Quality control

Quality control, run on a platform you build yourself.

Collecta is a no-code platform for running quality control on the shop floor. You build inspection, defect and nonconformance (NCR) modules with the fields your standards require, automate the routing of failures and corrective actions, and use a Claude-powered AI agent to surface defect trends and root causes from your live records.

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The problem

Why quality control is hard today

Quality data ends up scattered across paper checklists, photos on phones, and disconnected spreadsheets. Failed inspections do not reliably trigger corrective action, recurring defects go unnoticed, and audits become a scramble to reconstruct what happened.

How Collecta does it

Modules, automation & AI — working together.

Build the data model, automate the busywork, and reason over it all with the AI agent.

Build Inspections, Defects and NCR modules with custom fields — pass/fail status, measured values (number), photo attachments, severity, and formula fields for defect rate.

Automate routing: when an inspection result changes to fail, open an NCR, notify quality, and require an approval workflow before the affected lot can move on.

Use relation fields to link defects back to the work order, supplier or batch that produced them, so traceability is built into the data, not bolted on.

Ask the Claude AI agent to analyze defect history, identify recurring patterns and likely root causes, and draft the corrective-action narrative for an NCR.

Benefits

What you get with Collecta.

Paperless inspections with photos, measurements and pass/fail in one place.

Failed inspections automatically open and route nonconformances.

Full traceability from defect back to work order, batch or supplier.

Approval workflows gate affected lots until quality signs off.

AI-detected defect trends and root-cause analysis.

Audit-ready quality records with a complete change history.

FAQ

Questions about quality control.

Yes. You design Inspection modules yourself from 17 field types, including number fields for measurements, status fields for pass/fail, and photo attachments — no fixed template, so the checklist matches your standards.

An automation triggered by the status changing to fail can open a nonconformance record, notify the quality team, and start an approval workflow that blocks the affected lot until it is reviewed and signed off.

Yes. The Claude-powered agent analyzes your defect and inspection history through its tools to surface recurring patterns and likely root causes, and can draft corrective-action narratives grounded in your data.

See quality control running on your data.

Book a demo and we'll build the module, wire an automation, and run the AI agent on your own quality control workflow.

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