DeepGMP

Deep reasoning AI for quality decisions. Investigates deviations, drafts CAPA, and produces audit-trail-ready findings. Where ChatGMP retrieves and explains, DeepGMP reasons — across multiple regulations, lab data, and prior precedent.

What DeepGMP Does

✓ Investigates a deviation: ingests the deviation form, related batch records, training history, equipment qualification, and historical similar events. Outputs a probable-root-cause analysis with confidence levels.
✓ Drafts CAPA actions with owners, deadlines, acceptance criteria, and the regulatory rationale. Reviewer just signs.
✓ Cross-references new findings against prior FDA 483 observations and warning letters in your therapeutic area.
✓ Produces inspection-ready evidence packs — every conclusion linked back to source data, every citation reproducible.
✓ Pairs with ChatGMP (for regulatory questions) and LIMSAI (for live LIMS data) to form a full AI-quality stack.

Why "Decision-Grade" Matters Here

A deviation investigation that an FDA inspector cannot reproduce is worse than no investigation. DeepGMP's outputs are decision-grade by design:

· Replayable — same inputs + same regulatory snapshot = same investigation. Frozen for the record.
· Signable — a named QA / Quality Head signs the AI's reasoning. The signature binds them to the conclusion.
· Defensible — the reasoning chain is reconstructable in plain English under inspection cross-examination.

This is the QGI framework that the FDA's emerging AI guidance is converging on. DeepGMP is built for it from day one.

Who's Reserving

· QA Heads tired of writing the same deviation investigation 50 times a year
· CAPA owners drowning in late actions across multiple sites
· Compliance VPs rolling out an "AI-augmented quality" mandate from the C-suite
· Inspectors and CRO auditors looking for AI tools they can defend in their own audits

Reserve early access

DeepGMP launches in 2 weeks. The first 25 reservations get a free 60-minute onboarding with the engineering team.

Reserve Early Access →