Vision systems that ship, to the edge, the cloud, or both.
Detection, segmentation, OCR, and spatial intelligence trained on your data and deployed where it runs fastest.
- Pilot to production
- 0-10wk
- Detection precision
- >0%
- Edge inference
- <0ms
- Less labeled data with active learning
- 0×
Models tuned to your domain, not the COCO benchmark.
Off-the-shelf vision models work on the wrong distribution. We collect, label, and fine-tune on your imagery, manufacturing lines, retail shelves, medical scans, drone footage, and ship the model where it runs.
- Custom detection, segmentation, OCR, and pose estimation
- Active learning to cut labeling cost
- Edge or cloud deployment, your call, our infrastructure
From discovery to production.
- 01
Discover
Walk the workflow, audit the imagery, define the accuracy / latency targets, and pick the deployment topology.
- 02
Prototype with evals
Build a labeled holdout suite first. Models pass when they meet precision and recall targets on your task, not COCO.
- 03
Deploy
To edge devices, your cloud, or both. We handle hardware integration, OTA updates, and monitoring.
- 04
Operate
Active learning loops, uncertain frames flow back to labeling, retraining triggers automatically.
Have an OpenCV pipeline that hit a precision wall?
Book a 30-min consultWhat you get.
Real environments, real failure modes, real evals.
We test against the conditions you actually operate in: low light, motion blur, occlusion, weather. Models go through structured failure-mode analysis before they ship.
- Failure-mode-aware test suites, not just held-out IoU
- Quantisation and distillation for cost-effective edge inference
- Drift detection on production frames, automatic retraining triggers
Common questions.
Move vision off the prototype shelf and into production.
Free 30-minute consultation. We'll tell you whether your task is bounded enough to ship.
Schedule consultation