enGrasp AI
Video 12 provides an AI-driven platform that converts raw driving video footage into actionable insights. Its pipeline extracts contextual data, analyzes driver behavior, and determines incident accountability, automatically generating detailed reports for drivers, fleet operators, and insurers. For example, the system can flag a harsh‑braking event caused by a pedestrian entering the road and issue a “Pedestrian in Danger” alert.
- Artificial Intelligence
- Data & Analytics
- Enterprise Software
- Logistics & Supply Chain
Funding
Founders
Product
Problem
Fleet operators, insurers, and drivers often collect large amounts of dash‑cam video but lack efficient tools to extract actionable safety and risk insights from that footage. Manual review is time‑consuming, inconsistent, and unable to reliably determine driver behavior or incident fault.
Solution
Video 12 offers an AI‑driven analytics pipeline that automatically processes raw driving video to identify contextual elements (road environment, traffic signals, pedestrians) and precise driver actions (harsh braking, acceleration, lane changes). The system evaluates each event’s intent and severity, generating incident accountability assessments that distinguish safe versus risky maneuvers. Tailored reports provide drivers with performance feedback, fleet managers with safety metrics, and insurers with evidence‑based risk evaluations. By converting video into structured behavioral data, Video 12 enables proactive safety coaching, risk mitigation, and more accurate claims handling without manual video review.
Target Audience
Primary customers are commercial fleet operators, motor insurers, and professional driver training programs that require scalable, data‑driven safety insights from dash‑cam video.
Features
- Computer‑vision models that detect and classify road context such as traffic lights, pedestrians, and vehicle proximity
- Behavior analysis algorithms that pinpoint driver actions like harsh braking, rapid acceleration, and lane deviations
- Incident accountability engine that assesses fault and generates “Pedestrian in Danger” or similar safety alerts
- Automated report generation with driver evaluation, event summaries, and actionable safety advice
- API integration for seamless ingestion of dash‑cam footage from fleet telematics systems