With the rise of AI and large language models (LLMs), organizations are increasingly leveraging these technologies to enhance their applications and deliver innovative customer experiences. However, integrating AI models into existing systems and ensuring responsible adoption presents significant challenges, including data security, governance and multi-model management.

The AI Gateway Pattern has emerged as a solution to address these challenges, acting as a centralized entry point for integrating AI services into existing applications and systems. In the context of DevOps, this pattern can streamline the adoption of AI while providing critical governance and control mechanisms.

In this session, we’ll cover how organizations can centralize AI traffic through the AI Gateway by:

• Establishing a unified control plane to manage, secure and observe AI traffic across the organization.
• Supporting multiple AI backends including OpenAI, Anthropic and LLaMA.
• Implementing prompt validation, data filtering and security overlays.
• Centralizing logging and monitoring of AI traffic, enabling anomaly detection, usage analysis and cost optimization.
• Offering AI as a core platform service, allowing development teams to rapidly integrate AI capabilities.

We’ll demo these concepts using an OSS AI Gateway solution.