RunLocal: Solving the Last Mile Problem in AI Deployment

While tech giants battle over the next breakthrough in AI models, a critical challenge lurks beneath the surface: getting AI to work effectively on the devices we use every day. That’s where RunLocal comes in, on a mission to make on-device AI development accessible and efficient.

The challenge of deploying AI models on diverse devices – from phones to laptops – has become a significant hurdle for engineering teams. What works flawlessly in the lab often falls apart in the real world, where different hardware specifications and operating systems create a maze of compatibility issues. RunLocal is solving this by providing a comprehensive platform that allows teams to test, optimize, and confidently deploy AI models across a wide range of devices.

Founded by Ismail Salim, Ivan Chan and Ciaran O’Rourke, RunLocal emerged from their firsthand experience with the limitations of existing on-device AI tooling. The founders’ background, including Ivan’s work on Marshall Wace’s internal server-side AI platform, and Ismail/Ciaran’s early insight into the challenges of on-device AI development while working together on the first AI video codec at Deep Render, gave them unique insights into the gap between server-side and on-device AI development.

The platform’s approach is refreshingly practical. Instead of forcing developers to maintain their own device testing infrastructure, RunLocal provides a streamlined solution that can reduce model conversion and optimization time from weeks to days. This isn’t just about speed – it’s about giving engineers the confidence that their AI models will perform consistently across different hardware and operating systems.

What particularly caught our attention was RunLocal’s focus on real-world performance metrics. The platform enables teams to spot performance issues early, iterate faster, and ensure a consistent experience across devices.

The timing couldn’t be better. As AI continues to move from centralized servers to edge devices, the need for robust deployment solutions becomes increasingly critical. RunLocal is positioning itself at the intersection of two powerful trends: the democratization of AI and the shift toward edge computing. Their platform isn’t just solving today’s challenges – it’s building the infrastructure for tomorrow’s AI-powered applications.

The early results are promising. One customer, Skylum, reported decreasing the size of an embedding model by a factor of 10 in just a few days while maintaining accuracy. These kinds of outcomes demonstrate the platform’s potential to fundamentally change how teams approach on-device AI development.

At Ritual Capital, we believe the next wave of AI innovation will be defined not just by model capabilities, but by how effectively these models can be deployed and optimized for real-world use. RunLocal is building the essential infrastructure to make this possible, and we’re thrilled to be part of their journey.

Visit RunLocal at https://runlocal.ai.