Marginal vs Wattfare

Track every LLM call's cost and slice it by customer, feature, model, any field you define.

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

About Marginal

Track every LLM call's cost and slice it by customer, feature, model, any field you define. Marginal tracks the cost of every LLM call and slices it by the fields you care about, customer, feature, model. Cost is computed server-side, usage in, dollars out. Every API request is logged with its outcome, accepted counts, rejected events and why, stripped keys, unpriced models. The SDKs are zero-dependency, buffered, fire-and-forget: track() never throws and never blocks your request path.

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.