Real-time spatial intelligence
STARE Civic turns the cameras a city already has into a single, live spatial picture. Every vehicle, pedestrian, and robot is tracked with a persistent ID and shared the instant it happens.
The mission: allowing the safe coexistence of robots and humans.
Platform Ecosystem
Own your infrastructure. Privacy-first AI with on-premise deployment and complete data sovereignty.
Power your products with AI perception. Embed real-time spatial intelligence without reinventing the technology.
Connect everything together. Integrate proven spatial intelligence into existing customer ecosystems.
Connect to IP/RTSP cameras, video feeds, thermal cameras, LiDAR, and radar sensors through one unified interface.
Turn video into real-time spatial intelligence by detecting, tracking, georeferencing, and fusing data into a unified operational view.
Deliver actionable data to connected systems through C-V2X/ROS2, 5G connectivity, and one shared operational context.
Every vehicle, pedestrian, cyclist and robot detected and tracked frame-to-frame with a persistent ID that survives occlusion.
Pixels resolved to real-world coordinates sub-meter position, heading and speed, every object on one shared map.
Draw zones, lines and regions. Get live counts, dwell times and flow across the scene without writing a query.
Native C-V2X/ROS2 publishing puts the full scene on the same bus your robots and AVs already speak.
An asynchronous path scores safety, efficiency and accessibility near-misses, violations, congestion and VRU exposure.
The whole pipeline runs on a single NVIDIA edge box. Nothing leaves the network, and there's no cloud to depend on.
System Architecture
Most deployments wire each sensor to each consumer a tangle of point integrations that never quite agree with itself. STARE Civic uses a hub-and-spoke architecture: every sensor converges on one on-premise agent, which publishes a single shared context outward.

Signals that respond to the street as it actually is clearing queues and holding for crossing pedestrians.

Give delivery bots and AVs an over-the-horizon view that reaches beyond their own sensors.

Broadcast live hazards and intent to equipped vehicles before they round the corner.

Catch conflicts and near-misses at crossings in real time and act before they escalate.

Hand responders a live, shared map of the scene the moment they're dispatched.

Turn continuous ground truth into evidence for safer streets no manual counts.
System Architecture
Hardware Compatibility
SoftServ International — Natick, MA
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