SiMa.ai Announces Open-Source Palette Neat to Accelerate Physical AI Development
July 07, 2026
News
SiMa.ai announced its Palette Neat, an agentic development environment for Physical AI that produces application timelines from months to days. The platform is a purpose-built, open source, and has an integrated development environment that combines a Physical AI execution library and agent workflow layer for productivity-focused agentic development.
Combined with Modalix MLSoC SoM, or its new PCIe companion card form factor, the solution is ideal for Physical AI workloads across robotics, automotive, drones, industrial automation, aerospace and defense, smart vision, and healthcare.
“SiMa.ai is an AI software company that builds its own silicon,” said Krishna Rangasayee, founder and CEO of SiMa.ai. “Today, we are delivering the industry’s first agentic development environment for Physical AI. Together, Palette Neat and our pin-compatible SoM dismantle the incumbent GPU moat, allowing developers to design systems in plain English and develop them in days — and in many cases, hours.”
Benefits:
A New Development Paradigm:
- Use AI to deploy Physical AI with designers using natural language commands to build complete systems that enable users to focus on system-level differentiation for both new and legacy applications
From Months to Days or Hours:
- Agentic environment autonomously builds and maps applications directly to silicon
- Seamlessly reuse existing application code that preserves approximately 90 percent of legacy software investment
Frictionless Platform Migration:
- Palette Neat with the pin-compatible SoM and new PCIe companion card dismantles the incumbent GPU moat to scale Physical AI
Resources:
- Palette Neat Open Source: Access on GitHub.
- Palette Neat Documentation: Get started at the Developer Center.
- Modalix MLSoC SoM: Read the full hardware specification.
- Upcoming Webinar: Register for the June 30 event on “Scaling Physical AI.”
For more information, visit sima.ai.
Chad Cox is the Production Editor at Embedded Computing Design. His responsibilities are centered around content creation, writing and editing, and article research and development. Chad covers industry news and events and is known to interact with various industrial leaders via on-premise visits and online interviews. He is responsible for the digital footprint and dissemination of news via social media posts, advertising creation and the production of newsletters including the Embedded Computing Design’s Daily.
He is well versed in many facets of industrial computing including Edge AI, IoT, Processing, Security, Open Source, and more.
Chad graduated from the University of Cincinnati with a B.A. in Cultural and Analytical Literature and holds a master’s in education.
