SiMa.ai, a leader in Physical AI, today launched Palette Neat, the industry's first agentic development environment for Physical AI that collapses complex application timelines from months to days. The open source, purpose-built, integrated development environment combines a Physical AI execution library and agent workflow layer for productivity-focused agentic development. When paired with the full-production Modalix MLSoC System-on-Module (SoM) or its new PCIe companion card form factor, the unified platform delivers unmatched performance-per-watt for high-demand 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."

Palette Neat uses a natural-language interface and innovative agentic workflow to abstract away low-level compute complexity, eliminating the months of labor traditionally spent on porting and integrating applications to new silicon.

Key advantages of Palette Neat include:

• A New Development Paradigm: Use AI to deploy Physical AI. Developers use natural language commands to build entire systems, enabling engineering teams to focus strictly on system-level differentiation for both new and legacy applications.
• From Months to Days or Hours: The agentic environment autonomously builds and maps applications directly to silicon, shrinking development cycles to a fraction of the timeline. Developers can seamlessly reuse existing application code, preserving approximately 90% of their legacy software investment.
• Frictionless Platform Migration: Palette Neat, alongside the pin-compatible SoM and new PCIe companion card, dismantles the incumbent GPU moat to scale Physical AI while reducing cost, time, and engineering risk of switching hardware platforms.

The full-production Modalix SoM runs multiple Large Language Models (LLMs) concurrently alongside vision and sensor models—all under 10 W and purpose-built from the silicon up for Physical AI deployment. Designed as a pin-compatible drop-in replacement for the incumbent NVIDIA SoM form factor, it requires no carrier board redesign. Together, Palette Neat and Modalix SoM eliminate the engineering friction of adopting new AI hardware, requiring developers to integrate a completely new architecture or rewrite their entire software stack.

Access Palette Neat Open Source on GitHub. Read the full hardware specifications here.