MatriqMatriqTeaching machines to see, analyze, and automate complex physical workflows.
Computer Vision is bridging the gap between the digital and physical worlds. We train and deploy custom deep learning models (YOLO, ResNet, OpenCV) that can analyze live camera feeds and images with superhuman speed and accuracy.
Whether it is detecting millimeter-level fabric defects on an RMG production line, automating license plate recognition for toll booths, or deploying low-latency Edge AI to remote agricultural sensors, we build vision systems that solve real-world industrial problems.
Revolutionize RMG and manufacturing. Our camera systems can instantly detect misaligned stitching, fabric discoloration, and micro-defects on fast-moving conveyor belts, drastically reducing buyer rejections.
Implement frictionless security. We build advanced liveness-detection algorithms for e-KYC onboarding, contactless corporate attendance, and secure, VIP access control zones.
Upgrade infrastructure. Deploy Automatic Number Plate Recognition (ANPR) models for smart parking and toll plazas, or utilize crowd-density tracking for retail malls and event safety.
Extract structured data from unstructured images. We build custom OCR models capable of reading handwritten forms, faded receipts, and complex, multi-lingual government documents.
Modernize agriculture. Process drone imagery or mobile phone photos to assess crop health, estimate harvest yields, and instantly detect early signs of pest infestations or soil disease.
Run AI without the internet. We compress and deploy powerful models directly onto edge devices (like Nvidia Jetson Nano) for zero-latency processing in remote factory environments.