Case study · AI · Computer Vision

Insight Vision: real-time object detection without a GPU server

YOLO object detection running at full speed, inside the browser tab.

Visit live site
0Frames sent to a server

Challenge

Insight Vision demonstrates that production computer vision no longer needs a GPU server: it runs YOLO object detection on images and live video streams directly in the browser. Model inference executes through WebAssembly, so frames never leave the user’s machine: detection is instant, private by default, and free of round-trip latency.

Approach

We engineered the full application in Next.js and TypeScript, handling the unglamorous parts that make in-browser ML feel effortless: efficient frame capture from live video, model loading and warm-up, and a detection overlay that keeps pace with the stream. It’s live to try at insight-vision.vercel.app.

Outcome

Detection runs entirely on the user’s device: instant, private by default and free of round-trip latency or GPU hosting costs.

The application proves that production computer vision can run in the browser, and it is live to try at insight-vision.vercel.app.

Key results

  • YOLO inference compiled to WebAssembly, in-browser
  • Real-time detection over live video streams
  • Frames never leave the device, private by default
  • Live demo at insight-vision.vercel.app

Gallery

Inside Insight Vision

Get in touch to discuss your software vision with senior engineers

We use your details only to reply to your request. For more info please consult our privacy policy.