14 patents. 60 engineers. Deployed across 340+ factories. Our technology stack is purpose-built for the demands of UK manufacturing — not adapted from consumer AI or academic research.
From camera to cloud, every layer of the VisionForge platform is optimised for industrial precision, reliability, and scale.
VisionForge's proprietary training pipeline reduces the data required for custom model training by 80% versus standard deep learning approaches — achieving production-ready accuracy with as few as 200 labelled examples per defect class.
Achieve 95%+ accuracy with as few as 50 examples per class using our meta-learning framework.
Models identify their own uncertainty and request human labelling of the most informative new examples.
All models compiled to TensorRT for NVIDIA GPU acceleration — achieving <2ms inference at 4K resolution.
Grad-CAM visualisations show exactly which image regions triggered each classification decision.
VisionForge AR overlays inspection results, assembly guidance, and defect highlighting directly into the operator's field of view — reducing training time and improving first-time-right rates across assembly operations.
Compatible with HoloLens 2, Magic Leap, and industrial smart glasses platforms.
Defect locations projected onto physical parts with sub-5mm spatial accuracy using visual SLAM.
Compact 4K industrial camera unit with integrated LED controller and GigE Vision interface. IP65 rated.
DIN-rail mounted edge AI server with NVIDIA A2 GPU. -20°C to 70°C. <2ms inference. IP67 optional.
640×512 LWIR thermal camera with 7.5μm pixel pitch and ±1°C accuracy for predictive maintenance.
Stereo structured-light 3D sensor for ±0.02mm volumetric measurement and bin-picking applications.
8-channel LED illumination controller supporting ring, dome, darkfield, coaxial, and UV configurations.
24V industrial I/O module for conveyor trigger, rejection gate, alarm, and SCADA digital signals.