In depth
An AI gateway is a centralized service that brokers traffic between AI clients (chatbots, agents, IDEs, copilots) and AI services (LLM providers, MCP servers, internal AI tools). It is the AI-era equivalent of an API gateway, but adapted to the unique demands of AI workloads: large variable-size payloads, streaming responses, tool calls, multi-step agent workflows and the need for identity-aware policy on every interaction. By centralizing this layer, organizations replace dozens of direct provider integrations with one governed entry point.
Why it matters
Without an AI gateway, every application calls AI providers directly using shared API keys. Credentials sprawl across services, there is no central audit trail, and security teams cannot enforce identity-based policies on what data leaves the organization or what tools an agent can call. An AI gateway solves all three: it terminates identity at the edge, enforces policy on every request, and produces a single audit log across providers.
Common use cases
- Routing inference requests across multiple LLM providers from a single API
- Enforcing per-user or per-team token and cost limits
- Logging every prompt and response for compliance and audit
- Applying content filtering and prompt injection defenses uniformly
- Replacing direct API keys with short-lived, identity-bound tokens
How Ferentin handles it
Ferentin is the trust layer for AI agents. The platform centralizes identity, policy enforcement and audit across LLMs, MCP servers and AI tools. AI Gateway is one of the primitives this trust layer is designed around. See the platform overview for how it fits into the service edge, control plane and observability plane.