What is an AI Gateway? Key Benefits and Examples
Companies are building AI into their products quickly, but problems appear fast at scale. LLM traffic is less predictable than traditional API traffic. It brings new challenges such as token-based costs, sensitive data leaking through model responses, and prompt injection attacks. These issues are often beyond what application developers can handle on their own. This whitepaper introduces the AI gateway, a middleware layer that sits between applications and AI services to secure, govern, and manage every model interaction from one control point. It explains how AI gateways differ from traditional API gateways, how they work in practice, and the security, cost, and business benefits they offer. It also covers advanced capabilities that help enterprises scale AI with confidence.
Key topics covered
- What an AI gateway is and the challenges it solves for LLM-based applications
- How AI gateways differ from traditional API gateways
- How an AI gateway sits between GenAI applications and LLM providers in practice
- Security and compliance benefits, including access control, AI guardrails, and PII scrubbing
- Cost management through token-based rate limiting and usage monitoring
- Business value across risk management, governance, and faster AI adoption
- Advanced capabilities such as semantic caching, prompt management, and multi-model routing
- Common questions on multi-LLM adoption, deployment risks, and getting started
Author
Derric Gilling
Vice President & General Manager - API Platform BU, WSO2
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