Definition: Intermediary layer that manages, routes, and controls calls to AI model APIs, providing observability, caching, rate limiting, and failover across providers.
— Source: NERVICO, Product Development Consultancy
What is an AI Gateway
An AI Gateway is an intermediary layer that sits between applications and AI model providers (OpenAI, Anthropic, Google, open-source models). It functions similarly to a traditional API Gateway but is specialized for the specific needs of LLM-based applications: multi-provider management, semantic response caching, cost control, rate limiting, centralized logging, and automatic failover when a provider experiences issues.
How It Works
The AI Gateway intercepts all calls to AI model APIs before they reach the provider. For each request, it can apply routing policies (choosing the most suitable model based on cost, latency, or task type), caching (reusing responses for similar requests), format transformation (unifying the interface regardless of provider), access control (tokens, rate limits per user or team), and logging (recording each request with its cost, latency, and tokens consumed). Products like Portkey, LiteLLM, and Cloudflare AI Gateway are popular examples.
Why It Matters
As companies integrate multiple AI models into their products, directly managing each provider’s APIs becomes unsustainable. An AI Gateway centralizes control, reduces single-provider dependency (vendor lock-in), optimizes costs through caching and intelligent routing, and provides the observability needed to manage AI in production. Without it, teams lose visibility into the spending and performance of their AI systems.
Practical Example
A company uses Claude for customer support, GPT-4 for document analysis, and an open-source model for classification. With an AI Gateway, they manage all three providers from a single interface, implement caching that reduces API calls by 30%, configure automatic failover to alternative models, and get a unified cost dashboard that reveals 40% of spending comes from optimizable repetitive queries.
Related Terms
- AI Observability - AI system monitoring that the gateway facilitates
- LLM - Language models whose APIs the gateway manages
- Guardrails - Safety mechanisms that can be integrated into the gateway
Last updated: February 2026 Category: Artificial Intelligence Related to: API Management, AI Observability, LLM Routing, Model Orchestration Keywords: ai gateway, api management, llm routing, model orchestration, caching, rate limiting, failover, portkey, litellm