Physical AI data guides

The best robotics dataset marketplace for 2026 depends on your bottleneck: Hugging Face hosts the largest open robotics dataset catalog at 1,200+ datasets including the cadene/droid mirror at 92,233 episodes and 27,000,000+ frames; Truelabel routes net-new commercial capture to vetted partners with per-contributor consent and 24-72 hour pilot turnaround; Scale AI runs custom enterprise data engines for $200,000-$2,000,000 programs; Encord ships robotics-tooling-plus-capture at $80,000-$400,000 minimums; Roboflow hosts 350,000+ vision datasets useful for perception baselines; and 7 other specialized platforms cover synthetic, teleoperation, and embodiment-specific niches. This 2026 ranking benchmarks 12 marketplaces against 8 verifiable buyer-decision criteria.

• Robotics dataset marketplace
• Best robot learning datasets

The best teleoperation data provider for 2026 depends on your bottleneck: Truelabel routes net-new buyer-specific teleoperation capture to vetted partners with per-contributor consent, single buyer-owned commercial license, and 24-72 hour pilot turnaround at $25,000-$200,000 programs. Scale AI runs custom enterprise teleoperation programs at $200,000-$2,000,000+. Encord ships robotics tooling-plus-capture at $80,000-$400,000. Open public alternatives include DROID's 76,000 demonstrations on Franka Panda, BridgeData V2's 60,096 trajectories on WidowX 250, RoboSet's ~28,000 kitchen-scale episodes, and AgiBot World's 1,000,000+ episodes for humanoid teleop. This 2026 ranking benchmarks 10 teleoperation data providers against 8 buyer-decision criteria.

• Teleoperation data providers
• Teleoperation dataset marketplace

The best VLA training data provider for 2026 depends on which VLA family you're training: OpenVLA (7B parameters trained on 970,000+ episodes from Open X-Embodiment) typically pretrains on the OXE corpus then fine-tunes on net-new buyer-specific data; π0 (Physical Intelligence) and GR00T (NVIDIA) require embodiment-specific commercial-license data at 5,000-50,000 demonstrations per task family. The top 10 providers in 2026: (1) Hugging Face cadene/droid mirror at 92,233 episodes, (2) Truelabel for net-new commercial capture, (3) Scale AI for enterprise programs, (4) Encord for tooling-plus-capture, (5) Open X-Embodiment portal for cross-embodiment baseline, (6) BridgeData V2 for WidowX 250, (7) RoboSet for kitchen-scale manipulation, (8) RH20T for contact-rich tasks, (9) AgiBot World for 1M+ episode scale, (10) Appen for broad multi-modal capture.

• VLA training data providers
• Vision Language Action data

Data provenance is the record of where a dataset came from, how it was collected, who consented, what rights are attached, and how it changed before delivery. For physical AI, provenance is critical because training data can include people, private spaces, robots, facilities, and proprietary workflows.

• Consented training data
• Licensed robotics data

Egocentric data captures the task from a first-person wrist-camera point of view, while exocentric data captures the scene from an overhead or external third-person camera. Robot learning teams use egocentric data for dexterous interaction cues and exocentric data for workspace context, QA, and cross-robot transfer.

• Egocentric video data
• Exocentric video data

Hugging Face Hub hosts 1,200+ robotics datasets across 8 license categories: Apache-2.0 (cadene/droid is the canonical example with 92,233 episodes, 27,000,000+ frames, 401 GB), MIT (BridgeData V2 at 60,096 trajectories), CC BY 4.0 attribution-required (RoboNet), CC BY-NC 4.0 non-commercial (a meaningful subset), research-only with named-PI Data Use Agreement (Ego4D), custom-research with case-by-case commercial exception (multiple lab-specific datasets), and no-license-file (10-20% of robotics datasets — buyer must contact maintainer). For commercial training in 2026, only the Apache-2.0, MIT, and CC BY 4.0 categories are usable without further negotiation, and even those require per-dataset NOTICE files and indemnification riders. This 6-step buyer audit checklist covers the full review.

• Huggingface robotics dataset license
• Hf robotics dataset commercial use

The best physical AI data company depends on your bottleneck. Scale AI and Appen win when you need enterprise-managed labeling. Encord and V7 Darwin win when you need labeling tooling you can own. NVIDIA Cosmos and Isaac Sim win when synthetic data is part of the mix. Open X-Embodiment, DROID, and BridgeData V2 are the public-dataset workhorses. Truelabel sits underneath all of these as a marketplace that routes specific physical AI data needs — egocentric, teleop, manipulation — to vetted capture partners.

• Physical AI data providers
• Robotics training data companies

Buying physical AI training data in 2026 means navigating 6 modality classes (egocentric video, teleoperation, robot demonstrations, evaluation, synthetic, multimodal sensor fusion), 22+ embodiment types (Franka Panda, WidowX 250, UR5e, xArm 7, Stretch 3, Kuka iiwa, Sawyer, ALOHA, Mobile ALOHA, AgiBot, Unitree, custom humanoid), 8 license categories (Apache-2.0, MIT, CC BY 4.0, CC BY-NC 4.0, research-only, commercial-only, custom-research, no-license), and 5 delivery formats (RLDS, MCAP, Parquet, HDF5, LeRobotDataset v3.0). This 8-step buyer's guide covers vendor selection, sample QA gates, contract terms, and pricing benchmarks for 2026 procurement programs.

• Physical AI training data procurement
• Physical AI data buying

Robotics data annotation companies in 2026 split into 4 tiers: (1) enterprise data engines (Scale AI at $200K-$2M+ programs, Appen at $50K-$500K, Labelbox at $60K-$400K); (2) tooling-plus-capture specialists (Encord at $80K-$400K, Roboflow Universe at $0-$60K/year, V7 at $30K-$200K); (3) sensor-fusion specialists (Kognic for LiDAR + multi-camera, Segments.ai for point-cloud, Sama for global-south capture); (4) marketplace platforms (Truelabel for net-new commercial capture at $25K-$200K, Hugging Face Hub for open-license hosting). The right pick depends on your sensor stack, embodiment, license posture, and program budget. This 2026 buyer guide ranks 12 vendors against 8 criteria with 50+ verified facts.

• Robotics annotation companies
• Robotics data labeling vendors

Robot demonstration data shows how a task should be performed. Teleoperation data is a specific kind of demonstration captured while a human controls a robot and records robot actions, states, and observations. Buyers should choose based on whether they need human behavior, robot action traces, or both.

• Teleoperation data
• Robot demonstration data

Vision-language-action (VLA) training data acceptance criteria for 2026 cover 10 gates: (1) RLDS schema compliance, (2) language_instruction quality with 90%+ reviewer agreement, (3) embodiment match including Franka Panda firmware and gripper SKU, (4) action-schema time-alignment within 5 ms, (5) sensor-fidelity at 1080p / 30 fps minimum, (6) task-success labels with reviewer disagreement under 8%, (7) license + per-contributor consent harmonization, (8) coverage across 30+ objects / 5+ lighting conditions / 3+ background variations, (9) metadata completeness with timestamp and operator_id (hashed), (10) format integrity with time-sync drift under 5 ms. Reject batches that miss gates 1, 3, 7. Reject the program if gates 2, 5, or 6 fail above threshold. This checklist is the 2026 default for OpenVLA, RT-2-X, π0, and GR00T training programs.

• VLA acceptance criteria
• VLA dataset QA

Physical AI training data is data that teaches models to perceive, reason about, and act in the physical world. It can include video, robot states, actions, teleoperation traces, human demonstrations, pose, tactile signals, environment metadata, and consent artifacts.

• Physical AI dataset
• Robot training data