Turn Existing Cameras Into AI Sensors
Video can be analysed locally on your own network — instead of continuously uploading footage to an external cloud. The cameras are already installed; the intelligence is what we add.
Existing cameras · new intelligenceMost organisations already have hundreds of cameras. Edge AI turns that existing CCTV network into operational intelligence — analysed locally instead of continuously uploading footage to an external cloud.
The Cameras Are Already Installed.
You don't need new sensors. An Edge AI appliance sits beside your existing NVR and switch, analyses streams where they land, and turns video into business signals.
IP cameras, PoE switches and network video recorders are already standard across Indian factories, stores, warehouses, campuses and offices. What's usually missing is a layer that understands what the video shows — locally, in real time, without shipping every frame to an external platform.
Because inference happens on-site, detection keeps working when the internet doesn't — and your video stays on equipment you control.
See the video pipelineBusiness and Operational Analytics, First.
Detections that improve safety, flow and day-to-day operations — configured around your site and your cameras.
Person Detection
Know when and where people are present across your site.
Vehicle Detection
Track vehicle movement at gates, yards and parking areas.
Intrusion Detection
Get alerted when someone enters monitored zones after hours.
Occupancy Analytics
Understand how many people occupy a space, in real time.
Queue Monitoring
Spot growing checkout and counter queues before customers walk.
PPE Detection
Verify helmets, vests and safety gear on production floors.
Restricted-Area Monitoring
Keep sensitive zones under watch without manual review.
Object Detection
Detect unattended items, equipment and assets on camera.
ANPR-Ready Architecture
Infrastructure prepared for number-plate workflows where policy allows.
Retail Analytics
Footfall, dwell and customer-flow insights for every store.
Video Pipeline, Fully On-Site
Streams are analysed where they land on your network — not in a remote data centre.
IP Cameras
LAN / PoE Switch
Edge AI Appliance
AI Analytics
Dashboard / Alerts
Footage stays on the LAN — only alerts and analytics reach your dashboard
A Note on Responsible Deployment
Powerful analytics, carefully bounded
Facial recognition and sensitive surveillance functionality are not enabled by default in EdgeAIIndia deployments. The focus is business and operational analytics — safety, flow, occupancy and day-to-day operations.
- Facial recognition and identity tracking are not part of default deployments
- Analytics concentrate on operations: safety, flow, occupancy and processes
- Your organisation defines its own usage policies, retention rules and access controls
Where any identity-based capability is ever considered, it happens only on an organisation's explicit request — and remains that organisation's responsibility to deploy lawfully.
Why Local Processing Matters for Video
Video is the heaviest data an organisation produces. Processing it on-site changes the economics and the reliability of analytics.
No Continuous Upload
Camera streams stay on your LAN instead of streaming to a cloud.
Lower Bandwidth Costs
Dozens of cameras don't have to saturate your internet link.
Works Through Internet Outages
Detection and alerts keep running when connectivity drops.
Real-Time Alerts
Events trigger with on-site latency — not after a cloud round-trip.
Where Camera Intelligence Fits
The same on-site pipeline adapts across sectors — from a single store to a multi-site campus.
Every deployment is configured around your site, your existing cameras and your own policies. Sizing the hardware? Read choosing hardware for computer vision
Have an edge AI workload? Let's find the right hardware for it.
Tell us what you want AI to analyse on-site — cameras, machines, sensors or another workload — and we'll help map the infrastructure.