We believe billing infrastructure should never be the reason a great AI product fails to ship.
Every AI company eventually hits the same wall — they've built a great product, but monetising it means building a metering system, a credit wallet, an invoicing engine, and data exports from scratch. That's months of engineering time that should be spent on the product itself.
Credit deductions happen synchronously with sub-50ms latency. Your customers always see an accurate balance. We handle retries, idempotency, and failover so you don't have to.
Every credit movement is recorded in an immutable ledger. Every API call is logged. Your finance team, your customers, and your auditors can always see exactly what happened and when.
A great developer experience is non-negotiable. Clean REST APIs, OpenAPI documentation, sensible defaults, and a dashboard that gets out of your way — so you can integrate in minutes.
MetricaOS was born from a recurring frustration. While building AI-powered SaaS products, we kept running into the same problem: usage-based billing for AI APIs is genuinely hard. Token counts vary by model, costs differ between providers, customers need real-time balance visibility, and finance needs accurate invoice data — all at the same time.
Off-the-shelf billing tools weren't designed for the token economy. They assumed fixed seats or simple tiers. We spent weeks building custom metering pipelines that were fragile, hard to audit, and impossible to scale. Then we'd talk to other teams and hear the exact same story.
So we built MetricaOS — an opinionated, production-grade platform for AI usage metering. It handles the event pipeline, the credit engine, the subscription lifecycle, and the data exports, so engineering teams can focus on what makes their product unique.
Today MetricaOS powers billing infrastructure for AI teams across industries — from developer tools to healthcare AI to enterprise assistants. We're just getting started.