Edge-based vision AI for pose/action analytics and event detection, delivered from PoC to production deployment and operations.
Second-level alerts for falls, abnormal actions, intrusion, and loitering.
Offline operation to reduce bandwidth and cloud costs.
Integrates with dashboards, access control, and notifications.
On-device Latency
Stability & Monitoring
Delivery Process
Focused on pose/action analytics, security event AI, and in-vehicle vision—each with capabilities, use cases, and deliverables.
Improve response time, reduce false alarms, and provide traceable incident evidence.
Inference SDK, rule configuration, deployment guide, alert integration (Webhook/API), and a demo dashboard.
Convert video into actionable alerts for earlier risk detection.
Detection models, rule sheets, alert integration, logs/monitoring plan, and an operations manual.
Low-latency, production-ready edge vision for cabin and road scenarios.
On-device package, performance report, integration APIs, production checklist, and an OTA/retraining plan.
From requirements to production and ongoing operations. You may also select Production or Operations only.
Validate feasibility, KPIs, and risks to accelerate decision-making.
PoC report, demo, test data, recommended architecture, and timeline.
Deliver deployable, maintainable, and scalable model capabilities.
Inference SDK, deployment docs, integration APIs, performance report, and production checklist.
Ensure long-term stability, reduce false alarms, and continuously improve accuracy.
Operations manual, monitoring plan, retraining plan, and release strategy.
Reduce night-time risks and shorten response time through pose/action sequence analysis.