Vineet Vinod
Co-founder
Local AI should feel private, fast, and practical
Trillim makes fully local AI viable for real work, not just demos, with a focus on speed, privacy and easy setup
Founders
Ryan Baker
Co-founder
Problem
Local AI still breaks too easily
Getting local AI running is still harder than it should be. Even if you know your way around the stack, installs are fragile, setup varies across machines, and small mistakes can turn into hours of debugging before real work even starts.
Trillim
Built from the engine outward
Trillim starts with an inference engine built from the ground up to be fast and efficient, then wraps it in a workflow that is simple to install, easy to run, and easy to build on top of. The goal is one command to get moving, not a weekend of setup.
Future
Private automation on-device
The roadmap is broader model support, smarter models, and agentic workflow support for automations that live on your devices. That keeps the useful parts of AI close to you while protecting privacy.
Logo Design
Thanks to Mia Shafer for designing the logo.
