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Figure AI
Figure AI logoFigure AI · Feature trail

Physical Dataset Collection and Processing

1 post · Aug 2026

What this trail covers

Figure AI has launched 'Index', a proprietary pipeline for collecting and processing a massive, diverse physical dataset for robot training. This system ingests over 30 minutes of video uploads per second from a global network of 'Creators'. The pipeline includes five stages: filtering for technical, visual, and semantic quality; fraud review; deduplication to maintain diversity; rebalancing using task quotas and embedding-based clusters; and hierarchical text caption generation. The goal is to enable the generalization of AI models like Helix for robotics. The system has scaled to over 264,000 app downloads across 100+ countries with over 44,000 weekly active users, processing 16M videos and paying out $15M to Creators. Figure AI plans to invest over $1B in data and compute in the next 12 months.

All Figure AI trails
  1. Introducing Index: Building The World’s Largest and Most Diverse Physical DatasetThis post details the technical architecture and operational scale of 'Index', Figure AI's proprietary pipeline for collecting and processing physical data for robot training. It describes the five-stage pipeline: automated filtering for quality, human-led fraud review, embedding-based deduplication for diversity, rebalancing using task quotas and clustering, and hierarchical text caption generation. The system handles 30 minutes of video uploads per second, requiring robust infrastructure for 24/7 availability and large-scale compute. The post highlights the challenges of sourcing diverse, real-world data at scale and the technical solutions implemented to overcome them.