Physically accurate assets and scenes for robot simulation training at scale
San Francisco, CA
Joined April 2022
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So how does Mad Max compare against Astra? We put them head to head with identical prompts and inputs.
Mad Max came out ahead in the following areas:
-Geometric accuracy (proportions, scale)
-Subtle geometry details (normal maps)
-Cleaner Topology
-More detailed PBR materials
-Fully functional mechanical joints
Want to compare yourself? Mad Max is free to try for the next week at dashboard.palatial.cloud (4/4)
Bring your reference materials and context, Mad Max reasons about the task, does research and synthesizes messy input data into faithful recreations of real world objects across use cases and industries.
Each asset is validated against its target simulator, ensuring stability, working joints and photoreal materials. (3/4)
Simulation has an N+1 problem. In order to create accurate simulations, there are hundreds of engineering problems to solve and solving one doesn't always lead to solutions for the millions of other scenarios out there. This engineering gap is the primary reason sim is not ubiquitous in robotics today.
By combining frontier models like GPT-6 Astra and our own simulation-in-the-loop verification engine, we’ve created general solutions to many long-standing issues in asset generation, including open ended articulation, using an approach that scales with frontier progress. (2/4)
Introducing Palatial Mad Max, a state-of-the-art parametric generation agent that unlocks scalable Real2Sim for robotics and physical AI.
It's a generalized agent that can create extremely detailed SimReady assets with precise articulated parts and grounded physics properties designed for dexterous manipulation tasks.
Try it now at dashboard.palatial.cloud (1/4)
Check out some of the cool things folks have already built with the MCP!
My latest kitchen helper has six legs and wings 🪰
Inspired by Google’s fruit-fly brain work, I built a miniature kitchen with @PalatialSim's new MCP in less than an hour, then came roughly 18 hours of training, tuning and testing in MuJoCo to get the fly interacting with it.
MCP docs: docs.palatial.cloud/integrat…
Plugin docs:
docs.palatial.cloud/plugins-…
Most of the teams we work with live in two places: the simulator and the terminal. This week, we're shipping Palatial into both.
Download the @nvidia Isaac Sim plugin to generate new or import existing sim-ready assets directly in the stage. Or, use the MCP and ask your coding agent to call Palatial to create complete simulation packages for Isaac Sim, MuJoCo, or Newton.
try it out here: palatial.cloud/isaac-sim-plu…
Our talk at @siggraph 2026: Building SimReady 3D Worlds for Physical AI, is now live.
We cover what sim-ready actually means, common pitfalls, and the key challenges we solved to automate asset generation at the scale needed for robotics development.
Check it out if you missed it and thanks to the @nvidia team for inviting us!
At @siggraph 2026 we announced the world’s first SimReady asset agent and today we’re making it publicly available in open beta.
You can now generate and iterate on assets through natural language. Just upload your reference data, tell us your use case and the agent will figure out the best settings.
Try it out now @ dashboard.palatial.cloud
This kicks off shiptember. We've got a full month of releases lined up!
Palatial was just featured in @BusinessInsider's inaugural list of the 25 most promising robotics startups of 2026, alongside pioneering firms like @SkildAI, @GeneralistAI, @fieldai_, @UnitreeRobotics, and @foxglove.
Physical AI raised $16.3B in Q1 alone, and simulation is the layer that will unlock scale for all of it. Thanks @hlynakim for the nomination!
Tune in later this week to see what the team has been cooking up!