Selection
Included companies are active private technology businesses with a clear role in creating, collecting, transforming, evaluating, or operationalizing data for robotics and embodied AI.
Independent market landscape
Research current as of July 2026
The Physical AI
Data Landscape
A selective map of the startups turning physical experience into training data, simulated worlds, robot demonstrations, and production feedback loops.
Why this layer matters
Robots learn from experience—but useful experience is expensive.
Physical AI needs more than models and compute. It needs synchronized observations and actions, diverse human and robot demonstrations, high-fidelity simulated edge cases, and tools that expose why systems fail after deployment.
These companies are building that connective tissue: the infrastructure that turns motion, sensor streams, and field operations into repeatable learning loops.
Market taxonomy
Five ways to make physical experience computable.
Primary categories define placement. Tags capture overlap between data collection, human input, simulation, and production tooling.
Company landscape
The builders, organized by primary role.
Showing all 18 companies.
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Methodology
A selective, sourced view—not an exhaustive directory.
Categories
Each company receives one primary category based on its most visible offering. Real-world data and teleoperation overlap by design: teleoperation is both an operating method and a way to produce demonstrations.
Funding
Figures use the latest defensible public total through July 2026. “At least” and “approximately” flag incomplete disclosures, calculated totals, or reliance on reputable company databases.
Commercial approach
Profiles describe observable routes to market. Where pricing or monetization is not public, the landscape says so rather than inferring a revenue model.
Research cutoff
Company status and source pages were reviewed through July 18, 2026. Private-company reporting can change quickly; every profile links to its supporting sources for follow-up diligence.