciences Stalls Without ThemOrchestrating the 98%: Why the Operational Harness Will Define Pharma’s Agentic Era
Only 2 percent of a production-grade AI system is decision logic. The other 98 percent is operational infrastructure. In pharmaceutical manufacturing, that infrastructure carries the weight of GxP compliance, audit, and validation. In this white paper, Vasu Rangadass, Ph.D., President and CEO at L7 Informatics, makes the case that AI orchestration, not model sophistication, will…
Download: Orchestrating the 98%: Why the Operational Harness Will Define Pharma’s Agentic EraThe Economics of Digital Continuity: Quantifying the ROI of Unified Data Orchestration in PPM
The pharmaceutical industry faces a growing contradiction: accelerating molecular innovation constrained by legacy operational infrastructure. In this joint white paper, L7 Informatics President and CEO Vasu Rangadass and Turnberry Solutions Managing Partner Emily Anderson quantify the cost of fragmented data, the execution gap between portfolio visibility and operational reality, and the measurable ROI that unified…
Download: The Economics of Digital Continuity: Quantifying the ROI of Unified Data Orchestration in PPMThe Agentic Pivot: Strategic Reorientation for Regulated Process Industries
Point solutions digitized the work, but they didn't unify it. For pharma, biotech, and CDMO organizations, the result is systemic fragmentation that drains scientific talent, slows batch release, and blocks AI from delivering real value. In this white paper, Vasu Rangadass, Ph.D., President and CEO of L7 Informatics, makes the case and explains how regulated…
Download: The Agentic Pivot: Strategic Reorientation for Regulated Process Industries
L7 in 7 questions.
What does L7 Informatics do?
L7 Informatics builds the execution layer for regulated science. Its flagship platform, L7|ESP®, is a digital unified platform that contextualizes data at the point of generation, orchestrates workflows across research, development, manufacturing, and quality, and provides the operational foundation life sciences organizations need to make AI actionable at scale.
L7|ESP brings scientific and operational data, workflows, applications, instruments, and enterprise systems into a single digital environment. L7 serves pharmaceutical companies, biotechs, CDMOs, diagnostics organizations, cancer centers, CROs, and research institutions at every stage of growth.
What problem does L7|ESP solve for life sciences organizations?
L7|ESP solves the data fragmentation problem that blocks operational efficiency and AI expansion in life sciences. Most organizations run on disconnected systems, each with its own language, logic, and limits. The result is redundant processes, inaccessible data, and AI ambitions that outpace the infrastructure needed to support them.
Drug development slows, costs rise, and teams spend more time moving data than acting on it. L7|ESP closes that gap by unifying data and orchestrating workflows across research, development, manufacturing, and quality, giving organizations the shared operational context they need to operate as one connected enterprise.
How is L7|ESP different from traditional LIMS, ELN, MES, or point solutions?
L7|ESP is different in kind, not just in scale, from traditional LIMS, ELN, MES, and other point solutions. Point solutions are typically built to solve one problem in isolation. They may capture data, but they often leave organizations relying on custom integrations, manual handoffs, and workflow boundaries that become operational failure points.
L7|ESP contextualizes data at the source using ontology-driven knowledge graphs, orchestrates processes end-to-end, and delivers built-in LIMS, ELN, MES, and scheduling capabilities within a single unified platform. It can also layer over existing infrastructure without requiring rip-and-replace, enabling organizations to unify operations without starting over.
How does L7|ESP make AI actionable across scientific and operational workflows?
L7|ESP makes AI actionable by structuring data at the point of execution, before it becomes siloed, degraded, or disconnected. Using ontology-driven knowledge graphs, the platform captures context alongside raw data, linking instruments, reagents, personnel, process parameters, experimental conditions, and outcomes at the moment of generation.
This gives AI, machine learning, analytics, and automation workflows access to data that is structured, traceable, and grounded in scientific and operational context. Instead of depending on downstream data cleanup and transformation, L7|ESP gives organizations the execution foundation needed to scale AI across regulated life sciences operations.
What role does L7 play in agentic AI for life sciences?
L7 provides the operational foundation that makes agentic AI viable in regulated scientific environments. Agentic AI systems, including autonomous agents that plan, reason, and act across multi-step workflows, require structured, contextual, and trustworthy data to function reliably. Without an execution layer that ensures data integrity and context at the source, agents operate on incomplete or inconsistent information and are difficult to deploy safely in regulated settings.
L7|SYNAPSE™, L7|ESP’s agentic AI layer, enables context-aware AI that works directly within scientific and manufacturing workflows. It gives agents access to governed, structured data and the operational harness needed to support action with traceability, control, and compliance.
Can L7|ESP work with existing systems and legacy infrastructure?
Yes. L7|ESP is designed to layer over existing IT infrastructure rather than replace it. The platform integrates with instruments, equipment, legacy systems, and enterprise applications, allowing organizations to adopt L7|ESP incrementally and expand capability over time as their digital maturity grows.
This applies equally to brownfield environments with decades of legacy investment and greenfield organizations building from scratch. Organizations do not need to choose between modernizing and protecting prior investments. L7|ESP connects what already exists, fills the gaps between point solutions, and creates a unified operational layer across the technology landscape.
Is L7|ESP designed for regulated life sciences environments?
Yes. L7|ESP is built for GxP-regulated life sciences environments, including GLP, GCP, and GMP operations. The platform supports audit trails, electronic records and signatures, chain of custody, workflow control, and data integrity requirements across complex scientific and operational processes.
Because data is contextualized at the point of execution, traceability is structural rather than retrofitted. This enables teams to support regulatory submissions, audits, investigations, and root cause analysis with connected data and process context. L7|ESP also supports tech transfer between internal teams and external CRO and CDMO partners while maintaining the data integrity, harmonization, and operational continuity required in regulated environments.