One governed path for every model, tool, agent
Most enterprises reach AI through a tangle of direct model calls, duplicated tool integrations, and siloed agents, with no shared policy, no cost visibility, and no observability. AI Gateway replaces sprawl with one governed path between every AI consumer and everything it reaches.
AI Gateway sits between AI consumers (apps, copilots, agents, and employees) and everything they reach: models, tools, MCP servers, and enterprise systems. Every request is governed: policy-driven and configured not coded, enforced at runtime, and tenant-aware, with one deployment supporting many governed boundaries.
Every AI request enters through a single governed entry point.
Every capability is a toggle on a shared control plane, so you turn on only what you need.
Guardrails, PII controls, evaluations and grounding run inside the request path, not after the fact.
An API gateway governs HTTP. It does not understand a prompt, a token, a model route, a tool call or an agent trajectory. AI Gateway governs those AI-runtime decisions: model access, token budgets, prompt controls, evaluations and cost attribution.
LiteLLM is strong for model proxy, routing, budgets and fallback. AI Gateway governs models, MCP tools, agents, prompts, tenants, safety and quality from one plane: the AI-specific layer above your model proxy.
No. It is model-agnostic and cloud-aware by design, with swappable open-source components behind stable published APIs, so you adopt best-fit models and switch freely.
No. Capabilities are modular and opt-in. Most enterprises start with two, usually model routing and guardrails, and enable the rest as configuration.
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