A practical guide to multi-view, multi-modal, and temporal data at scale
Annotation breaks at scale not because labels are wrong, but because continuity breaks across views, time, and interpretation.
This guide explains how high-performing teams design annotation systems that preserve consistency under production load. It gives AI Project Owners a clear execution model to prevent rework, QA bloat, and unpredictable cost growth.
Sama provides ML Professionals and AI team Leads with an indispensable solution for Computer Vision data labeling.
