AI Gateway Built for AI Agents at Scale

An AI agent gateway is an infrastructure layer that sits between agentic applications and multiple AI model providers. It gives agents one stable API for model access while handling routing, failover, logging, guardrails, and cost controls. For multi-step agents, this reduces brittle provider dependencies and makes every tool call, reasoning step, and model response easier to monitor and govern.

An AI API gateway is a unified entry point for accessing AI models and services through one consistent API. Instead of integrating separately with OpenAI, Anthropic, Google Gemini, xAI, and others, teams connect once and let the gateway manage provider routing, authentication, monitoring, usage limits, failover, billing visibility, and policy enforcement across applications.

AI agents use APIs to call language models, retrieve data, invoke tools, update systems, and complete multi-step workflows. An agent may call an LLM for planning, use another API for search or database access, then call a model again to summarize results. A gateway keeps these repeated AI calls reliable, observable, and controlled.

FastRouter supports agent scale by aggregating access to 100+ models through one OpenAI-compatible endpoint, then applying intelligent routing, automatic fallback, and governance at the gateway. This matters because agents often generate many rapid sequential calls. Centralized routing helps maintain throughput, reduce latency, and prevent a single provider outage from breaking agent loops.

Yes. FastRouter is designed to drop into existing OpenAI SDK-based code by changing the base URL to the FastRouter endpoint. This lets teams keep familiar development patterns while gaining multi-provider model access, routing policies, failover, observability, and governance without rewriting every agent framework or provider integration.

For agents, failover prevents provider outages, rate-limit errors, and model failures from interrupting multi-step workflows. FastRouter can reroute failed requests to fallback models or providers automatically, using centrally configured policies. This keeps autonomous processes moving and reduces the chance that a temporary provider issue causes failed user sessions or incomplete jobs.

FastRouter provides cost controls through project-level and API-key-level limits, role-based access, usage analytics, and routing strategies that can favor cost-efficient models when appropriate. This is especially important for agents because runaway loops or high-volume workloads can generate unexpected spend. Gateway-level controls apply consistently across applications without custom code in each agent.

FastRouter observability captures request details across models and providers, including usage, latency, cost, errors, and model outcomes. For agentic applications, these logs help engineers trace multi-turn runs, identify failing steps, compare model behavior, and debug quality issues. A unified dashboard is easier than stitching together separate provider logs after incidents occur.