We built the world's first agentic AI platform designed from the ground up for FDA and EMA regulated environments. Not AI adapted for compliance — AI architected within it. Multi-agent systems that reason, plan, and execute across your entire CQV and GxP operation without ever leaving your compliance boundary.
Traditional AI tools respond to prompts. Agentic AI plans, reasons over multiple steps, calls tools, evaluates outputs, and executes complex workflows autonomously. In a GxP context, that means an agent can receive a deviation notification, trace the root cause through process historian data, draft a full investigation report aligned with ICH Q10, assign CAPA owners, and schedule follow-up — in seconds, not weeks.
Agents don't just retrieve — they think. Multi-step reasoning chains evaluate evidence, apply regulatory context, and reach defensible conclusions.
Agents execute: they draft documents, update systems, trigger workflows, query databases, and generate GxP-compliant outputs — without waiting for a human to press send.
Every agent action is bounded by validated rules, logged with immutable audit trails, and designed to satisfy FDA, EMA, and ICH expectations before the inspector arrives.
From signal to signed document — our orchestration layer coordinates specialized agents that hand off seamlessly, maintain audit trails at every node, and escalate to human review at the right moments.
Our agents are not autonomous for autonomy's sake. We've defined 14 categories of GxP decisions where human review gates are mandatory and immovable — regardless of agent confidence scores. This isn't a limitation; it's what makes our platform the only agentic AI system you can actually deploy in a regulated environment without creating a 483 on day one.
Six specialized agents. One orchestration layer. Each agent is independently validated, has documented intended use, and is tested against your site's specific GxP context before deployment.
Receives deviation notifications, traces causal chains through process historian data, applies Ishikawa and fault-tree logic within ICH Q10 governance framework, and produces ranked CAPA pathways.
Ingests URS, equipment specs, and process parameters to generate complete IQ/OQ/PQ protocols aligned with ASTM E-2500, ISPE GAMP 5, and site-specific templates — ready for review in hours, not weeks.
Continuously monitors multivariate process data streams, detects statistical anomalies before they become deviations, and generates ICH Q8/Q9/Q10 aligned annual product reviews automatically.
Monitors FDA, EMA, ICH, PIC/S, and MHRA feeds in real time, interprets guidance changes in the context of your site's programs, and surfaces actionable compliance gaps before your next inspection.
Continuously audits GxP data streams against ALCOA+ principles — attributability, legibility, contemporaneous, original, accuracy — and flags violations before they compound into inspection findings.
Manages the full lifecycle of GxP software validation — from intended use documentation and risk assessment through IQ/OQ/PQ execution to periodic review — aligned with FDA's 2022 CSA guidance.
Not benchmarks. Not synthetic demos. Outcomes from the types of regulated environments our practitioners have worked in for over 30 years.
A temperature excursion in an aseptic fill zone triggered ARCA. Within 8 seconds, the agent traced the root cause to a damper actuator failure, cross-referenced 14 similar FDA precedents, drafted a full deviation report with 3 ranked CAPA pathways, and flagged product disposition risk — complete with ICH Q10 formatted output ready for QA review.
VERITAS detected a 3-sigma multivariate drift in pH and dissolved oxygen correlation 72 hours before the batch would have been impacted. The agent generated an alert, initiated a deviation pre-assessment, and surfaced the root cause to process engineering — catching what periodic statistical review would have missed entirely until post-batch analysis.
PRAXIS ingested equipment URS documents, process flow diagrams, and site SOPs to generate a complete IQ/OQ/PQ protocol package for a new isolator installation in 3.5 hours. The package passed internal QA review with only 4 minor comments — versus a typical 3-week document cycle with a traditional protocol author.
Following an FDA Warning Letter citing data integrity deficiencies, LEXIS and ALCOA worked in concert to map every cited observation to specific SOPs, identify ALCOA+ gaps across 6 manufacturing systems, and generate a structured corrective action plan with owners and timelines — in under 4 hours vs. a typical 6-week remediation planning engagement.
Every agentic deployment comes with a complete governance package — built by the same practitioners who have defended AI implementations in front of FDA and EMA inspectors.
Every agent has a formal intended use statement, scope boundaries, and exclusions — the first thing an inspector will ask for and the last thing most AI vendors have prepared.
Formal risk assessments for each agent aligned to FMEA methodology, with identified failure modes, severity rankings, detection controls, and risk-based validation strategies.
Full lineage documentation for training datasets — source, curation method, bias assessment, and ongoing drift monitoring — because data integrity applies to AI training data too.
Model updates, retraining events, and prompt version changes are managed through a formal change control process with impact assessment, validation, and release authorization.
Ongoing performance metrics — accuracy, precision, recall, and domain-specific KPIs — reviewed periodically against pre-defined acceptance criteria with documented review outcomes.
Documented decommissioning procedures ensuring data preservation, decision history archiving, and successor agent validation before any transition — no orphaned AI in your GMP environment.
Start with a structured discovery conversation. We'll identify your highest-value agent use case, design the governance framework, and show you exactly what compliant deployment looks like — before a single model is trained.