Computer Vision

Eyes on your operation. Wired to your systems.

Detection, counting, and inspection on real-world images and video — useful because the results land in the software that runs your operation, not in a dashboard nobody opens.

What we build

  • Detection & counting

    People, products, vehicles, assets — from cameras you already have where feasible.

  • Visual quality control

    Defect and anomaly detection integrated into the production or intake flow, with review queues for edge cases.

  • Document & image understanding

    When the input is photos of the real world: receipts, meters, shelves, sites.

  • Edge or cloud

    Deployment decided by your latency, bandwidth, and privacy constraints, not by fashion.

When teams come to us

  • Manual counting or inspection that doesn't scale
  • Incidents you only discover after the fact
  • A camera investment that never became data

How it starts

The Discovery Sprint validates feasibility on your actual footage before anyone commits to a build.

How we build it

  1. Feasibility on your footage

    We test detection quality on your actual cameras and conditions before anyone commits. The Discovery Sprint can cover this step.

  2. Metrics agreed first

    Precision and recall targets defined with you, on your cases. "It works" gets a number before we build.

  3. Pilot on one line or site

    The smallest real deployment that proves value in production conditions.

  4. Scale and operate

    Rollout with monitoring, review queues for edge cases, and a retraining loop that keeps accuracy honest.

Works well with

FAQ

  • Do we need special cameras?

    Usually not. We start from the cameras you already have — and tell you honestly if they're not enough before you spend anything.

  • What accuracy can we expect?

    It depends on your footage, lighting, and cases — which is exactly why feasibility runs on your real data before any commitment, and targets are agreed as numbers, not adjectives.

  • Cloud or on-site processing?

    Decided by your latency, bandwidth, and privacy constraints — both are on the table, and the answer is an engineering trade-off, not a default.

Turn cameras into operations data.