Spring Silicon
Spring Silicon builds a full-stack compute platform for physical AI, spanning custom ASIC hardware, compilers, kernels, and operating systems designed specifically for edge inference in robots, drones, and autonomous vehicles. The company co-optimizes every layer from frontier model research to silicon to deliver real-time performance and power efficiency that generic consumer or datacenter chips cannot achieve.
- Semiconductor
- Artificial Intelligence
- Robotics
- Autonomous Vehicles
- Drones & Uncrewed Systems
- Hardware
- Automotive Technology
- Industrial Automation
Funding
Funding not disclosed
Founders
Founder details are not available yet.
Product
Problem
Robots, drones, autonomous vehicles, and heavy industrial systems lack compute hardware tailored to their real-time, physical constraints. Existing solutions are either scaled-down datacenter systems or repurposed consumer chips, which fail to deliver the performance, latency, and power efficiency required for reliable edge inference in dynamic environments.
Solution
Spring Silicon is building a full-stack compute platform specifically for physical AI, spanning compilers, software, and custom ASIC hardware. The company designs its infrastructure from the ground up for edge inference, ensuring every layer—from low-level kernels to silicon—is co-optimized for the demands of autonomous machines. This vertical integration allows workloads to run more efficiently than generic alternatives, with software and hardware engineered together to maximize real-world performance. The company works across the entire stack, from frontier model research to compilers, kernels, operating systems, firmware, and silicon, ensuring tight coupling between algorithm development and underlying hardware. The result is a purpose-built stack that powers next-generation machine autonomy across robotics, drone, and vehicle platforms.
Target Audience
Primary customers are companies developing autonomous robots, drones, and vehicles, along with heavy-industry operators requiring dedicated edge-inference compute for intelligent machine decision-making.
Features
- Custom ASIC design tailored for edge inference workloads in physical AI
- Full software stack including compilers, embedded systems, and operating-system kernels
- Co-optimized hardware and software architecture developed in-house across the entire compute stack
- Frontier model research integrated with low-level system design to align model requirements with hardware capabilities
- Focus on real-time performance and power efficiency for autonomous machines rather than repurposed consumer or datacenter parts