BAV ONE Computer Vision Operating System · Turn existing cameras into programmable AI sensors
Explore the platformChoose edge, on-premises, cloud or hybrid architecture per workload. Pricing, hardware, storage and operational responsibilities vary by deployment.
edge
Run approved models close to the visual source for responsive, resilient operations.
on-premises
Operate within customer-managed infrastructure and private networks.
cloud
Centralize approved workloads, administration, analytics and event services.
hybrid
Combine local inference and retention with selective cloud management and visibility.
Reference flow
Technical assessment
Camera count, inference load, latency, bandwidth, retention, resilience, privacy and customer infrastructure determine the architecture and commercial scope.
Feature availability and performance depend on camera compatibility, resolution, frame rate, field of view, lighting, network stability, infrastructure, scene complexity, suitable training data, integration requirements and approved technical scope.
From visual data to enterprise intelligence
Map your visual sources, operating conditions, AI modules, deployment model and integrations with our team.
