Introducing Sentinel: Physical AI System for Safety
For years, AI has helped EHS teams identify risks earlier and make faster decisions. But most systems still operate after the fact, analyzing events once they have already occurred. The next step is bringing that same intelligence into the flow of work itself, where movement, machinery, and people intersect in real time.
That is the idea behind Sentinel, Intenseye’s integrated hardware and software system designed to extend real-time safety from the digital layer to the physical floor. Sentinel connects computer vision directly with site operations, giving organizations a new way to see, understand, and act on risk as it unfolds.
How Sentinel Works
Each Sentinel device interprets conditions such as heat, motion, proximity, and speed to build live awareness of what is happening on the floor. Instead of depending on manual observation or periodic reporting, Sentinel delivers continuous visibility across critical areas.
When unsafe activity or environmental change is detected, the system can issue alerts or connect with machinery to stop unsafe motion. This connection between detection and response allows teams to prevent incidents instead of only analyzing them afterward.
The Sentinel Hub
At the center of the system is the Sentinel Hub, a local processor that powers connected devices and cameras. Sentinel is a device suite with purpose-built cameras and sensors, and it also connects to existing site cameras to unify new and legacy infrastructure with minimal changes.
The Hub runs advanced computer vision models on site using NVIDIA Jetson Orin NX, built for high-performance AI at the edge. This local design keeps latency to a minimum, delivers subsecond processing for real-time decisions, and ensures that video remains within the facility’s secured network by default.
Sentinel supports both edge and cloud deployments, combining the immediacy of on-prem decisions with the scale of cloud applications that benefit from large multimodal models. Sentinel is ready to support the next generation of NVIDIA Jetson modules, which will increase throughput and efficiency for real-time video inference so deployments continue to benefit from advances in edge computing.
Real Results in the Field
In pilot programs, Sentinel has already shown measurable results. At CRH Building Products, the team connected Sentinel to their existing PLC systems, allowing it to stop machinery when unsafe motion occurred. The result was a sharp drop in intervention time and a visible reduction in high-severity risks within weeks of activation.
“Even with great training and culture, you cannot guarantee everyone’s safety. With Intenseye’s Sentinel, we are finally closing that gap.”
— Bob Malin
This same setup can be extended to other automated responses, such as triggering local audio warnings or sending instant notifications to operators. Each facility can decide how to respond in real time while maintaining full control over data and configuration.
Privacy and Security by Default
Every Sentinel system is designed to keep control of data in the customer’s hands. Video is processed locally, and anonymization such as face blurring and masking takes place before any footage leaves the site. Each model is trained only on the customer’s own data and is never shared or reused elsewhere.
Intenseye maintains SOC 2 Type 2 certification to ensure that every part of the system meets strict security and compliance requirements. Privacy and data protection are not add-ons but built-in features of every deployment.
Building Toward Real-Time Safety
Sentinel marks a shift in how organizations think about safety. Instead of reacting to what has already happened, teams can now see and respond as conditions change. By embedding intelligence at the edge and complementing it with cloud-scale applications, Sentinel helps safety and operations teams work together faster and with more confidence.
This is the foundation of real-time prevention. And it begins with Sentinel.
👉 Learn more or request a demo at intenseye.com/products/sentinel



