Deepen AI provides multi-sensor data labelling and calibration tools and services to accelerate computer vision training for autonomous vehicles, robotics and more.
AI performance is fundamentally dependent on data integrity, not just data volume. Deepen AI ensures data is not just labeled - but correct, consistent, and production-ready.
This case study demonstrates that fixing upstream data issues before annotation prevents costly rework and delivers reliable model training datasets.
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To advance AVL’s Dynamic Ground Truth reference system, AVL needed two key things:
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This research involved 30,000 conversations between specialized individuals with diverse backgrounds. The project was completed over a duration of 9 months.
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