NewsNTech
The distribution bottleneck in AI application development sits above the model APIs.
Every deployment that draws on multiple foundation models must resolve which model to call for a given request, at what cost, with what fallback behavior when one provider is slow or unavailable, and against which pricing structure.
Developers building AI-powered products face the overhead of maintaining separate API integrations, credentials, and billing relationships for each model provider they want to access.
The infrastructure layer that abstracts that routing and aggregation problem has become its own market, separate from the model providers it connects.
Keep reading