Golden Sample Inspection AI

Mark a known-good part, compare every part against it, and flag any deviation, with no defect library to start.

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Automated quality inspection comparing a "golden sample" metal part to a "rejected" part highlighting a "missing hole" and a "dent".

Golden Sample Inspection AI for the Toughest High-Mix Lines and New Part Launches

Deploy Anywhere, Run Everywhere
Run golden sample inspection on fixed, robot-mounted, and line scan cameras at any station, on the edge, on-prem, air-gapped, in your VPC, or via API.
One Platform, Full Adoption
Tools every plant team can adopt, from operators who set the golden sample to quality and manufacturing engineers who set the tolerances, no separate ML team required.
Secure, Compliant, and Audit-Ready
Data stays safe with SOC 2 Type II compliance, encrypted data, and an uptime SLA, with an image and a score for every part, tied to its golden sample.

“The vision AI solutions we developed with Roboflow have been a core component of connecting our teams and unlocking their ability to collaborate.”

Lou Stocco

Director of Manufacturing Advanced Analytics, USG

Read the full story See customer stories

Talk to a Vision AI engineer who's shipped in manufacturing.

Bring us your golden sample and we'll map a working solution.

Ask us about:

Solution architecture that fits your stations, SKUs, and quality system
A live demo on images of your own good and bad parts
Deployment options: edge, on-prem, air-gapped, or VPC
ROI modeling against escapes, false rejects, rework, and inspection hours

Over 80,000 organizations build with Roboflow.

Rivian
Pella
Chobani
USG Corporation
BNSF Railway
American Woodmark

Start where you are

Vision AI is transforming businesses

Customers across the board are solving complex challenges and driving meaningful impact.

Automotive customer
$10 million
Saved by automatically detecting defects on the production line
Logistics & freight company
90%
Less time spent manually tracking shipping inventory
Building materials supplier
60%
Lower customer return rate with improved product quality

Compare Every Part to the Golden Sample, from the First Article to the Last Shift

Add a real-time inspection layer to every station with Roboflow vision AI for golden sample inspection. Built for high-mix lines, new part launches, and assemblies where good parts are plentiful, defects are rare and varied, and the inspection standard is a known-good part on the bench.

Learn from known-good parts:

Train anomaly detection on images of good parts only, as in few-shot defect detection, and score every new part against them.
Flag cracks, dents, foreign objects, and defects nobody has labeled yet as deviations from the good set, with anomaly detection.
Score each image against a baseline of good parts with embeddings and outlier detection, as in visual anomaly detection.

Compare to the golden template:

Find each feature of the golden part on every new part with template matching, and flag what is missing.
Detect every component, fastener, and hole, and compare the count and layout to the golden sample, as in rivet inspection.
Measure position and spacing against the golden sample with a Workflow that returns pass or fail for each feature.

Run it across the line:

Keep a golden sample for every SKU, revision, and station, and switch with the recipe.
Route borderline parts to a reviewer, and add confirmed good parts to the reference set.
Send pass and reject signals to a PLC so a deviating part is pulled before it moves on.

Bring intelligence to every station today. Stop deviations from the golden sample from becoming escapes, rework, and customer complaints.

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Frequently asked questions

What is golden sample inspection with vision AI?

Golden sample inspection with vision AI uses one or more known-good parts as the reference and a trained computer vision model (opens in a new tab) to compare every new part against them, flagging missing features, layout changes, and defects that do not match the good parts. It pairs with assembly verification and fastener verification.

Do I need images of defects to start?

No. Anomaly detection learns from images of good parts, and template matching and layout checks compare each part to the golden sample directly, so inspection can start on day one. As defects show up, synthetic defect data and confirmed rejects grow a defect model that names each defect type.

Can it integrate with our line, robots, and quality systems?

Yes. Roboflow writes pass, reject, and score to a PLC tag over OPC UA or MQTT, sends images and results over REST (opens in a new tab) or to a database for MES and quality systems, and runs on robot-mounted cameras, as in vision-guided robotics.

Roboflow serves as the inspection engine, and your quality teams own the golden samples, tolerances, and accept and reject rules.

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Golden Sample Inspection AI