Read -> Compare -> Flag -> Rank -> Notify

Batch Record Right-First-Time Checker

The agent sweeps a completed batch manufacturing record before it reaches QA and compares every field against the recipe limits. It returns a severity-ranked list of blanks, unsigned steps, math errors, and out-of-range parameters, each tied to the exact field or step. The operator fixes the record before submission, so it lands right the first time.

The Problem

The batch record came back from QA. Three blanks, one unsigned step, a yield that did not add up.

A batch record moves to QA at the end of a run. Two days later it comes back: a blank in-process weight on step 14, an unsigned dispensing step, and a reconciled yield reading 3 kilograms over theoretical. The operator who ran the batch is on a different shift now, so the fix means tracking down who did what and re-checking the paper. The batch sits on hold while QA and production trade emails.

What Changes

Every blank, signature, and number checked before the record leaves the floor.

The agent reads the completed record the moment it is submitted, pulls the matching recipe limits, and checks each field for blanks, missing signatures, arithmetic, and values outside spec. It hands the operator a ranked exception list with the exact step and a plain note on each item. The record gets fixed on the same shift it was run.

Humans stay in control: the agent flags and ranks exceptions, and the operator decides each fix while QA signs the final disposition.

HOW THE AGENT WORKS

TRIGGERLLMAPIDECISIONACTIONWAIT

TRIGGERCompleted record submittedFires when an operator submits a completed batch record or an eBR export lands.

APIFetch recipe limits tableLoads the approved limits and spec table for the batch product code.

LLMScan for blanks and signaturesReads every field and step, marking blanks and missing signatures.

LLMRecompute math and rangesRecomputes totals and yield and checks each parameter against its limit.

DECISIONExceptions found?

LLMRank exceptions by severityOrders the flagged items high to low with a plain note on each.

ACTIONSend exception list to operatorDelivers the ranked exception list so the operator fixes the record before QA.

The agent does not approve or reject the batch record. Your QA reviewer does. The agent removes the back-and-forth of finding blanks and math errors after submission.

HOW TO BUILD IT

Three levels of depth. Pick the one that matches where you are.

For the ops person who needs to understand what's involved and brief their team.

Batch RecordCompleted record plus recipe limits

The AgentWorkflow engine + LLM

OperatorReviews the ranked exceptions and fixes

WHAT YOUR TEAM PROVIDES ONCE

Batch record intake - reads PDF, CSV, or an electronic batch record export
Recipe limits check - compares each parameter to the approved spec table
Completeness scan - finds blanks and unsigned or unwitnessed steps
Math recheck - recomputes weights, totals, and yield reconciliation
Exception list - severity-ranked flags with the exact field and a plain note

What happens day-to-day: an operator finishes a batch and submits the record. Within a minute the agent returns a ranked list of what is missing or off. The operator fixes the blanks and math on the same shift, then sends a clean record to QA.

For the IT person or technical lead who needs to scope the integration.

INQUIRY SOURCES

Completed batch record (PDF, CSV, or eBR export)

Recipe and limits/spec table

Master batch record template for expected fields and signatures

WORKFLOW ENGINE (N8N)

Record submission received

Load recipe limits and template

Extract fields and signatures

Recompute math and ranges

Any exceptions?

Rank by severity

Deliver exception list

CONNECTS TO

MES / eBR (Werum PAS-X / Emerson Syncade / Körber)Read: completed record, step data. Write: none

ERP (SAP / Oracle / Tally)Read: recipe limits, spec table. Write: none

Document store (SharePoint / Veeva / OpenText)Read: master batch record template. Write: exception log

Notification (Email / Slack / Teams)Read: none. Write: exception list to operator

WITHOUT PMS API

Without API access, the operator exports the completed record and recipe table as PDF or CSV and drops them in a watched folder. The agent runs the same checks and returns the list by email. A few steps stay manual, and the check runs on submit rather than in real time.

WITH PMS API

With API access to the MES or eBR system, the agent reads the completed record and recipe limits directly, checks the moment a batch is submitted, and posts the exception list back to the operator's queue. No manual export. Best experience.

For the person who wants to build this agent step by step. Each node below maps to an n8n workflow node.

TRIGGERNode 1

Trigger - a completed batch record arrives

Watch the eBR export folder or an MES webhook for a submitted batch. Fire on new record.

Output: { batch_id, product_code, file_url, submitted_by, submitted_at }

APINode 2

API - load recipe limits and template

Call the ERP or recipe service by product_code to get the limits table and the master batch record field list.

Output: { product_code, limits[], required_fields[], required_signatures[] }

LLMNode 3

LLM - extract fields, values, and signatures

Send the record text or parsed CSV. The model returns each field with its value and signature status.

Output: { fields[]: { id, value, signed } }

You are checking a completed pharmaceutical batch record for completeness. Extracted record content: {record_text}. Required fields: {required_fields}. Required signatures: {required_signatures}. For each field return its value and whether a signature or witness is present. Respond ONLY with valid JSON. No explanation.

INPUT

{"record_text": "Step 12 charge NaOH 45.2 kg signed JM. Step 14 in-process weight ____ unsigned", "required_fields": ["step12_charge", "step14_ipc_weight"], "required_signatures": ["step12", "step14"]}

OUTPUT

{"fields":[{"id":"step12_charge","value":"45.2 kg","signed":true},{"id":"step14_ipc_weight","value":null,"signed":false}]}

LLMNode 4

LLM - check math, ranges, and completeness

Send extracted fields and recipe limits. The model recomputes totals and yield and compares each value to its limit.

Output: { exceptions[]: { severity, field, note } }

You are verifying math and parameter ranges on a batch record. Fields with values: {fields}. Recipe limits: {limits}. Theoretical yield: {theoretical_yield}. Recompute each total and yield, and compare every parameter to its limit. Return one exception per problem with severity high, medium, or low, the exact field, and a plain note. Respond ONLY with valid JSON. No explanation.

INPUT

{"fields":[{"id":"yield_kg","value":103.0},{"id":"dry_temp_c","value":72}],"limits":[{"id":"dry_temp_c","min":50,"max":65}],"theoretical_yield":100.0}

OUTPUT

{"exceptions":[{"severity":"high","field":"dry_temp_c","note":"Drying temperature 72 C is above the 65 C limit"},{"severity":"medium","field":"yield_kg","note":"Reported yield 103 kg exceeds theoretical 100 kg, reconcile charge and output"}]}

DECISIONNode 5

Decision - exceptions found?

If the exceptions array is empty, mark the record clean and stop. Otherwise continue to ranking.

Output: { has_exceptions: boolean }

ACTIONNode 6

Action - send the ranked exception list

Sort exceptions high to low and post them to the operator's queue or channel with the batch_id.

Output: Message with severity-ranked exceptions, each with field and note

MVP vs Advanced — Where To Start

MVP — START HERE

Watch one folder for eBR exports
Load recipe limits for one product line
Check blanks and missing signatures
Recompute yield and key totals
Email a ranked exception list
Operator fixes before QA submission

ADVANCED — ADD LATER

=+ Live MES webhook on batch submit
=+ Full spec table across all products
=+ Signature and witness audit trail check
=+ Trend repeat exceptions by step and shift
=+ Auto-route clean records to the QA queue
=+ Dashboard of right-first-time rate by line

Full Video Walkthrough Coming Soon

Watch the agent scan a completed batch record and return a ranked exception list in under a minute.

Everything on this page is free to learn.

When you're ready to build — do it yourself or bring us in.

Book a call to scope this

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Frequently asked questions

Batch Record Right-First-Time Checker is an AI agent that flags blanks, unsigned steps, and math errors before the record reaches QA.

The batch record came back from QA. Three blanks, one unsigned step, a yield that did not add up. The Batch Record Right-First-Time Checker addresses this: flags blanks, unsigned steps, and math errors before the record reaches QA.

No. Your team stays in control. The agent does not approve or reject the batch record. Your QA reviewer does. The agent removes the back-and-forth of finding blanks and math errors after submission.

This is 1 of 5 agents in Production & Batch Manufacturing. → · Explore all 15 departments →