Case Study: Sea Machines achieves scalable, high-quality video annotation for autonomous workboats with Scale AI

Sea Machines - Customer Case Study

Sea Machines Robotics, a Boston-based autonomous technology company that develops advanced control systems for workboats and commercial vessels, needed to annotate large volumes of video to improve perception and control but didn’t want to build an in‑house labeling organization. Sea Machines partnered with Scale AI, using Scale Video for bounding‑box annotations, to get the scalable, flexible data pipelines and labeling expertise required as their data sources and volumes grew.

Scale AI delivered its Scale Video platform plus engineering, QA, and customer operations support to integrate with Sea Machines’ pipeline, providing high‑quality annotations while ramping volumes up and down. The partnership enabled Sea Machines to generate sufficient labeled training and test data to iterate on perception models across multiple vessels, improve system performance, and accelerate global deployments without building internal annotation infrastructure.

Sea Machines

Fiona Hua

Perception/Machine Learning Lead