We turned our hackathon project into an open-source framework for AI optimisation

Every team was spending hours tuning temperature, model, and token settings or just sticking with defaults.
We asked ourselves: what if optimisation could optimise itself?

That hackathon project ended up winning the Reinforcement Learning Track at Weavehacks-2 (W&B + Google Cloud).

Now it’s grown into The Convergence: an open-source framework that automates API optimisation using evolutionary algorithms, multi-armed bandits, and reinforcement learning.

It learns what works, remembers across runs, and balances cost, quality, and latency automatically for AI performance.

We open-sourced it because every AI team faces this problem, and the infrastructure for continuous, transparent optimisation should be shared.

If you’re tired of guess-and-check prompt tuning, come explore how we’re making AI systems self-improving by design.

🏆 Devpost: https://devpost.com/software/the-convergence#updates
💻 GitHub: https://github.com/persist-os/the-convergence