Solution

Oncology Drug Manufacturing Excellence

For quality and manufacturing operations teams in pharma: batch genealogy, record validation, and SOP change tracking answered in plain English from the documents your plant already produces.

Batch recordSOPSpreadsheetScanned recordChange control
Thousands of batch queries previously tracked by handEvery answer traceable to its recordEvery compliance call human-approved

The problem

Why this exists

36,000

Batch queries tracked by hand

Traceability questions were logged and chased manually across systems, and answers took days — with each increase in production volume making the workflow slower, not just busier.

3 formats

The evidence lives in Excel, PDFs, and scans

Raw material and product traceability data sits scattered across spreadsheets, PDFs, and scanned records, so every genealogy question becomes hours of cross-referencing.

Every revision

SOP documentation drifts out of sync

Frequent SOP updates with no automation behind them leave batch documentation trailing the current procedure — the kind of drift an auditor finds before you do.

The product, not a promise

A batch record you can interrogate

Oncology Drug Manufacturing Excellence — workspace
Genealogy mapped raw material to finished productFlowchartcited
Plain-English batch query answered with tables and sourcesCitedcited
SOP revision tracked against affected batch recordsVersionedcited
Record value conflicts with the batch spreadsheet — flaggedverify
Compliance trend report generated for the quality reviewOn demandcited
HUMAN-APPROVED BEFORE IT POSTS

How it works

File in. Answer out.

  1. 1

    Ingest

    Batch records, SOPs, spreadsheets, PDFs, and scans flow in from across manufacturing systems.

  2. 2

    Understand

    AI agents extract and structure the data locked inside each format.

  3. 3

    Trace

    Genealogy agents map raw materials, intermediates, and finished product across datasets into flowchart views.

  4. 4

    Check

    Agents validate records, track SOP changes, and flag compliance risks as they appear.

  5. 5

    Answer

    Teams ask questions in natural language and get answers as text, tables, or visuals — with sources.

Who it's for

Built for the people who own the outcome

Quality engineer

Batch questions answered in minutes, with evidence.

  • Ask in plain English — no SQL, no cross-referencing marathon
  • Genealogy rendered as a flowchart, raw material to product
  • Every answer carries the records behind it

Site quality head

Traceability that holds as production scales.

  • Query workload absorbed by agents, not added headcount
  • SOP changes tracked against affected documentation automatically
  • Trend reports surface drift before the audit does

Compliance / regulatory affairs

Evidence-first automation, accountability with people.

  • Compliance-relevant findings route to a human for the call
  • Every agent answer traceable to the source record
  • Documentation consistency measurable, not assumed
Pharmaceutical manufacturingBiologicsAdvanced therapiesContract manufacturersMedical devicesChemicals
Thousandsof batch queries previously tracked by hand
Genealogyraw material to product, mapped
Plain Englishquestions, no SQL needed
Human-approvedevery compliance call

A US-based global pharmaceutical company — biologics, advanced therapies, and small-molecule drugs — was tracking 36,000 batch queries by hand. Raw material and product traceability suffered, answers took days, and the data needed to answer them was scattered across Excel sheets, PDFs, and scanned records. Frequent SOP updates with no automation behind them meant documentation drifted out of sync, and every increase in production volume made the manual workflow slower, not just busier.

In oncology manufacturing, traceability and documentation accuracy sit directly on the patient-safety path — the cost of drift is measured in more than hours.

What it does

Botminds deploys AI agents against the documents and data the plant already produces. The agents read spreadsheets, PDFs, and scans, extract the batch and quality data inside them, and keep it queryable. Teams ask questions in natural language — no SQL — and get answers back as text, tables, or visuals, generated through AI-driven query automation.

For genealogy, agents map raw materials, intermediates, and finished product across datasets and render the lineage as flowchart insights, replacing hours of manual cross-referencing per query. For change control, agents validate records, track SOP updates, flag compliance risks, and generate trend reports so quality teams see drift before an auditor does.

Why governed matters

Pharma quality systems run on evidence. Every answer the agents produce is traceable to the record it came from, and compliance-relevant findings route to a human for the call — the agents surface, people decide. Automation does the reading and cross-referencing at scale while accountability stays with the quality organization. The outcome is faster batch queries, consistent SOP documentation, and traceability that holds up as production scales.

Objections, answered

What teams ask us first

How do I trust an agent's answer on a compliance question?

Every answer is traceable to the record it came from — the batch sheet, the SOP version, the scanned page. Compliance-relevant findings route to a human for the call: agents surface, the quality organization decides.

Our records are a mix of Excel, PDFs, and old scans — will it read them?

That mix is the design case. Agents extract and structure data from spreadsheets, PDFs, and scanned records into one queryable layer, so a genealogy question spans all three formats in a single answer.

Does this fit a validated pharma quality environment?

The platform assists the quality system rather than replacing it. Answers carry their evidence, findings route to named humans, and the full trail — question, sources, decision — is preserved for inspection.

How long before our team can ask real questions?

Point the platform at a set of batch records and SOPs; the first genealogy and validation answers are a review exercise against known cases. Most quality teams are checking agent answers against their own within days and using them in live queries within weeks.

Bring one batch genealogy question.

Watch agents trace it from raw material to finished product, with sources, live in the demo.

Request a demo