Professional Annotation for Vision-Language-Action Models
Transform raw egocentric videos into robot-ready datasets through temporal action segmentation, semantic phase annotation, natural language labeling and multi-stage quality verification.
We help robotics companies convert large-scale first-person manipulation videos into high-quality datasets for VLA models, imitation learning and embodied AI systems.
What We Annotate
Professional annotation services designed specifically for embodied AI and robot learning.
Temporal Action Segmentation
Split long egocentric manipulation videos into meaningful action segments with precise boundaries.
Semantic Phase Annotation
Divide complex manipulation tasks into semantic execution phases for structured learning.
Natural Language Annotation
Generate detailed robot-friendly descriptions for every action segment in the dataset.
Quality Assurance
Multi-stage review ensures annotation consistency and training data quality.