Hydra, a local vs Wattfare

Route to a target confidence of correctness, not just the cheapest model. Hydra samples models adaptively (SPRT), cuts AI API costs 70-85% along the way, and keeps...

Users connect, set a spending cap, and you call any model through one SDK, charged to them, not you.

About Hydra, a local

Route to a target confidence of correctness, not just the cheapest model. Hydra samples models adaptively (SPRT), cuts AI API costs 70-85% along the way, and keeps sensitive data local. Hydra rides the cost/quality Pareto frontier, stops sampling the instant confidence clears the bar, and reads the code graph to know when a change is dangerous. A hub file with many transitive dependents is cascade-capable, so it demands more confidence. Every access an agent makes is recorded in a local, hash-chained ledger.

About Wattfare

Users connect, set a spending cap, and you call any model through one SDK, charged to them, not you. OpenAI-compatible Works with the Vercel AI SDK ~5-min integration. One button connects a user's inference budget to your app, metered, capped, and revocable. The problem AI costs are the one line item you can't predict. Every AI app makes the same uncomfortable bet: price high enough to survive your power users, ration usage so nobody hurts you, or quietly lose money on the heavy ones.