Source gets fuzzy
Reviewers cannot see what evidence shaped the output.
For QA and Quality Systems leaders
AI in GMPwithout losingcontrol.
Agents prepare the packet. Humans keep the decision.
SOLVE designs controlled agent workflows around source, boundary, evidence, human review, and receipts so regulated teams can move faster without hiding responsibility.
Allowed source
Blocked action
Required evidence
Human approval
Receipt
Why AI pilots stall
Regulated teams do not need louder AI. They need visible control.
AI pilots in GMP work usually fail for ordinary reasons: unclear source, unclear authority, weak evidence, hidden system access, and no clean reviewer responsibility.
Authority drifts
The agent starts looking like the decision-maker instead of the preparation layer.
Evidence breaks
Teams cannot see what changed, what is missing, or what still needs human review.
Trust never lands
The pilot sounds advanced but does not give QA a defensible operating model.
The GMP AI offer
Controlled AI/cGMP Diagnostic
One workflow mapped end to end: task boundary, human review, evidence model, receipt model, risks, and implementation recommendation.
Discovery
Pick the workflow and pressure-test whether a diagnostic is worth doing.
$500+Controlled AI/cGMP Diagnostic
Map risks, sources, blocked actions, reviewer responsibility, evidence requirements, and next build path.
$1,500-$2,500Implementation Sprint
Build the controlled workflow with project-specific QA, validation, change-control, and support boundaries visible from day one.
$5,000-$15,000Best first workflows
Start where the evidence keeps slipping.
QMS meeting follow-up
Turn discussion into owners, blockers, missing evidence, and draft action packets.
Deviation weak signals
Surface repeated small signals before the pattern becomes painful.
Review packet preparation
Organize source material, gaps, assumptions, and reviewer questions.
Action tracker synthesis
Make open items, aging, dependencies, and accountable next steps visible.
Claims boundary
What SOLVE will not overclaim.
No autonomous GMP decisions
Agents prepare and organize. Humans own regulated decisions and final records.
No unsupported validation promise
Validation and change-control claims require scoped, project-specific evidence.
No hidden production access
Systems, data, and access boundaries must be named before use.
No replacement of QA responsibility
The workflow is designed to make ownership clearer, not to remove accountable review.
Bring one workflow
Request the AI in GMP diagnostic.
Bring one review workflow where AI could organize evidence or draft the packet while a human keeps the decision.