We help robotics teams go from CAD files to trained policies in days, not months. Deep expertise across Isaac Sim, Isaac Lab, Genesis, MuJoCo, and the full Physical AI stack — including any custom engagement you need.
3 weeks to import a single robot arm. 6 weeks tuning physics. 3 months closing the sim-to-real gap. These aren't niche issues — they're the dirty secrets of robotics simulation, costing teams months before a single line of autonomy code gets written.
Here's one real example we see every week in the industry →
We solve all of them — so your team can focus on autonomy, not plumbing.
From raw CAD files to deployed policies on real hardware. Six focused practices plus any custom engagement — all delivered by specialists who ship production code.
Everything needed to get your robot into simulation — correctly. CAD, STEP, URDF, MJCF, Blender exports in — physics-validated, articulation-ready assets out.
Full-fidelity digital twins of your facilities, production lines, and robot cells. Real-time synchronization with physical systems for monitoring and optimization.
Bridge the reality gap with systematic domain randomization, physics calibration, and iterative policy validation. Proven methodologies — including zero-shot deployments we've already shipped.
Custom environment design, reward engineering, and GPU-accelerated policy training across Isaac Lab, Genesis, MimicGen, MobilityGen, and other frameworks.
Generate millions of annotated training samples for vision, LiDAR, and multi-sensor perception models. Physically-accurate environmental effects included.
Turnkey deployment to all NVIDIA Jetson platforms, DGX Spark, DGX workstations, and custom edge hardware. ROS2 integration and containerized delivery.
We take on bespoke robotics engineering work — proprietary simulators, novel sensor integration, unusual robot morphologies, industry-specific pipelines. If it involves robots, physics, and code, we've probably solved something similar.
A cross-section of recent reference projects, from humanoids and quadrupeds through deformables, fluids, industrial lines, and digital twins. Cards with multiple clips include a prev/next control. Videos stream only when a card scrolls into view, so the page stays fast.
This isn't a single project — it's a pipeline we ship. Data collection (VR teleoperation, egocentric capture, exoskeleton-based) feeds Isaac Lab Mimic / DexMimicGen to scale a handful of demos into a full training dataset. IL or RL training, sim-to-real validation, deployment on the real robot. G1 and Digit shown here; the same pipeline runs on Franka, UR-class, custom humanoids — any embodiment.
End-to-end RL locomotion policy trained from scratch in Isaac Lab and zero-shot deployed on real Go2 hardware. Open reference project for our sim-to-real methodology.
Deformable wire physics with a custom contact character, manipulated by articulated arms in Isaac Sim. The same insertion family scales from thin cables to plug-and-connector assembly tasks — ported across UR-class and other industrial manipulators.
Massively parallel manipulation policies in Isaac Lab across the major industrial arms — UR5e, Franka Panda, KUKA, ABB and others. Reinforcement learning, imitation learning from teleop data, and sim-to-real validation on the same physical hardware.
Physically-grounded cloth simulation tuned for downstream perception and grasping policies — the same pipeline we apply to apparel, draping, and soft-goods manipulation.
Particle-level simulation of water, dust, debris and dynamic environmental conditions in Isaac Sim. The same approach extends to any phenomena that interact with perception sensors — RTX LiDAR, depth and RGB cameras — for robust outdoor and harsh-environment training.
Conveyor, sorter and forklift simulation with synchronized actuators — the building blocks for virtual commissioning of warehouses, packaging lines, and material-handling fleets before hardware is touched.
The digital-twin sample for this engagement is a real client facility. We hold it under NDA and don't publish it. Happy to share it under a mutual non-disclosure on a discovery call.
A live digital-twin sample of a real client facility — geometry, materials, and sensor placement modelled to enable virtual walk-throughs, layout iteration, and operator training before deployment.
Physical AI starts with the asset. Most teams hit a wall here: CAD that won't import cleanly, joints that scramble, contact dynamics that lie, and no off-the-shelf model that looks like the part they need to train on. We forge the missing piece — OpenUSD-native, physics-validated, articulation-ready — and then run the data layer on top: VR / egocentric teleoperation, MimicGen-class data multiplication, and end-to-end policy training. Same standard the leading SimReady catalogs ship to Google DeepMind, Figure and AgiBot — delivered as a custom engagement, sized to your robot.
Every asset ships as OpenUSD with the SimReady metadata you'd expect from NVIDIA's catalog and Lightwheel's library — physics class, materials, kinematic joints, semantics. Dual export to MJCF for MuJoCo. Drops cleanly into Isaac Sim, Isaac Lab, Newton, Genesis and any OpenUSD-based pipeline.
Mass, inertia tensors and centre-of-mass measured from the source CAD or hand-validated for parts where the CAD lies. Friction and damping tuned against real data. Convex decomposition with clean collision meshes — no self-intersections, no penetration, no surprise contact forces in training.
Joint hierarchy reconstructed from URDF / MJCF / STEP, drive types (position/velocity/effort) chosen per joint, gains tuned so the asset moves like the real thing under PhysX or Newton — not like a default-friction prop.
VR teleoperation (Apple Vision Pro, Meta Quest), egocentric capture, Space Mouse and exoskeleton-based collection. Then Isaac Lab Mimic / DexMimicGen scale a handful of demos into a full training dataset — the same 100–1000× multiplication pattern the SimReady ecosystem ships into Isaac Lab.
URDF importers break. Joint hierarchies scramble. Physics properties vanish during CAD-to-USD conversion.
→ Sim-ready assets, 24–72h deliveryDefault friction coefficients, incorrect inertia tensors, and untuned contact dynamics produce policies that fail on real hardware.
→ Systematic physics calibrationVisual domain gaps, physics mismatches, and sensor noise models break trained policies when deployed to production.
→ Proven zero-shot methodologiesEvery Isaac Sim release breaks existing workflows. APIs change, extensions disappear, importers behave differently.
→ Automated migration & regression testingNaN crashes, exploding gradients, reward exploits. 10M+ samples wasted on dead-end policies.
→ Expert reward design & tuningDDS middleware mismatches, Python version conflicts, single-threaded bottlenecks, physics synchronization issues.
→ Production-grade ROS2 bridgesLiDAR returns that don't match real-world scans. Camera noise models that break perception. Missing environmental effects.
→ Physics-accurate sensor modelsPetabytes of simulation data. Different GPU classes for sim, training, and inference. Multi-node orchestration at scale.
→ Right-sized infrastructure designWe work at every layer — from raw CAD assets through foundation model deployment. No black boxes, no hand-offs between teams. Just specialists who ship.
A structured process that adapts to your urgency. The timeline below is a typical engagement — if you need it faster, we compress it. Tell us your deadline and we'll build the plan around it.
We understand your robot, your environment, your goals. Free 30-minute consultation to scope the engagement and identify quick wins.
We audit your current pipeline, identify bottlenecks, and deliver a detailed roadmap with effort estimates and prioritized recommendations. Faster if urgent.
Working proof-of-concept in your simulation environment. You see real results before committing to a full engagement. Compressible for tight deadlines.
Asset conversion, environment setup, policy training, integration testing. Regular check-ins, transparent progress, scope-adjusted timelines.
Sim-to-real validation on your hardware, documentation, team training, and ongoing support. You own everything — no vendor lock-in.
Need it sooner? Tell us your deadline on the discovery call. We scale our pace to your urgency — compressed timelines, parallel tracks, or a short focused sprint when the deadline demands it.
We partner with industry leaders, research labs, and startups building Physical AI. Some engagements are public, most are not — and we keep it that way. Alongside client work, we ship open reference projects that demonstrate our methodology end-to-end.
Simulation engineering for industrial infrastructure. Engagement details are confidential under NDA.
Production-grade digital twins, line simulations and weather/perception engagements for industrial and infrastructure clients. Kept confidential by design — available to discuss under mutual NDA.
Franka, UR, and humanoid platforms across industrial, research, and startup clients. Engagements kept confidential by design.
We will keep secrets inside the company itself. Whatever we work on with clients stays between us — we won't share it outside. Security is the main principle of every engagement. NDA-ready from day one.
Reduction in time spent on simulation pipeline issues after onboarding us
Typical asset conversion turnaround from broken CAD to validated USD
Average time saved per robot integration vs in-house pipeline development
Vendor lock-in — you own every artifact we deliver, with documentation
Robotic assembly, bin picking, quality inspection, virtual commissioning of production lines.
AMR fleet simulation, pick-and-place optimization, multi-robot coordination.
Outdoor autonomous systems, inspection robots, extreme-environment validation.
Surgical robot simulation, rehabilitation device training, medical device validation.
Autonomous navigation, sensor fusion testing, unmanned systems simulation.
Custom simulation environments, benchmark creation, reproducible experiments.
Book a free 30-minute discovery call. Tell us about your robot, your simulation challenges, and your timeline. We'll tell you exactly how we can help — and what it'll cost.