Examples shown use the public VisA dataset to illustrate how batch comparison pinpoints outliers for operators. No customer data is displayed.
Image pairs derived from the Visual Anomaly (VisA) dataset. [1]
Rules-based vision fails when unfamiliar defects appear. Our inspection engine evaluates the natural variation inside each batch so deviations stand out instantly, without seeing or training on them.
Each image is contrasted against the live cohort to highlight novel patterns, materials, or damage.
We connect to your camera feeds and station workflows so findings arrive where action happens.
24/7 system checks and status digests keep quality teams ahead of emerging issues.
Cloud-hosted visual anomaly detection that integrates seamlessly with your manufacturing operations.
Connect your IP camera streams directly to our API. Simple integration with your existing infrastructure.
Images are processed in batches using our zero-shot anomaly detection models, identifying defects without prior training.
Anomalies are flagged and sent to your console for immediate review and action by your quality team.
Complete data isolation and privacy by design. Our zero-shot approach means we never need to train on your images.
Our models work immediately without training on customer data. Your images are processed, not learned from.
All customer data is completely isolated. Only you have access to your images—not us, not anyone else.
Images are processed securely in the cloud with encrypted transit and storage. Your data never leaves your control.
Get in touch to discuss how Fletcher Vision can protect your manufacturing line from defects you've never seen before.
