AI for Regulated Life Sciences · ISO/IEC 42001 Certified

Your regulators won’t accept
“the AI said so.” We built AI that can prove it.

CLAiRE, iQuality, and MAiGRATE are purpose-built for the one constraint generic AI ignores: every claim has to trace back to your organizational truth — not a model’s training data.

Audit Trail Review

Days of senior time per cycle

~2 min

Full 21 CFR Part 11 review, per click

Regulated Migration

12–18 months, $1–3M

5–6 wks

~Half the cost, per-record evidence

Annual Product Quality Review

~1 month per product

1–2 days

18 months of FTE freed per year (20-product pharma)

Audit Event Coverage

5–10% sampled quarterly

100%

Nightly review across every connected audit source

The Problem

AI is everywhere. Defensible AI is rare.

Most life sciences teams have already run the generic AI pilots. They know the tools can summarize a document. What they’ve learned — the hard way — is that the hard part isn’t capability. It’s defensibility.

  • Audit trail reviews still take days because someone has to connect the finding to the regulation, manually
  • Annual product quality reviews still run a month per product, even with good data
  • Regulated migrations take 12–18 months and $1–3M because the evidence work is bespoke every time
  • A regulator asks “how do you know?” — and the answer requires an interview, not a file
  • Generic LLMs answer from training data. Regulators require answers from your organizational truth

The constraint that changes everything

In pharma, biotech, and medical device, every AI decision has to be defensible to a regulator. Every deployment has to fit inside your governance. Every piece of evidence has to trace back to your records — not to a model’s training data.

Generic AI hallucinates users that don’t exist, SOPs that were never approved, certifications that weren’t in scope. In a regulated environment, that’s not an inconvenience. It’s an audit finding.


This is why every regulated AI decision must be grounded against your knowledge graph before the model reasons — and why every claim traces back to a specific node with timestamps and version fingerprints.

  • “The hard part of regulated AI is not finding a capable model. It is making the model’s answers defensible. That requires grounding against your organizational truth — not training data. Generic AI cannot do that.”
    – The design principle behind CLAiRE, iQuality, and MAiGRATE

Three Products. One Foundation.

360° AI compliance on one certified platform.

Each product runs on your identity, your AI, with your evidence in your custody. Governed under ISO/IEC 42001 — the only certified AI Management System in life sciences compliance.

QMS · DMS · TMS

iQuality

The platform your quality team actually runs on.

Next-generation Quality, Document, and Training Management — purpose-built for regulated life sciences. Three integrated modules built on 21 CFR Part 11, with CLAiRE AI baked in across every workflow. Deploys in weeks, not 18 months.

Migration Platform

MAiGRATE

Regulated migration in weeks. Not quarters.

Productized migration for regulated data — from TrackWise, MasterControl, and SAP into Veeva Vault QMS, Veeva QualityDocs, or ServiceNow GRC. Ships with per-record audit-grade evidence. Fixed price. Not a consulting engagement.

Agentic AI Platform

CLAiRE

The harness around the model.

A no-code platform to design, orchestrate, and deploy autonomous AI agents — purpose-built for regulated industries. Nine agents, each solving a specific problem. Every output ships with a cryptographic evidence chain and a complete audit log.

CLAiRE Agent Catalog

Eight agents. Each solving a specific problem.

Customers buy the agent for the pain it addresses. Each is a standalone product — not a path to anything else. Each runs on your own AI, reads only what you authorize, and produces an audit-grade evidence pack on every run.

ATR

Continuous GxP compliance monitoring across Veeva Vault, Jira, Polarion, ServiceNow, TrackWise. Nine standard checks per event — each tagged Critical, Major, or Minor with 21 CFR Part 11 and EU Annex 11 citations.

Read-only by design

APQR

Six specialized agents compile your APQR across TrackWise, JMP, ERP, and SharePoint. Every claim cited back to a source record. Cuts a month-per-product process to one or two days.

Every claim cited to source

DRIFT

Detects drift between your source-of-truth (Workday, master CSV) and downstream regulated systems. Per-record diff with severity, reason, and source evidence. Writes require explicit operator sign-off.

Detect-only by default

QDR

Continuous monitoring of live quality data — deviations, CAPAs, OOS, complaints, change controls. Surfaces trends and anomalies between event-by-event QMS review and the year-end APQR cycle.

Catches issues between cycles

VERA

Continuously ingests FDA enforcement actions — Warning Letters, 483 observations, Untitled Letters. Finds comparable past cases for any new observation and drafts response material grounded in actual precedent.

Find precedent before they do

TOAST

Imports engineering and regulatory standards (IEEE, ISO, IEC, ASME, USP), decomposes them into atomic requirements, and assembles a typed knowledge graph. Optionally pushes work items into Polarion ALM.

New standard to requirements in hours

GRC

Tracks controls across GxP, 21 CFR Part 11, SOX, Cybersecurity (NIST CSF, CIS, MITRE ATT&CK), NIST 800-53, ISO 27001, and SOC 2. Continuous evidence collection from Splunk, Sentinel, Okta, AWS Config.

Audit prep as a continuous process

Nova

Embedded AI copilot inside Polarion ALM — installed as a native plugin, no extra infrastructure. AI chat, compliance dashboard, Smart Trace gap detection, AI quality check. All data stays on your Polarion server.

Data never leaves your server

How It Works

Your installation. Your network. Your data. Your evidence to keep.

Every AI call grounds against your knowledge graph before it reasons. Every claim the model produces traces back to a specific node with timestamps and version fingerprints. When a regulator asks “how do you know?” — the answer is a path through the graph. Not an interview.

The CLAiRE ontology encodes your compliance structure as a typed graph: users, roles, training records, SOPs, batch records, deviations, CAPAs, change controls, and the cross-references among them. Models cannot invent users, certifications, or approvals that do not exist in your source systems.

Your Environment

Your Identity · Your AI · Your Evidence

SAML/IdP · Azure OpenAI or self-hosted · Splunk / Sentinel

Product Layer

iQuality — QMS · DMS · TMS

Quality, Document, and Training Management

The Harness

CLAiRE Agentic AI Platform

ATR APQR DRIFT QDR VERA PRECEDENT TOAST GRC Nova

Security & Compliance

One security posture. Two deployment modes.

Either mode: your identity provider runs access, your AI tenant does the inference, your audit log stays in your custody. Data never goes to public models.

SOC 2 Type II ISO 27001 ISO 42001 AI Mgmt 21 CFR Part 11 AES-256 at rest TLS 1.2+ in transit Hash-chained audit logs Certificate of Deletion

Option 1 — Compliance Group SaaS: Single-Tenant Dedicated Realm

Your realm is a hard tenancy boundary — separate schema, separate secrets vault, separate knowledge graph, separate audit log. No shared caches. No cross-realm read paths. Customer SAML SSO, Compliance Group zero standing privilege, per-realm encryption keys.

Option 2 — On-Premise: Inside Your Data Center

Installed as a Docker stack on your infrastructure. Your Azure OpenAI, AWS Bedrock, or self-hosted model. Your evidence store and audit retention. Air-gapped deployment supported for the strictest environments.

Ready to Start

30 minutes. A concrete plan for where to start.

  • 45 minutes
  • Practitioner-led
  • Written brief included
  • Zero obligation