Turnyourcamerasintosafetyintelligence
Detect accidents, near-misses, and hazards in real-time. Edge-native AI that works with your existing CCTV infrastructure.
Near-Fold Proof
The homepage should answer the core category questions immediately.
These proof points are written as text so category traffic and AI-assisted search systems can understand the deployment model, speed profile, and operating fit without relying on a demo.
Deployment model
Dhi runs on your current camera estate without forcing a rip-and-replace hardware program.
Latency
Real-time detection and escalation happen at the edge so the alert arrives while operators can still intervene.
Privacy posture
Raw footage stays inside your environment unless you explicitly approve otherwise.
Supported environments
The operating model is designed for rail platforms, depots, warehouses, docks, and high-risk industrial zones.
Measurable outcomes
Teams use Dhi to reduce incident-discovery time, surface unsafe behavior earlier, and benchmark pilot performance quickly.
Edge-native architectureEdge-native architecture
Built for speed, privacy, and reliability in harsh environments.
Ingest
Connects to existing RTSP/ONVIF cameras. No new cabling required.
Process
Edge AI processes video locally. <200ms latency per frame.
Protect
Privacy firewall ensures only structured events leave your site.
Alert
Real-time notifications to safety teams via SMS, Email, or API.
See Dhi in your environmentSee Dhi in your environment
Select an industry to see how our edge AI identifies and prevents specific hazards in real-time.
Train Station
Monitor platform edges, track intrusion, and crowd density in real-time.
Active Detections
Why Edge AI?Why Edge AI?
The cloud is too slow for safety. Dhi brings intelligence to where the data is generated.
Real-time Latency
Process video in <ms. Detect incidents as they happen, not hours later.
Offline Capable
Zero dependency on internet bandwidth. Works when the cloud is down.
Privacy First
Raw video never leaves the device. Only structured data is transmitted.
Edge Compute
Runs on NVIDIA Jetson & industrial x86. Optimized for low power.
Production-ready infrastructure
Dhi is validated on enterprise-grade hardware and designed to integrate with your existing systems.
Validated hardware
Tested on NVIDIA AGX Orin, Jetson NX, and industrial x86 edge nodes.
VMS integration
Plug into Genetec, Milestone, Avigilon, and other major video management systems.
Protocol support
Native RTSP and ONVIF support for seamless camera connectivity.
Enterprise integrations
Connect to incident management, ticketing, and SIEM systems via API.
Built for compliance and trust
Dhi's architecture is designed to meet the requirements of unions, regulators, and security teams.GDPR Compliant • SOC 2 Ready • Edge-Local Data
View security detailsContinue Exploring
See how Dhi fits transit operations
Move from category research into a concrete operating environment with platform, station, and yard workflows.
Compare edge AI against cloud AI
Review the latency, privacy, and operating tradeoffs before you commit to an architecture path.
Open the pilot planning checklist
Use the implementation checklist that maps category interest into a scoped first deployment.
Choose the fastest next step.
Category visitors usually need a lightweight way to move from research into architecture review, checklist download, or an actual pilot conversation.
Start narrow. You do not need a full estate-wide rollout to validate Dhi.
Request a demo
See the flow on a real operating scenario and scope a pilot around one facility or corridor.
See deployment architecture
Review camera ingest, edge inference, alert routing, and what stays on-premises.
Get the implementation checklist
Download the deployment checklist buyers use before green-lighting an industrial AI pilot.
Talk to an engineer
Bring camera count, VMS constraints, latency expectations, and privacy requirements to a technical review.