Musa Molla

When we started building GraphBit, we kept running into the same problem: most AI frameworks looked great in demos but collapsed in production. Crashes, lost context, concurrency issues- all things developers shouldn’t have to fight just to ship real agent workflows. That’s why we built GraphBit on a Rust execution core for raw speed and resilience, wrapped in Python for accessibility. The goal: give developers the best of both worlds, high-performance orchestration with a language they already love. We’ve also been using it across multiple internal projects with great results. What excites me most isn’t just the benchmarks and performance (though 14x faster and zero crashes still makes me smile 😅), but how GraphBit is already being used: - Teams running multi-LLM workflows without bottlenecks - Agents handling high-concurrency systems that used to break other frameworks - Enterprise users valuing observability, retries, timeouts, and guards baked in from day one We’re also proud to say our architecture is patent-pending, because we believe the way agents execute should be as reliable as any enterprise system. This is just the start. We’d love for you to try GraphBit, break it, push it and tell us what to improve. Your feedback will shape where we take it next. — Musa Founder, GraphBit

As a developer-first company, Python was the obvious choice for our API layer. It gives engineers the flexibility and ecosystem they need while keeping integrations effortless.

Rust powers our core because speed and safety aren’t optional at scale. Its concurrency model and memory guarantees let us push agentic AI into true production environments.