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PharmFindr Scribe

:::info Coming soon Scribe is in development for enterprise QA teams. Join the waitlist to get early access. :::

Scribe is a pair of AI agents that automate document-heavy QA workflows — CoA reconciliation, batch record pre-screening, and PQR compilation — turning multi-hour or multi-day manual reviews into a targeted check. Every output is a tracked Word suggestion with an exact citation back to the source document.

Screenshot: Scribe landing page hero

How it works​

  1. Drop in your source document — a CDMO-supplied CoA, an executed batch record, a PQR data package, or any structured pharma document.
  2. Scribe agent drafts the summary — Scribe reads the source and fills out the summary template as Word tracked changes, with a comment on each entry citing the exact source location.
  3. Reviewer agent double-checks every entry — a separate reviewer agent checks the scribe's work against the source and flags errors privately. The scribe corrects and the loop runs until convergence, up to three rounds.
  4. One clean layer of suggestions reaches you — you receive a single Word document with tracked changes and citation comments. Accept, reject, or modify — every decision stays yours.

Screenshot: Word document with Scribe's tracked-change suggestions and citation comments Diagram: scribe agent and reviewer agent verification loop

What you get​

  • CoA reconciliation — a line-by-line check of assay, dissolution, impurities, and microbial results against Quality Agreement release specs, with every out-of-spec result flagged and both numbers cited.
  • Batch record pre-screening — flags deviations, missing signatures, and OOS results in executed batch records before QA disposition.
  • PQR compilation — aggregates a full year of batch data, deviations, complaints, and stability results into the Annual Product Review template.
  • Citation-backed suggestions — every entry includes a comment citing the page, section, or table it came from in the source document.
  • Scribe + Reviewer verification loop — an internal back-and-forth between agents converges on accuracy before anything reaches you, with a hard iteration cap and escalation if unresolved.
  • Audit trail on demand — the full scribe–reviewer iteration history is persisted and available on request, even though it stays hidden from the default view.

Who it's for​

  • QA directors looking to eliminate the manual document review bottleneck without adding headcount or sacrificing traceability.
  • Quality managers running CoA reconciliation, batch record pre-screening, or PQR compilation.
  • Regulatory affairs teams who need every output to be a tracked, citation-backed suggestion that's audit-ready from the moment it leaves the agent.