BAV ONE Computer Vision Operating System · Turn existing cameras into programmable AI sensors
Explore the platformDetection alone does not need to create an alert. BAV ONE evaluates operational context and a configured Vision Policy first.
How it works
Each stage remains observable and can be validated independently.
Evaluate class, confidence, zone, direction, time and duration before deciding whether the condition matters.
Route approved events with severity, evidence and accountable recipients instead of broadcasting every model output.
Surface events in AVEKSHA or assessed enterprise integrations while keeping video delivery separate from event metadata.
Capability, compatibility and performance depend on the camera scene, approved models, infrastructure and acceptance criteria. Human review remains appropriate for critical decisions.
Related guidance
Frequently asked questions
No. A Vision Policy determines whether context, duration and severity justify an event or alert.
Yes. BAV ONE supports assessed edge, on-premises, cloud and hybrid architectures. The selected design depends on camera access, compute, bandwidth, data-control and operational requirements.
No. Compatibility depends on stream access, protocol, resolution, frame rate, camera angle, lighting, network conditions and the selected use case. Bharat AI Vision validates these factors before rollout.
Begin with a camera and workflow assessment, then validate a focused one-to-four-camera pilot against agreed operating conditions and acceptance criteria.
Validate before rollout
Map the operating requirement, assess compatible streams and validate a focused workflow before expanding.
