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FLAGSHIP AI QUALITY AGENT

CAPA Intelligence
Agent

Build stronger investigations in less engineering time.

Retrieve similar events, expose missing evidence and prepare a source-linked investigation draft - while your authorised quality professionals retain every decision and approval.

Human approvalSource lineageRead-only start
CONTROLLED CAPA WORKFLOWHUMAN IN CONTROL
NEW QUALITY EVENTCNC dimensional varianceNCR-2026-0148
QAICAPA
INTELLIGENCE
SIMILAR EVENTS6source-linked
EVIDENCE COVERAGE82%3 gaps flagged
DRAFT STATUSReadyfor investigator review
1
REQUIRED NEXT STEPInvestigator review and approval
REDUCEInvestigation administration
IMPROVEEvidence coverage and consistency
REVEALSimilar events and recurrence
RETAINHuman accountability
THE CUSTOMER PROBLEM

CAPA teams do not need
another blank form.

They need the relevant history, evidence and controlled documents brought together before scarce engineering time is lost searching for them.

01

History stays fragmented

Similar events sit across NCRs, complaints, audits and shared folders under inconsistent language.

02

Evidence varies by investigator

Preparation quality depends on experience, memory and the time available to search.

03

Administration delays action

CAPAs remain open while engineers reconstruct context that already exists somewhere in the business.

THE CONTROLLED WORKFLOW

From quality event to
review-ready investigation.

CAPA Intelligence supports the preparation work around an investigation. It does not declare root cause, approve disposition or close the CAPA.

01

Structure the event

Normalise the problem description and identify the affected product, process, supplier, equipment and site.

02

Retrieve relevant history

Find similar NCRs, complaints, audit findings, previous CAPAs and controlled documents.

03

Expose evidence gaps

Create an investigation plan and show which records, checks or interviews are still required.

04

Prepare the draft

Draft the problem statement, containment summary and testable hypotheses with every source attached.

05

Route for human approval

The named investigator edits, approves and exports the controlled output to the existing QMS.

CUSTOMER DELIVERABLES

Useful outputs.
Visible evidence.

Every pilot is designed around an agreed system of record and a named human approval point.

01

Similar-event evidence pack

Relevant historical events, recurrence links and previous corrective actions with direct source references.

02

Investigation preparation pack

A structured problem statement, evidence request list and investigation plan for accountable review.

03

Controlled draft support

Containment and corrective-action drafting assistance clearly separated from authorised decisions.

04

Value and governance report

Measured improvement against baseline, user acceptance, source lineage and the production recommendation.

FIXED-SCOPE VALUE PROOF

The eight-week
CAPA Intelligence Pilot.

One site. One CAPA or NCR workflow. One primary data source. Up to 10 users. A bounded engagement with a clear decision at the end.

Week 1

Baseline and controls

Confirm scope, success measures, data access, accountable owners and approval gates.

Week 2

Data mapping

Prepare a representative historical sample and map the primary source into a controlled evidence structure.

Weeks 3-4

Retrieval and workflow setup

Configure similar-event retrieval, evidence checks, source lineage and the investigation draft workflow.

Weeks 5-6

Controlled user trials

Quality users test real or representative cases while QAI measures relevance, effort and reviewer rework.

Week 7

Refine and verify

Tune the workflow, confirm governance controls and compare results with the agreed baseline.

Week 8

Value report and scale decision

Deliver the verified improvement report, controlled operating guide and recommendation for production use.

Included in the pilot

  • Baseline and measurable value hypothesis
  • Representative historical sample
  • Similar-event retrieval and evidence-gap workflow
  • Source lineage and human approval controls
  • User testing, training and operating guide
  • Final verified improvement report

Deliberately outside the pilot

  • Autonomous root-cause or disposition decisions
  • Automatic CAPA closure or product release
  • Replacement of the customer's QMS
  • Multi-site or enterprise-wide rollout
  • Unscoped data migration or systems integration
  • Claims of compliance or certification
VALUE PROOF

Success is agreed
before configuration.

The pilot compares the controlled workflow with the customer's current baseline. No vague claims and no value declared without customer verification.

  1. 01Investigation preparation hours per event
  2. 02Median investigation and CAPA cycle time
  3. 03Evidence completeness and reviewer rework
  4. 04Similar-event retrieval acceptance rate
  5. 05Recurrence visibility after corrective action
Q+
GOVERNANCE BOUNDARY

Evidence supports judgement.
People remain accountable.

The agent may retrieve history, flag evidence gaps and suggest testable hypotheses. It never declares root cause, approves disposition, closes CAPA or releases product.

Customer-approved sourcesLeast-privilege accessPrompt and version controlsRecorded human approval
THE BUYING JOURNEY

Diagnose. Prove.
Operate.

Begin with evidence, progress to a bounded CAPA pilot and move into managed production only when the value report supports it.

OPTIONAL ENTRY

Quality Cost Assessment

GBP 3,500

5-10 working days to map quality workload, cost, data readiness and the strongest value case.

50% credited against a pilot commissioned within 30 days.
FLAGSHIP

CAPA Intelligence Pilot

GBP 19,500

Eight weeks, one site, one CAPA/NCR workflow, one primary data source and up to 10 users.

Fixed scope. Prices exclude VAT.
PRODUCTION

Core Managed Service

GBP 2,500/month

One site and one workflow with monitoring, support and a monthly value report.

Annual service following a successful pilot.
START WITH YOUR CAPA WORKLOAD

Is there enough value
for a controlled pilot?

Book a free 30-minute Quality Value Call. We will test the use case against urgency, measurable workload, available data and the governance boundary.

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