01
Edge
Process close to the cameras when site-level response, connectivity, or bandwidth is central to the decision.
Explore edge deploymentDeployment
Run intelligence where it fits.
Choose an edge, on-premise, cloud, or hybrid shape around the realities of your sites and the teams responsible for them.
AI layer activeDeployment
Architecture follows the operation.
The right answer depends on where the data is generated, where decisions happen, and how the system must be operated.
02
On-premise
Keep processing within controlled infrastructure when governance, integration, or local operations require it.
Explore on-premise deployment03
Existing camera estates
Start from the VMS, NVR, streams, network, and permissions already present at the site.
Assess an existing estate04
Multi-site
Coordinate distributed sites while retaining a deployment shape that each location can actually support.
Explore multi-site deploymentArchitecture decisions
Privacy and deployment are part of the design.
Video placement, retention, access, network paths, model execution, and response integrations should be decided together. Local processing can reduce unnecessary movement of raw video, but it does not by itself make a deployment compliant or secure.
We use a proof of concept to test the practical trade-offs before a larger rollout.
From estate to production
A deployment plan teams can operate.
A useful architecture includes the day-two work: monitoring, updates, permissions, support, and capacity decisions.
Map
Inventory streams, sites, network boundaries, retention, and operational owners.Shape
Select the processing location and integrations that fit the workflow.Prove
Measure quality, latency, resilience, and operator fit on representative sources.Operate
Define monitoring, updates, access, and expansion before scaling.
Plan the architecture
Bring the camera estate and the constraints.
We will help frame a deployment path that can be tested before it is expanded.