Case Study: Optimus Ride achieves faster, higher-quality labeled data for autonomous vehicle perception with Scale AI

Optimus Ride - Customer Case Study

Optimus Ride, a Boston-based developer of autonomous vehicles for geo‑fenced environments, was collecting far more sensor data than its team could label in-house as it expanded into new deployments. To speed up annotation and raise label quality, Optimus Ride engaged Scale AI and adopted Scale 3D Sensor Fusion - Cuboid Annotation and Scale Image - Bounding Box Annotation.

Scale AI delivered fast, SLA-backed annotations, APIs and logging to automate workflows, and processes to flag and resolve edge cases, giving Optimus Ride higher-quality training data and shorter labeling cycles. With Scale AI’s labeled data, Optimus Ride accelerated perception development, increased trust in its models, and supported deployments across four states and Washington, D.C.

Optimus Ride

David Robert

Head of Product