AI-Assisted Batch Record Review
Less manual checking, more time for QA judgement.
Extract handwritten entries, check calculations against approved rules, and flag potential documentation exceptions for QA review.
- Less Manual QA Review Time
- Shorter Batch-Release Timelines
- Faster Batch Release
From Manual Review Effort To Faster QA Decisions.
MANUAL REVIEW
- Page-by-page checking
- Repetitive verification
- QA time consumed
AI-ASSISTED REVIEW
- Automated routine checks
- Exceptions surfaced first
- Faster, focused QA review
Too Much QA Time Goes Into Routine Verification
Every batch record deserves a thorough review. But checking calculations, signatures, timestamps, quantities, and documentation page by page consumes the capacity QA needs for the cases that actually require judgment.
More batches means more manual review, by the same team.
What QA spends its time checking
- Calculations
- Quantities
- Signatures
- Dates & timestamps
- Material entries
- Process compliance
- Missing information
From Batch Record To Review-Ready Exceptions
One pass through the record, five checks, a short list at the end for QA to assess.
Ingest
Upload scanned paper records, PDFs, or documents pulled from approved
repositories.
Extract
Identify process entries, tables, quantities, signatures, timestamps, and
calculations.
Validate
Apply configurable rules built from your approved batch record
requirements.
Detect
Flag missing information, incorrect calculations, and documentation inconsistencies.
Review
Present every exception with supporting evidence for QA assessment and
disposition.
01
Ingest
Upload scanned paper records, PDFs, or documents pulled from approved
repositories.
02
Extract
Identify process entries, tables, quantities, signatures, timestamps, and
calculations.
03
Validate
Apply configurable rules built from your approved batch record
requirements.
04
Detect
Flag missing information, incorrect calculations, and documentation inconsistencies.
05
Review
Present every exception with supporting evidence for QA assessment and
disposition.
What QA Actually Receives
Only the findings that need attention, with the context to act on them.
- Review-ready exception summary
- Evidence linked to source pages
- Rules, findings, and reviewer actions stay traceable
What Changes For QA Teams
Less routine checking. More review capacity.
More Capacity
Review more batches without a matching increase in manual effort.
Faster Reviews
Consistent Checks
Focused Expertise
QA
Control
Clearer Review Evidence
Less routine checking. More review capacity.
Built For Controlled Pharmaceutical Workflows
Designed for control, accountability, and complete review traceability.
01 · OVERSIGHT
Human-in-the-loop
QA reviewers stay responsible for exceptional cases and every final decision.
02 · RULES
Configurable rules
Validation logic can be aligned to your approved procedures and record types.
03 · FINDINGS
Explainable findings
Every exception carries the rule that triggered it, the evidence, and the document reference.
04 · RECORD
Traceable activity
Findings, reviewer actions, and decisions are documented and stay trackable.
01 · OVERSIGHT
Human-in-the-loop
QA reviewers stay responsible for exceptional cases and every final decision.
02 · RULES
Configurable rules
Validation logic can be aligned to your approved procedures and record types.
03 · FINDINGS
Explainable findings
Every exception carries the rule that triggered it, the evidence, and the document reference.
04 · RECORD
Traceable activity
Findings, reviewer actions, and decisions are documented and stay trackable.
FITS INTO YOUR EXISTING ENVIRONMENT
Designed To Work With Your Existing Quality Environment
Connect to the systems and document repositories your QA teams already use — without replacing established workflows.
Frequently Asked Questions
BMR in the pharmaceutical industry stands for Batch Manufacturing Record. It is the complete documented history of a specific drug batch that tracks its manufacturing lifecycle. Every BMR contains details such as product information, bill of materials, equipment records, process parameters, in-process checks, sign-offs, etc.
It is a critical document in drug manufacturing as it provides evidence that the batch was manufactured according to GMP requirements, supports quality review and audits, and ensures traceability throughout the manufacturing process.
AI automates routine documentation checks such as calculations, signatures, timestamps, material quantities, and process sequence. Instead of manually reviewing every page, quality teams can focus on the exceptions that require expert judgment.
OCR extracts text from batch manufacturing records. AI-powered batch manufacturing record review goes beyond extraction by validating information against configurable business rules, identifying inconsistencies, and generating explainable findings for quality reviewers.
Yes. The solution can process scanned paper records, PDFs, and electronic batch manufacturing records (eBMR), depending on your document sources and existing quality systems.
Less Manual Checking. Faster BMR Review.
See how Saxon’s AI-assisted agent checks calculations and flags potential exceptions, while QA stays in control.