We build computer-vision systems that run in the real world — detecting, classifying, and verifying what's in a video or image stream, at the edge and in real time, with the false-positive control that makes them usable.
A model that scores well on a benchmark is the easy part. The hard part is a system that runs 24/7 on real cameras, in bad light and weather, without drowning people in false alarms or sending raw video where it shouldn't go. That's what we engineer.
We built Prahari — an edge-first, AI-verified CCTV intrusion-monitoring product — end to end: the detection models, the edge software, the rules engine, and the verification layer. That same capability applies anywhere images or video need to become reliable, real-time decisions.
YOLO-class models tuned to your scene — people, vehicles, objects — with tracking across frames.
Vision that runs on-site so it's fast and private — raw video never has to leave the premises.
Multi-stage pipelines that filter noise and surface only the events that matter, in seconds.
Reading text, fields, and structure out of images and scans for downstream automation.
Intrusion, tripwire, and loitering detection on existing CCTV — with near-zero false alarms.
Counting, zone monitoring, PPE and compliance checks, and anomaly detection on a site or floor.
OCR and visual extraction that feeds straight into an automated workflow.
Tell us what you're trying to build. We'll give you an honest read on whether — and how — we can help, with a clear, fixed scope.
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