RunLocal AI
The first AI agent for optimizing ML model inference on edge hardware
What they do
Engineering teams struggle to debug and optimize ML model inference performance on edge hardware, requiring brittle scripts and manual experimentation.
An AI-native platform with an AI agent that automates on-device performance debugging, optimization, and experiment tracking for ML inference on edge devices.
Engineers and ML teams at companies building autonomous vehicles, robotics, drones, and smart camera systems deploying models on edge hardware.
Founders
Co-Founder & CEO of RunLocal AI Building the first AI agent for optimizing ML model inference on edge hardware (like Nvidia Orin and Qualcomm) → www.runlocal.ai Previously worked on the first edge AI video codec at Deep Render and AR/VR apps at Meta.
CTO of Neuralize. Previously a software engineer at Marshall Wace (Europe's largest hedge fund) building an internal AI platform for developers and optimizing low latency streaming systems.
Company timeline
- Founded2024
- YC batchSummer 2024
- StatusActive
- Team size3 people
- LocationLondon, England, United Kingdom
