title: Robotics description: >- DataMesh Robotics generates industrial-grade synthetic training data for embodied AI. Build digital twins, simulate sensors, auto-label ground truth, and export to NVIDIA Isaac Sim/Omniverse and robotics pipelines. tagline: Industrial Synthetic Data for World Model and Embodied AI icon: "\U0001F916" order: 6 features:
- name: Industrial Scene Modeling description: >- Build high-fidelity industrial environments from CAD/BIM, facility drawings, asset libraries, and site constraints — optimized for simulation at scale. icon: Cpu
- name: Photoreal Visual Generation description: >- Generate high-quality RGB and synthetic imagery with controllable lighting, textures, and camera optics — supporting robust perception training across real-world variability. icon: Camera
- name: Physics & Material Properties description: >- Assign physical attributes (mass, friction, restitution, joints, constraints) and material definitions to make interactions realistic — essential for manipulation, contact, and mobility learning. icon: Tag
- name: Auto-Labeled Ground Truth description: >- Generate consistent large-scale annotations such as segmentation masks, 2D and 3D bounding boxes, instance IDs, depth, keypoints, poses, trajectories, and scene metadata. This also includes invisible data like temperature, pressure, and embedded business logic. icon: Tag
- name: Industrial Task Goals & Reward Setup description: >- Define goals, success conditions, and reward signals for industrial tasks: tight tolerances, multi-step procedures, safety constraints, partial observability, and domain-specific semantics. icon: Shuffle
- name: Export to Training & Simulation Stacks description: >- Package datasets and OpenUSD scenes for downstream training, evaluation, and Sim2Real workflows — including integration paths for NVIDIA Isaac Sim/Omniverse and common robotics toolchains. icon: Box faqs:
- question: What kinds of data can you generate? answer: >- We can generate multi-modal datasets such as RGB images, depth, segmentation, instance IDs, 2D/3D bounding boxes, object poses, robot state/trajectories, and scenario metadata. Outputs are configurable to your training goals and target simulator.
- question: Is this only for perception, or also manipulation? answer: >- Both. Perception datasets are common, but DataMesh Robotics is built for embodied tasks where physics matters — manipulation, contact-rich interactions, mobility, and inspection actions.
- question: How do you ensure sim-to-real transfer? answer: >- We combine industrial-accurate geometry and constraints with physics parameters and structured variation (domain randomization).
- question: Can you integrate with NVIDIA Isaac Sim? answer: >- DataMesh Robotics is designed to integrate with OpenUSD-based workflows and can be adapted to support Isaac Sim/Omniverse pipelines depending on your environment and requirements.
- question: Can you work with our proprietary assets? answer: >- Yes. We can ingest your assets and help optimize them for simulation while supporting enterprise deployment options to protect IP.
- question: What does a pilot project look like? answer: >- A pilot commonly includes one target environment, a small set of tasks, a defined dataset spec, an integration path to your training stack, and a performance validation loop. We also have ready-to-use templates to generate generic training data in certain industries.
- question: Can this be deployed on-premise? answer: >- Yes. DataMesh Robotics suites can be used with both cloud and on-premise environments. relatedSolutions:
- name: "Process Simulation" href: "/solutions/process-simulation" relatedCases: []
Overview
DataMesh Robotics generates industrial-grade synthetic training data for embodied AI. Build digital twins, simulate sensors, auto-label ground truth, and export to NVIDIA Isaac Sim/Omniverse and robotics pipelines.
Early Access — DataMesh Robotics is currently available to select enterprise partners. We are working with partners including industrial automation companies to refine simulation-based data generation workflows for real-world robotics applications.
Ready to Accelerate Your Robot Training Pipeline?
Tell us your target robot, tasks, and environment. We'll propose a data generation plan, integration approach, and a demo tailored to your industrial scenario.
Contact us at: robotics@datamesh.com