"Bring reality into every stage of robot development"
US startup that turns text, photos and CAD into SimReady 3D assets and scenes for robot simulation in Isaac Sim, MuJoCo and Newton.
Palatial Platforms Inc., operating as Palatial, is a United States software startup that automates the creation of simulation-ready 3D assets and environments for robot development. Its platform turns text descriptions, photographs of real objects and CAD or mesh files into assets that can be loaded directly into robot simulators, so that robotics teams can build training and test environments without hand-modelling every object. The company's tagline is Bring reality into every stage of robot development.
Palatial did not start in robotics. According to an interview with co-founder and CEO Steven Ren, who trained in architecture and worked in visualisation, real-time rendering and VR, the company began as a cloud platform that turned architects' CAD files into browser-based interactive visualisations and then built an Unreal Engine plugin that scanned 3D scenes for inefficiencies and applied optimisation fixes. It later moved to large-scale, high-fidelity simulation environments for training robots, with simulation-ready asset generation as its first robotics product. The company was earlier known by the domain palatialxr.com, which now redirects to palatial.cloud.
Assets produced by Palatial are described as SimReady, with precise geometry, physics-friendly meshes, physically based rendering materials, mass, friction and inertia properties, and articulated joints. The documentation describes Text to Sim, Image to Sim and CAD to Sim workflows; the Palatial Agent, which turns instructions and reference material into a configured asset build; editing, reprocessing and variant generation for comparing alternate versions of an asset; a viewer for inspecting an asset's pipeline, physics, validation results and exports; and organisation and public asset libraries. The company says more than 1,000 free assets are available in its library. Export packages target the Isaac Sim, MuJoCo and Newton simulators.
The website groups its tools into real-to-sim functions, including asset generation, scene generation and real2sim playback intended to make simulation results match what happens on a real floor, and sim-to-real functions that generate variants of assets and scene conditions and create scenarios that are hard to reproduce physically, for training robust robot policies. Access is provided through a web dashboard, an Isaac Sim plugin that generates or imports Palatial assets into an Isaac Sim stage, a REST API, and integrations that let developers generate and manage assets from coding agents such as OpenAI Codex CLI and Claude Code.
Palatial lists NVIDIA, Humanoid Robotics, Origami Robotics, Genesis AI, Industrial Next, Amazon, Gritt Robotics and Innate among its partners and customers, and shows the NVIDIA Inception Program, Early Stage Quant Fund and Newlab on its site. VCBacked records a 1.5 million US dollar angel round in July 2024 from the AngelList Early Stage Quant Fund and lists the company's headquarters in Brooklyn, New York. For the RobotToday landscape it sits in the data, teleoperation and simulation segment as a provider of simulation content for robot learning.
Primary type & automation activities this supplier delivers:
Web platform and agent that generate SimReady robot-simulation assets with physics properties and articulated joints from text, photos or CAD files.
Plugin that generates or imports Palatial assets directly into an NVIDIA Isaac Sim stage.
Library of 1,000+ free SimReady assets with PBR materials, mass, friction and inertia data for Isaac Sim, MuJoCo and Newton.
REST API plus Codex CLI and Claude Code integration to create, monitor, reprocess and download simulation assets programmatically.
Contact Palatial Platforms Inc.
WEBSITE
https://palatial.cloudHEADQUARTERS
United States
Company Facts
Founded
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Primary Role
Software/Algorithm
Company Size
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Primary Region
North America
Annual Sales
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Funding Stage
Early-Stage VC
Funding Total
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