
AI gateway solutions serve as intelligent middleware deployed between custom-built enterprise applications and the underlying large language models (LLM) and artificial intelligence (AI) agents they rely on. Rather than coding application programming interface (API) keys and logic for specific providers directly into applications, development teams can route all model requests through the AI gateway. This centralized control plane standardizes API interactions and handles the heavy lifting of enterprise AI infrastructure.
AI gateways provide development teams with unified controls for multi-LLM routing, automatic failover, semantic caching, token-based rate limiting, and exact cost tracking. By abstracting the underlying AI models from application logic, AI gateways ensure high availability, optimize inference costs, and enforce strict API governance. This also prevents "shadow AI": the use of unauthorized models and unmonitored API keys hidden within application code.
Many existing API management platforms have extended their functionality to include AI gateway solutions. AI gateways are also closely related to LLMOps platforms, which handle the broader end-to-end lifecycle of building, fine-tuning, and evaluating models. However, while LLMOps focuses heavily on model development, AI gateways focus strictly on runtime API consumption and governance.
Additionally, buyers looking to secure employee web interactions with public AI chatbots rather than developer-driven application traffic should explore the AI security posture management (AI-SPM) category.
To qualify for inclusion in the AI Gateways category, a product must:
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