Catch defects in real time with computer vision that never blinks. Our AI models detect surface flaws, dimensional errors, and anomalies directly on your production line — before they ever reach your customer.
From edge deployment to root-cause analytics, our visual AI platform covers every dimension of modern quality assurance.
Real-Time Defect Detection
Identify surface flaws, dimensional errors, and color anomalies at full production speed with zero blind spots.
Zero-Shot Anomaly Detection
Deploy inspection without thousands of labeled samples. Our few-shot AI adapts to new products in hours, not weeks.
Multi-Camera Synchronization
Monitor complex assemblies from multiple angles simultaneously — catching what single-camera setups routinely miss.
Inline & Offline Inspection Modes
Inspect on moving conveyor belts at line speed or run offline batch checks — the same AI engine powers both modes.
Root Cause Analytics
Trace every defect back to a machine, operator shift, or raw material batch with built-in SPC dashboards.
Edge & Cloud Deployment
Run on-premises for sub-10ms latency or deploy over hybrid cloud for global scale — your architecture, your choice.
A structured deployment path designed to deliver value fast and keep improving automatically over time.
Step 1
We integrate cameras, lighting, and sensors with your existing production line — no downtime, no line redesign required.
Step 2
Our AI models learn your product’s acceptable quality range using a small set of reference samples — often less than 50 images.
Step 3
Real-time inference flags defects, triggers alerts, and routes non-conforming items away — all within the cycle time of the line.
Step 4
Defect data feeds a continuous retraining loop — accuracy improves week over week, automatically, without engineer intervention.
Have questions? Our FAQ section has you covered with quick answers to the most common inquiries.
What types of defects can your AI detect?
Our AI handles a broad spectrum — surface scratches, dents, cracks, dimensional deviations, color mismatches, missing labels, foreign bodies, fill level errors, and seal failures. New defect classes can be added post-deployment with minimal re-training.
Do I need to retrain the model every time I switch products?
How long does the initial deployment take?
Can your system work with our existing cameras and infrastructure?
What accuracy rates can we realistically expect?
