This fixed-scope discovery sprint is for teams considering computer vision for operations monitoring, safety, occupancy, service workflows, or another real-world environment. In 5 days, you get a practical plan for deciding what to build first and what it will require.

I review the workflow you want to improve, available footage or camera setup, detection and alert needs, data requirements, and deployment constraints. The result is a focused recommendation based on your environment, not a generic AI experiment.

A review of your use case, workflow, and success criteria

Assessment of available footage, camera placement, lighting, and hardware constraints

Recommended detection and system approach for the first release

Data, integration, and deployment requirements

Key technical risks and reliability considerations

A phased roadmap for a production build, including the recommended next step

Teams deciding whether computer vision is viable before committing to a full build

Existing CCTV, IP camera, webcam, or recorded-footage setups

A specific operational question, such as occupancy, queue monitoring, safety events, object detection, or activity tracking

This sprint produces the plan. A production computer-vision system, custom model training, live stream processing, alerts, dashboards, or deployment can be scoped as a separate build after we agree on the findings and priorities.