Guide
On-Premise Video Analytics for Privacy-Sensitive Facilities
- Author
- DHI Safety OperationsEdge AI ArchitectureReviewed by DHI Engineering
- Published
- 2026-07-02
- Read time
- 9 min read
- Updated
- 2026-07-02
Who this is for
For privacy, legal, IT, and security reviewers at facilities where video movement needs strict control.
The buyer question
How can a facility evaluate video analytics without losing control of raw footage?
Define approved camera zones
The review should start with the camera zones allowed for safety analytics, the event types allowed in each zone, and the teams allowed to receive events.
Separate metadata from footage
Structured event metadata is not the same as continuous video export. The architecture should explain what moves, when it moves, and who approves clips.
Document retention and access
A pilot should define retention, access, audit trails, and clip approval before live alerting begins.
How to use this with DHI
Use this page as a pre-pilot checklist. Pick one zone, one event type, one alert owner, and one review cadence. If the current cameras cannot support the workflow, fix the camera plan before expanding the deployment.
Continue exploring.
- GuideOn-premise privacy guideRead the detailed privacy guide.
- PlatformPlatform architectureReview how DHI runs local inference and routes safety events.
- PricingPricing and pilot scopeSee what changes pilot and rollout scope.
- ContactBook a pilot conversationScope one camera zone, one event class, and one response path.
Validate "on-premise video analytics for privacy-sensitive facilities" on your live feeds.
Coordinate a 30-day architecture review and live camera validation based on the protocol described in "on-premise video analytics for privacy-sensitive facilities" for your facility.
Best follow-up: bring the current workflow that "On-Premise Video Analytics for Privacy-Sensitive Facilities" is supposed to improve.
- Book a demoSee the flow on a real operating scenario and scope a pilot around one facility or corridor.
- See deployment architectureReview camera ingest, edge inference, alert routing, and what stays on-premises.
- Get the implementation checklistDownload the deployment checklist buyers use before green-lighting an industrial AI pilot.
- Talk to an engineerBring camera count, VMS constraints, latency expectations, and privacy requirements to a technical review.