Deviation & CAPA management that keeps up with the plant.
Reduce deviation investigation time without cutting corners: AI drafts the structured investigation, your QA team challenges and decides, and the closure file is defensible by design.
Every open deviation is a question
an auditor hasn’t asked yet.
The backlog isn’t laziness — it’s arithmetic. Each investigation costs days of drafting, review, and rework, and the plant keeps producing events while your team writes about the last ones.
Where investigation time actually goes
Blank-page drafting
Every investigator starts from scratch — assembling the narrative, impact assessment, and root-cause argument by hand, event after event.
Inconsistent files
Ten investigators, ten writing styles. QA burns cycles reworking reports into something consistent and review-ready.
Closure-date pressure
Backlogs push closure dates, rushed closes produce weak root causes — and weak root causes produce repeat deviations.
AI does the heavy lifting. Your experts make every call.
- A structured first draft in a fraction of the time. The AI drafts the investigation — event description, impact, root-cause reasoning, CAPA logic — from your evidence.
- The right questions, before writing starts. Structured questions surface missing evidence on day one, not in QA review.
- Your experts stay in charge. Root cause, CAPA, and closure are human decisions. The reviewer edits, challenges, and signs.
- Defensible, consistent closure files. Every claim traceable to its source; every file reads the same way, whoever ran the investigation.
What auditors look for in a deviation investigation
Speed only matters if the file holds up. These are the marks of an investigation that survives scrutiny.
- A clear problem statement. What happened, where, when, and to what — specific enough that a stranger could understand the event.
- An impact assessment with honest scope. Product, lot, adjacent systems, and prior lots considered — not just the batch in front of you.
- A root cause the evidence actually supports. Not a restated symptom, not "human error" as a reflex — a cause that explains the event.
- CAPA tied to that root cause. Actions that address the cause, with an effectiveness check that would notice if they didn’t.
- Consistency and traceability. The file reads like your other files, and every statement can be traced to its source.
Deviation & CAPA questions we hear most
How do we reduce deviation investigation time without cutting corners?
Separate the drafting from the judgment. Most investigation time goes into assembling and writing — work AI can accelerate dramatically. The judgment — root cause, CAPA, closure — stays with your qualified people. That split is how teams see 60–70% time savings on targeted workflows (depending on adoption and process fit, validated in proof-of-concept) without weakening the file.
Can AI write a deviation investigation report?
AI can draft one — and constrain itself to your evidence while doing it. What it can’t do is own the conclusion: root cause and CAPA are determinations your reviewer makes and signs. That’s exactly how the Investigations module is built.
What about the CAPA backlog?
Same workflow: the AI drafts the CAPA rationale and links it to the root cause; owners review, adjust, and commit. Consistent CAPA logic also makes effectiveness checks easier to define and defend.
Bring your last five deviations
A pilot on your own recent deviations is the fastest honest answer — measure drafting time, consistency, and review effort on your own data.