Batch Records · review by exception

Review the exceptions. Not every page.

Batch review is where releases stall. Batch Records reads the full record and surfaces only what needs a human decision — so your reviewers spend their time on judgment, not on turning pages.

Built for

Manufacturing / Ops Quality / QA Batch release Site leadership

Somewhere in those pages are the
six entries that matter.

Right-first-time dies in review queues: reviewers turn every page to find a handful of exceptions, releases wait — and page-fatigue is exactly where misses come from.

What Batch Records does

Every page read. Only the exceptions escalated.

The record gets a complete read; your reviewers get a short list of decisions. That’s the whole idea.

Reads the full record

Every page ingested and read — nothing sampled, nothing skimmed.

Exceptions & anomalies flagged

Inconsistencies, gaps, and anomalies surfaced across the record for human judgment.

Review by exception

Reviewers see what needs a decision — not a stack of pages that don’t.

Human disposition, always

Release decisions belong to your qualified people. The AI prepares the review; it never disposes a batch.

Decisions captured

Every reviewer decision logged, attributable, and reviewable — a clean story for any inspection.

Works with your records

No rip-and-replace: it works alongside how the plant runs today, with integration scoped per deployment.

The workflow

Four steps from completed record to disposition

1

Ingest

The completed batch record comes in — every page.

2

AI reads & flags

The full record is read; exceptions and anomalies are surfaced with their context.

3

Reviewer decides

Your reviewer works the exception list — judging, annotating, deciding. Every decision is captured.

4

Cleaner disposition

A faster, better-documented path to release, with the full review defensible after the fact.

What changes

Faster release. Fresher reviewers. Cleaner story.

60–70%
Time saved on record review*
100%
Of pages read — nothing skimmed
1 list
Reviewers work exceptions, not page stacks
0 AI dispositions
Release is always a human decision

*Time savings of 60–70% observed on targeted workflows, depending on adoption and process fit, validated in proof-of-concept.

Asked in every serious conversation

Straight answers on Batch Records

Does the AI release the batch?

Never. Disposition is always your qualified reviewer’s decision. Batch Records prepares the review — reading everything and surfacing what matters — and captures the decisions your people make.

What if the AI misses something?

The review is designed as assistance, not replacement: the record remains fully available to the reviewer, every flag is traceable to its location in the record, and your procedures define what human review covers. In a pilot you compare its flags against your own review of the same records — on your data, before you rely on it.

Does it work with our batch records and QMS?

It’s built to work alongside your existing records and systems — no rip-and-replace. Formats and integration scope are agreed per deployment.

How do we start?

The cleanest pilot in the platform: take recently completed batch records your team already reviewed, run them through, and compare. Talk to us to set it up.

Your data is never used to train shared models Designed for CSV/CSA & Part 11 expectations Full audit trail on every draft and decision
Batch Records · pilot on your own data

Bring one completed batch record

We’ll show you the exception list on a record your team already knows — the fastest honest answer to “would this have caught it?”