Platform
Edge Intelligence — AI on the Device
Processed on the device. What leaves is anonymous data, not video.
How Edge AI Works
Counting happens on the device, not in the cloud.
Capture
A 12MP sensor sees the queue, the counter and the lane.
Process
NVIDIA compute inside runs the models on the device.
Extract
What leaves is anonymous data, not video.
Deliver
Counts and alerts reach Pulses OS, AI Operators and your systems.
Why Edge, Not Cloud?
Fast, on site
No round trip to the cloud. Alerts start on site.
Privacy by design
What leaves is anonymous data, not video. Insights, not images.
No Cloud Dependency
Devices keep counting when the network drops.
Bandwidth Efficiency
Sending data, not video streams, keeps bandwidth low.
No inbound ports
The device opens no inbound ports to your network.
Edge vs. Cloud Processing
| PULSES EDGE | CLOUD-BASED | |
|---|---|---|
| Latency | On the device | Round trip to the cloud |
| Privacy | Anonymous data | Video in transit |
| Offline | Keeps counting | Waits for the network |
| Bandwidth | Data only | Full video stream |
| Security | No inbound ports | Network-level |
| Scalability | Per-device | Server capacity |
Strategic Partnership
Powered by NVIDIA
Pulses Vision Devices run their models on NVIDIA compute, with NVIDIA-signed firmware.
- Signed
- NVIDIA Device Firmware
- NVIDIA-signed device firmware
- GPU-accelerated computer vision inference
- AI models built to run on the device
- Secure boot
- Model updates over the air
What on-device processing feeds
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Three AI Operators
CX, Ops and Compliance Operators, fed by on-device counts.
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Shared Context Engine
Vision data joined with data from your systems and the time of day.
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Connectors to your systems
Data in from your systems. Alerts out to Teams, Slack, Salesforce and SAP.
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Privacy modes
Anonymous Analytics and Pseudonymous KPIs, chosen per deployment.
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Dashboards
Dashboards, the AI Assistant, MAP View and the API.
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Skill Store
Add skills in plain English or through MCP.
