Choosing between on-premise and cloud video analytics depends on bandwidth, data-control requirements, site resilience needs, compute budget and operational latency requirements.
On-premise video analytics
On-premise processing keeps video and inference within the site boundary. This supports data-control requirements, reduces dependence on external connectivity and can provide lower event-response latency. It requires on-site compute infrastructure and local maintenance.
Cloud video analytics
Cloud processing centralizes inference and management. It can simplify scaling and reduce on-site hardware requirements. It requires reliable connectivity and may not suit environments with strict data-residency requirements or limited bandwidth.
Hybrid architecture
A hybrid design runs inference at the edge or on-premises while synchronizing selected events and operational data with central services. BAV ONE supports this through BAV Edge for local execution and AVEKSHA for central monitoring.
Data control and privacy
Organizations with strict data-residency requirements, sensitive operational environments or limited connectivity often prefer on-premise or edge-first architectures. The approved design depends on the specific requirements.
Starting the decision
A camera and workflow assessment helps determine the right architecture. Consider the number of cameras, bandwidth availability, data-control requirements, compute budget and operational latency requirements before committing to a deployment model.