Computer Vision Makes Bi-Directional Material Locks Safe

Computer Vision Makes Bi-Directional Material Locks Safe Read More »

Use Case

Case Study: How AI Prevents Cross-Contamination in Biomanufacturing The Challenge: Preventing Bi-Directional Movement in Material Locks In biopharmaceutical manufacturing, even the smallest mistake can cause serious setbacks. One critical risk area is material transfer in cleanroom environments. Maintaining unidirectional material flow is essential to avoid cross-contamination. Yet despite strict Standard Operating Procedures (SOPs), human error […]

Ensuring Bioreactor Integrity: Computer Vision for Leak Detection

Ensuring Bioreactor Integrity: Computer Vision for Leak Detection Read More »

Use Case

In biologics upstream manufacturing, bioreactor leaks remain a persistent and costly threat. Whether caused by handling errors, faulty connections, or worn seals, even a small leak can compromise an entire batch—leading to contamination, production losses, and expensive downtime. DEEPEYES Leak Detection offers a game-changing approach. Using advanced computer vision technology, it provides continuous, real-time monitoring

From Proof of Concept to Real-Time Quality Control — Preventing Assembly Errors in Seat Production

From Proof of Concept to Real-Time Quality Control — Preventing Assembly Errors in Seat Production Read More »

Use Case

An internationally active automotive supplier based in Germany – one of the world’s largest providers of mechatronic systems for vehicle doors, seats, and electric motors – continuously invests in cutting-edge manufacturing technologies to maintain the highest quality standards in premium car seat production.This production process combines intricate manual steps such as stamping, welding, painting, and

Enhancing Process Safety and Efficiency with DEEPEYES Computer Vision

Enhancing Process Safety and Efficiency with DEEPEYES Computer Vision Read More »

Use Case

Client: Global Top 10 Pharma Manufacturer – US Manufacturing Site The client faced persistent risks in their secondary bottle packaging process, including: Packing mix-ups and mislabeling due to manual errors. Reintroduction of rejected products into the process stream. An average of 11 monthly deviations, requiring significant QA time for video review. Safety non-compliance due to

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