Industrial-grade AI, engineered to predict
A continuous intelligence stack — from edge inference and computer vision to behaviour modelling and a real-time prediction engine — built for safety-critical scale.
Four stages, milliseconds apart
Every layer of the intelligence stack
Composable engines that perceive, track, reason and predict in real time.
Edge AI
Low-latency inference at the edge keeps video local, reduces bandwidth and delivers sub-second decisions.
Computer Vision
Deep perception models detect people, vehicles, PPE and zones across challenging industrial conditions.
YOLO Detection
High-throughput object detection identifies hazards frame-by-frame with calibrated confidence.
Multi-Object Tracking
Persistent identities across frames and cameras enable trajectory and proximity reasoning.
Behaviour Analysis
Motion, posture and intent modelling distinguishes routine activity from emerging risk.
Risk Scoring
An explainable scoring engine converts signals into a live, auditable risk index per zone.
Prediction Engine
Spatiotemporal models forecast near-miss probability before contact occurs.
Real-time Analytics
Streaming analytics surface trends, hotspots and compliance metrics as events unfold.
From pixels to prevention
A continuous intelligence pipeline that converts raw video into predictive safety action.
CCTV Cameras
Existing infrastructure becomes the sensory layer — no new hardware required.
Computer Vision
Each frame is parsed for people, equipment and PPE in real time.
Object Tracking
Persistent multi-object tracking across cameras and time.
Behaviour Analysis
Motion, proximity and intent are modelled to flag unsafe actions.
Prediction Engine
Spatiotemporal models forecast near-misses before contact.
Risk Score
A live, explainable score quantifies risk per zone and shift.
Alert Engine
Threshold-aware routing to the right people, instantly.
Dashboard
One command centre for live ops, analytics and compliance.
Secure by architecture
Data Security
Encryption in transit and at rest, granular role-based access, and options for on-premise and edge-only processing so sensitive video stays inside your perimeter.
Privacy by Design
Configurable redaction, retention policies and audit trails support enterprise governance and regulatory requirements.
Continuously learning
A closed-loop MLOps process keeps models accurate as your environment changes.
Collect
Site-representative data and feedback loops capture real operating conditions.
Train
Models trained and tuned for each environment, PPE policy and camera profile.
Validate
Rigorous evaluation against safety-critical thresholds before release.
Deploy
Staged rollout to the edge with versioning and rollback.
Monitor
Continuous drift detection and performance monitoring in production.
Improve
Retraining loops keep accuracy high as conditions evolve.
Models and metrics are validated per deployment before production use.
Want a technical deep-dive?
We'll walk your engineering and safety teams through the architecture on your own footage.