Inferagate
AI Gateway & Traffic Control

One stable gateway in front of every model provider.

Centralize access to OpenAI, Claude, Gemini, Bedrock, Azure OpenAI, vLLM, Ollama, and private LLMs through one governed API layer.

What it solves

Stop wiring every application directly to every provider.

Inferagate gives teams a single OpenAI-compatible endpoint while operators decide which provider, model, route, fallback, and workspace policy should serve each request.

  • Unified AI gateway for managed APIs and private runtimes.
  • OpenAI-compatible API layer for existing AI apps.
  • Provider abstraction so apps can move without code changes.
Routing logic

Smart routing based on production signals.

Route prompts dynamically between on-prem models, private GPU runtimes, and cloud providers.

  • Model availability, cost, latency, workspace policy, and allowed provider rules.
  • Primary, fallback, and restricted model roles.
  • Multi-provider failover for outages, timeouts, rate limits, and model failures.
Console areaProviders, Models, Routes
Primary usersPlatform, engineering, app teams
OutcomeOne approved route per use case
Step by step

Connect providers, then route traffic through the gateway.

Open providers
Inferagate provider registry and readiness screen
  1. 01
    Add the provider lane

    Open Providers, choose the upstream type, give it a stable lane name, and attach credentials.

  2. 02
    Validate readiness

    Run validation so the console confirms health, adapter type, auth posture, and model discovery.

  3. 03
    Register served models

    Move to Models, select discovered models, and keep only the approved production candidates.

  4. 04
    Create the route

    Use Routes to choose the primary model, fallback behavior, timeout, and production rollout path.