Scan -> Cluster -> Link Batches -> Rank Risk -> Alert Review Board

Complaint and Out-of-Spec Cluster Signal Agent

This agent scans complaints and out-of-spec results across recent batches and groups the ones that share a pattern. When a cluster crosses your threshold, it links the batches through genealogy, describes the pattern, and ranks the cluster by risk. Your QA review board gets the alert early, while it is still a signal and not a recall.

The Problem

Three complaints, two out-of-spec results, one shared lot. Nobody connected them in time.

A handful of complaints come in over a month, spread across different customers and regions. In parallel the lab logs two out-of-spec assays on separate batches. Each one gets handled on its own, closed as isolated, and filed. What nobody saw was that all five trace back to a single raw material lot, and by the time that surfaces the product is already in the field.

What Changes

The pattern surfaces as a ranked signal, not a post-recall autopsy.

The agent reads the complaint log, the out-of-spec log, and batch genealogy on a schedule and groups records that share a batch, lot, or attribute. It scores each cluster by count and severity and sends the ones that cross your threshold to the QA review board with the linked batches and the pattern spelled out. The board decides whether to open a formal review.

Humans stay in control: the agent flags and ranks the cluster, but your QA review board reviews the evidence and decides whether a formal review or escalation is warranted.

HOW THE AGENT WORKS

TRIGGERLLMAPIDECISIONACTIONWAIT

TRIGGERScheduled cluster scanRuns on a schedule across recent complaints and out-of-spec results.

APIPull complaint and OOS logsReads recent complaints and out-of-spec results with their batch references.

APIPull batch genealogyLoads the parent-child links between batches, lots, and raw materials.

LLMCluster by shared attributeGroups records that share a batch, lot, or attribute into candidate signals.

DECISIONCluster above threshold?

LLMRank clusters by riskScores each cluster by count and severity and recommends an action.

ACTIONAlert QA review boardSends clusters above threshold to the board with linked batches and the pattern.

The agent does not open reviews or make recall calls. Your QA review board does. The agent removes the manual cross-referencing of complaints and out-of-spec results across batches.

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.

Complaint & OOS logsField complaints and lab out-of-spec results

The AgentWorkflow engine + LLM

QA review boardOpens formal review, decides

WHAT YOUR TEAM PROVIDES ONCE

Complaint log - field and customer complaints with batch references
Out-of-spec log - lab results that failed specification with batch references
Batch genealogy - the parent-child links between batches and lots
Risk thresholds - the count and severity that should trigger an alert
Notification channel - where the QA review board receives cluster alerts

What happens day-to-day: the agent runs a scan across recent complaints and out-of-spec results. It groups records that share a batch, lot, or attribute, scores each group, and sends the ones that cross your threshold to the QA review board with the linked batches and the pattern. The board opens the evidence, decides whether to start a formal review, and the routine noise never reaches them.

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

INQUIRY SOURCES

Complaint log: field and customer complaints with batch references and dates.

Out-of-spec log: lab results that failed specification, with batch and test references.

Batch genealogy: the parent-child links between batches, lots, and raw materials.

WORKFLOW ENGINE (N8N)

Scheduled cluster scan

Pull complaint and out-of-spec logs

Pull batch genealogy

Cluster records by shared attributes

Cluster above threshold

Rank clusters by risk

Send alert to QA review board

CONNECTS TO

Complaint system (TrackWise / Veeva Vault QMS / Salesforce)Read: complaints and batch references. Write: nothing

LIMS (LabWare / STARLIMS / LabVantage)Read: out-of-spec results. Write: nothing

Batch genealogy (SAP / MES / Werum PAS-X)Read: batch and lot parent-child links. Write: nothing

Notification (Slack / Teams / Email)Read: nothing. Write: cluster alert to QA review board

WITHOUT PMS API

Without API access, the agent runs on periodic exports of the complaint log, out-of-spec log, and genealogy, and returns a cluster report your QA team reviews. The signal arrives later, but the cross-referencing is still done for you and a human still decides.

WITH PMS API

With API access to your complaint system, LIMS, and batch genealogy, the agent scans continuously and sends ranked cluster alerts to the QA review board as patterns form. The board acts on a live signal instead of a monthly report. 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 - runs the cluster scan on a schedule

Schedule, for example every night, to scan the trailing window.

Output: A run over recent complaints and out-of-spec results.

APINode 2

API - pulls complaint and out-of-spec logs

GET complaint and out-of-spec records with batch references for the window.

Output: Complaint and OOS records ready to group.

APINode 3

API - pulls batch genealogy

GET batch genealogy to link batches, lots, and raw materials.

Output: Genealogy links for the batches in scope.

LLMNode 4

LLM - clusters records by shared batch and pattern

Send records and genealogy; ask for clusters grouped by shared attribute.

Output: Clusters with their linked batches and shared pattern.

You are a QA signal analyst. Group the complaint and out-of-spec records that share a batch, lot, or attribute into clusters.

Records: {records}
Batch genealogy: {genealogy}

For each cluster give the linked batches, the record sources, and the shared attribute. Respond ONLY with valid JSON. No explanation.

INPUT

{"records":[{"id":"C-771","type":"complaint","batch":"B-2207"},{"id":"OOS-44","type":"oos","batch":"B-2209"},{"id":"OOS-45","type":"oos","batch":"B-2213"}],"genealogy":{"B-2207":"RM-88","B-2209":"RM-88","B-2213":"RM-88"}}

OUTPUT

{"clusters":[{"cluster_id":"CL-1","pattern":"Low assay result","batches":["B-2207","B-2209","B-2213"],"sources":["complaint","oos"],"shared_attribute":"Raw material lot RM-88"}]}

LLMNode 5

LLM - ranks clusters by risk

Send clusters and thresholds; ask for a risk score, band, and recommendation.

Output: Clusters ranked by risk with a recommendation.

You are a QA risk analyst. Score each cluster by record count and severity against the thresholds and recommend an action.

Clusters: {clusters}
Thresholds: {thresholds}

Give a risk score from 0 to 100, a band, a one-line reason, and a recommendation. Respond ONLY with valid JSON. No explanation.

INPUT

{"clusters":[{"cluster_id":"CL-1","batches":["B-2207","B-2209","B-2213"],"shared_attribute":"RM-88"}],"thresholds":{"count":3,"severity":"medium"}}

OUTPUT

{"ranked_clusters":[{"cluster_id":"CL-1","risk_score":87,"risk_band":"high","reason":"Three batches share one raw material lot with a matching low-assay signal","recommend":"Open formal review"}]}

ACTIONNode 6

Action - sends the cluster alert to the QA review board

Send clusters above threshold to the QA review board channel.

Output: A ranked cluster alert for the board.

MVP vs Advanced — Where To Start

MVP — START HERE

Start with one product family and its complaints.
Cluster on shared batch and raw material lot only.
Use a simple count-over-threshold rule before adding severity.
Send a plain alert to the QA review board, with no auto-escalation.
Have the board confirm or dismiss each cluster for the first cycle.
Log dismissed clusters so you can tighten the rules.

ADVANCED — ADD LATER

Add out-of-spec trends and stability results as inputs.
Weight risk by severity, customer harm, and batch volume.
Link clusters to the relevant SOPs and prior CAPAs automatically.
Draft a review initiation record for the board to accept.
Track how many flagged clusters became formal reviews to tune thresholds.
=+ Watch for the same pattern across sites, not just one plant.

Full Video Walkthrough Coming Soon

Watch the agent group scattered complaints and out-of-spec results into one ranked cluster alert.

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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Reads the approved change, finds who needs retraining, drafts the assignments

Deviation Triage and Similar-Event Finder

Drafts the deviation, suggests a severity, finds how similar events were resolved

Frequently asked questions

Complaint and Out-of-Spec Cluster Signal Agent is an AI agent that clusters complaints and out-of-spec results across batches, flags the signal early.

Three complaints, two out-of-spec results, one shared lot. Nobody connected them in time. The Complaint and Out-of-Spec Cluster Signal Agent addresses this: clusters complaints and out-of-spec results across batches, flags the signal early.

No. Your team stays in control. The agent does not open reviews or make recall calls. Your QA review board does. The agent removes the manual cross-referencing of complaints and out-of-spec results across batches.

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