Service
Computer vision & visual inspection
We build computer-vision pipelines for inspection and monitoring — detection and segmentation models trained on your imagery, deployed as a service your line or field team can actually use.
What this covers
- Defect detection & segmentation — surface defects, structural flaws, assembly errors; pixel-level segmentation when the shape and extent of a defect matters, not just its presence.
- Dataset strategy — labeling plans, augmentation, and handling the class imbalance that dominates real inspection data, where defects are rare by definition.
- Edge and server inference — models sized for your constraint: GPU server, industrial PC, or embedded device.
- Human-in-the-loop — review queues and confidence thresholds so the system earns trust instead of demanding it.
Where it works well
Manufacturing QC, infrastructure and construction inspection (cracks, spalling, corrosion), and monitoring tasks where a person currently reviews images one by one.
Common questions
- How many labeled images do we need to start?
- Often fewer than teams expect. With modern pretrained backbones and careful augmentation, useful prototypes frequently start from hundreds — not tens of thousands — of labeled examples, and the labeling plan is part of the engagement.
- Can models run on our existing hardware?
- Usually yes. We profile your target — GPU server, industrial PC, or edge device — and choose or distill models to fit its latency and memory budget.
- What accuracy can we expect?
- We never promise a number before seeing data. Scoping includes a quick feasibility pass on your imagery so expectations are set from evidence, not sales copy.