AI MES software that drafts the paperwork and never signs it.
V5 Ultimate runs execution on the floor and puts AI alongside it — reading the batch as it runs, drafting the deviation the moment a step breaks, ranking exceptions at batch close, and explaining yield drift with the evidence attached. Every output is a suggestion an authorised human accepts, edits or rejects, and the audit trail records which.
You're looking at AI in your MES because the execution data is already there — and nobody is using it.
Deviation write-ups take 30–60 minutes of an experienced person's day, from a blank box
Batch review means scrolling 200 clean steps to find the two that aren't
Yield drifts for a month before anyone correlates it to a shift, a scale or a raw-material lot
Building a new recipe from an existing Word SOP takes engineering days
Every AI vendor you've seen wants your batch data in their cloud, which validation will not accept
Nobody can tell you what the AI would be permitted to decide on its own — which is the only question QA asks
What AI actually does inside execution — and what it is blocked from doing.
Deviation drafted at the failing step
When a reading falls out of band, AI writes the narrative from the real step data — equipment, lot, operator, timestamps, prior occurrences on the same line. QA edits a draft instead of starting from nothing.
Review-by-exception triage
At batch close AI ranks every exception by regulatory weight and product impact, groups repeats, and puts the two that matter at the top of the reviewer's queue.
Yield-variance root-cause hints
Where yield drifts, AI correlates the batch against operator, shift, scale, ambient conditions and raw-material lot, and proposes the two or three most likely contributors with the evidence behind each.
Paper SOP to executable steps
Drop in a Word or PDF procedure and AI proposes the step sequence, tolerance bands, signature points and witness rules. Engineering adjusts and approves through normal change control.
Ask V5 on the kiosk
Operators ask what a step means in plain language and get an answer sourced from the effective SOP revision — not a guess, and not the version that expired last quarter.
Hard guardrails, written down
AI never signs, never releases a batch and never overrides a tolerance gate. It drafts, ranks and explains; a trained human with the right authority makes every regulated decision.
What AI in the MES is actually worth.
- Deviation write-up drops from around 40 minutes to a few minutes of review
- Reviewers stop reading clean steps — exceptions surface ranked, with repeats grouped
- First recipe build from an existing SOP goes from days to an afternoon
- Every AI suggestion is stored with its evidence and the human decision that followed it
- Model access runs inside your tenant boundary — training on your batch data is not part of the deal
How AI in execution stays defensible.
21 CFR Part 11
AI produces drafts, never records. The signature, its meaning and its binding belong to the human who applied it, and the audit trail shows whether a suggestion was accepted, edited or rejected.
EU GMP Annex 11
Computerised-system controls apply to the AI layer as they do to every other function: defined intended use, risk assessment, verified outputs and documented human review.
GAMP 5 Second Edition
AI assistance is treated as a supporting, non-decision-making function with critical thinking applied to its intended use — not as an unvalidated black box inserted into a GxP decision.
EU AI Act
Assistive, human-in-the-loop use in manufacturing quality, with documented purpose, human oversight and traceable outputs — the posture regulated manufacturers need on file before 2027 enforcement bites.
PIC/S PI 041 data integrity
AI reads the same attributable, contemporaneous record everyone else does. It cannot write a result, backdate an entry or alter an audit trail.
AI in MES, answered honestly.
What is an AI MES?
A manufacturing execution system with a model layer reading live execution data and producing drafts, rankings and explanations for humans — deviation narratives, exception triage, root-cause hypotheses, recipe proposals. It is not an MES that decides. In a regulated plant the decision, the signature and the accountability stay with a qualified person; the AI removes the typing and the searching.
Will QA accept AI in a GMP system?
They accept it when the intended use is narrow, the outputs are suggestions, the human decision is recorded, and nothing the AI produces becomes a record without a signature. That is exactly how V5 is built — and the guardrail list above is the one we hand to your validation team.
Does our batch data train someone's model?
No. Inference runs against your tenant's data for your tenant's users. Your batch records, recipes and deviations are not used as training data.
Can AI release a batch or close a deviation?
No. Release, disposition, signature and tolerance overrides are blocked to the model by design. It can rank what needs attention and draft what needs writing.
How is this different from an analytics dashboard bolted onto an MES?
A dashboard describes yesterday. This sits in the workflow: the deviation appears pre-written at the step that failed, the exception queue arrives ranked, the recipe proposal lands in change control. No export, no separate tool, no second data model.
What does it take to turn on?
Nothing extra to install. AI assistance is part of the platform; your team chooses which assists are enabled per site and per role, and the configuration itself is under change control.
See AI draft a deviation on a live batch — then watch a human sign it.
Free trial. No sales gate. First signed batch in 30 days.