Deepen argues annotation pipeline is safety-critical
It explains how data quality failures cause perception errors in ADAS, citing ISO 26262, SOTIF, and Euro NCAP 2026. Deepen offers a unified platform for calibration, annotation, and validation.
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Safety-first data lifecycle tools and services for autonomous systems
deepen.aiLast updated
In short: Deepen secured seed funding, patented new sensor calibration tech, and launched a unified Physical AI data suite for autonomous systems.
It explains how data quality failures cause perception errors in ADAS, citing ISO 26262, SOTIF, and Euro NCAP 2026. Deepen offers a unified platform for calibration, annotation, and validation.
The platform automates calibration for AV, ADAS, and robotics sensors with high accuracy using minimal real-world data. It supports LiDAR, radar, cameras, IMUs, and GNSS in a single workflow.
The award recognizes their team's work in building data infrastructure for Physical AI systems like autonomous vehicles and robotics. They provide end-to-end solutions including data collection, annotation, and safety evaluation.
The tool bridges perception and action for robotics and autonomous vehicles using Chain of Causation. It supports multimodal understanding, actionable outputs, evaluation, and enterprise readiness.
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