Machine Vision

Object recognition, behaviour analytics & species counting

Vision systems that turn camera streams into decisions — recognising objects, reading fine-grained detail and spotting behaviour as it happens, deployed on the edge alongside the cameras already on site. From recognising and valuing objects to reading behaviour and counting wildlife — vision pipelines built to run in real time on the edge.

Core Capabilities

From recognising and valuing objects to reading behaviour and counting wildlife — vision pipelines built to run in real time on the edge.

• Casino chip recognition. — Vision models identify chip denominations, count stacks and value bets on the table in real time, feeding game-pace and exposure data back to the operator.
• Cheating & collusion detection. — Movement and action recognition flags irregular play and collusion at the table as it happens, rather than after the money has gone.
• Retail loss prevention. — The same behaviour-analysis approach spots the movement patterns of shoplifting from existing store CCTV, surfacing alerts instead of unwatched footage.
• Wildlife & species counting. — Fine-grained classification recognises individual bird species from field cameras to count vulnerable and protected populations automatically.
• Edge-deployed, real-time pipelines. — Detection, tracking and alerting run on modest on-site hardware with no cloud round-trip, keeping latency low and sensitive footage local.

How it works

Object & fine-grained recognition

We build models that don't just see an object but read it. For a casino operator we recognise gaming chips on the table — telling denominations apart, counting stacks and valuing bets in real time — and for a conservation project we classify individual bird species from field cameras to count vulnerable populations automatically, work that would take a specialist days by hand.

Behaviour & movement recognition

Beyond what is in frame, we analyse how people and objects move. Our movement-recognition models flag suspicious play and collusion at the casino table, and the same approach is reused for retail loss prevention — spotting the body language of shoplifting from existing CCTV — turning hours of footage no one watches into alerts staff can act on.

Real-time, edge-deployed pipelines

We engineer the whole pipeline — capture, detection, tracking and alerting — to run on modest hardware next to the cameras, with no cloud round-trip. That keeps latency low enough for live tables, keeps sensitive footage on site, and lets the same system run unattended at a remote field location.