Stripe charges per transaction. Twilio charges per message and per minute. OpenAI charges per token. Three companies, three completely different units of value, three pricing models built around what actually costs them money or reflects what the customer gets. Picking a monetization model for an API isn’t a marketing decision bolted on at the end — it shapes how the API gets designed in the first place.

Pay-per-call

The simplest model: charge a flat fee for every request, sometimes with volume discounts at higher tiers. Google Maps and most geocoding APIs work this way. It’s easy for a customer to understand and easy for a provider to bill, since usage tracking is just a request counter.

An API can pass every unit test in its suite and still break every client that calls it, because unit tests check that functions do what the code says they do, not that the API does what the contract says it does. That gap is where most production API incidents actually come from: a field renamed, a status code changed from 200 to 204, a required parameter quietly made optional. Testing an API well means testing at several different levels, because each one catches a different class of failure.

Ask two developers in 2026 what platform they use to design an API, and you will get two answers that have almost nothing in common. One of them means the tool where they write the OpenAPI document, lint it, mock it and publish the reference docs. The other means the layer that sits between their application and a dozen model providers, routing requests to whichever LLM is cheapest or still up. Both groups call it “API design.” Both groups are right, because the two stacks have quietly grown into each other.

Orkes, the workflow and agent orchestration platform founded by the original engineers behind Netflix’s microservices infrastructure, has closed a $60 million Series B round led by AVP, with participation from Prosperity7 Ventures, Nexus Venture Partners, Battery Ventures, and Vertex Ventures US. The raise signals growing enterprise demand for orchestration infrastructure that can take AI workloads from prototype to production without falling apart.

The company’s foundation is Conductor, an open-source orchestration engine originated at Netflix in 2016 and still actively maintained by Orkes. Netflix’s own internal usage of Conductor has grown fivefold in recent months, and the project counts developers at JP Morgan Chase, Tesla, Atlassian, Oracle, American Express, and GE Healthcare among its users. Since its $20 million Series A in 2024, Orkes has tripled its paying customer base and built a developer community in the hundreds of thousands.