The AI Gateway: Scaling Centralized Inference Across Decentralized Teams

This presentation by Meryem Arik, CEO of Doubleword, addresses the challenges and solutions involved in managing AI inference in enterprise environments.

• Introduction:

  Meryem Arik discusses the necessity of centralizing inference processes due to the chaos emerging from multiple AI inference providers used by decentralized teams.

• Objective:

  The talk aims to demonstrate the importance of AI gateways as a single control point for inference that enables decentralized teams to innovate efficiently.

• Main Topics Covered:
  • Inference Demands: Understanding the diverse requirements of teams that build various applications, emphasizing the need for different models to suit different cases.
  • Centralization Benefits: Centralizing inference is recommended to optimize GPU utilization, monitor reliability, and smooth load balances. It is especially crucial for organizations with self-hosted models to prevent infrastructure inefficiency.
  • AI Model Gateways: Meryem argues for AI model gateways as a means to manage decentralized model usage, reduce chaos, and control costs through features like budget management and rate limits.
• Real-World Application:

  The presentation includes a before-and-after use case from a financial services firm, illustrating the practical impact of implementing AI model gateways.

• Conclusion:

  AI model gateways offer a streamlined approach for managing inference in a decentralized environment, blending governance and agility.

The session concludes with a Q&A segment, allowing participants to explore these concepts further and discuss AI and inference questions in general.

This is the end of the AI-generated content.

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.