Trusted by leading robotics labs and physical intelligence builders

Data for Physical AI & Robotics

The data engine that gets physical AI from the lab to the real world.

Physical AI data is a fundamentally different problem than LLM training – multi-sensor, physics-constrained and unforgiving at deployment. We run production-grade pipelines for the world's leading AV programs. Now, we bring that same rigor to robotics and world models, with data delivered in weeks.

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Trusted by leading physical AI labs and robotics innovators

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  • Train everywhere. Deploy anywhere.

    Diversity scales capability. Power your autonomous systems with egocentric videos and teleoperation data spanning remote digital setups, lab scenarios, outdoor field conditions and factory floors, across hundreds of manipulation tasks, object categories, lighting conditions and occlusion scenarios.

  • Every sensor type. Every modality. In sync.

    Get physics-aware and semantic labels with keypoint tracking, action preference labeling, failure modes, contact points and spatial reasoning across lidar, RGB, depth, force-torque and tactile sensors. Our proprietary platforms handle collection, annotation and QA in one integrated pipeline.

  • From pilot to production, on your timeline.

    Scalable, repeatable data pipelines, from quick experiments to long-term batches timed to your R&D cycles. We set up labs globally, manage hardware procurement and complex data workflows, and handle compliance end-to-end. One vendor, one SLA and one team invested in your continued success.

  • 1M+
    Video hours in progress
  • 70+
    Global delivery centers for data collection
  • 1M+
    Global community available for diverse tasks

End-to-end training data for physical intelligence

Powered by our experience in automotive autonomy, we help robotics labs with sensor setups, hardware integration, foundational training and simulations, and real-world interactions.

One partner from pre-training to production

A single physical AI data partner for every R&D requirement. We guide you from day-0 strategy, to day-1 data capture, to month-1 real-world validation.

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  • Diverse pre-training coverage

    Our globally distributed data solutions are built to handle varying needs and edge cases. This includes data types (e.g., egocentric and wrist-mounted videos, robot manipulation, humanoid interactions), sensor types (e.g., RGB-D, lidar, IMU, force, torque, tactile), cross-embodiment coverage (e.g., single or dual arm, dexterous hands, teleoperation) and collection modes (e.g., digital and remote, onsite moderated, field operations).

  • World model and simulation training

    World model and sim2real training requires high-fidelity reconstructions, spatial mapping and real-world interaction data. We deliver these capabilities alongside expert-led teleoperations, digital twin setups, execution traces, long-horizon activity sequences and the evolving requirements for simulation grounding.

  • High-context, physics-aware annotations

    Our dual-language grounding links task-level intents to fine-grained timestep labels, equipping models with both strategic understanding and granular action grounding. We bridge the gap between lab demos and live deployment by leveraging physics-aware object annotations in Ground Truth Studio and kinematics-aware semantic labels in Fine-Tune Studio, which include complex reasoning and explainability notes.

  • Complex post-training support

    Improve decision robustness and train world model future-state predictions with complex labeling workflows such as explainability narratives for spatial, temporal and physical evaluations, and chain-of-thought reasoning for the same. Our platforms handle collection and annotation for complex sensor-fusion data as well as human-in-the-loop VLA training with action justifications.

Awards and recognition

Celebrating excellence

TELUS Digital was named a Leader in Everest Group's 2024 PEAK Matrix® assessment for data annotation and labeling solutions — one of only five providers recognized out of 19 evaluated. The assessment measured providers across market impact, vision and capabilities.

Access the report
  • PEAK Matrix Data Annotation and Labeling Leader

Unite.AI interview: Bridging the gap from language to physical AI

Steve Nemzer, Sr. Director, AI Growth & Innovation at TELUS Digital, discusses world models and the shift toward reliable agentic AI operations.

One pipeline for every embodiment and every world model architecture

Train world models and robotic and humanoid systems with high-quality data — delivered in weeks.

6 - Data for AI Training