The AI Gateway: Scaling Centralized Inference Across Decentralized Teams

As enterprises adopt AI, one tension has become clear: inference needs to be centralized for efficiency, governance, and reliability, while use cases and model development are necessarily decentralized across teams. Without the right architecture, this leads to fragmented deployments, rising costs, and governance blind spots.

A pattern that has become more common is the use of AI Gateways, an evolution of the API gateway. In this talk, we’ll explore the AI Gateway pattern - an architectural approach that provides a single control point for inference while enabling decentralized teams to innovate at speed.

We’ll cover the trade-offs and best practices while working through a real life before/after use case of a Financial services firm. This talk will leave the audience with practical tips, and will point towards relevant open source technologies to explore to unlock scale, reduce duplication, and deliver both governance and agility.