> ## Documentation Index > Fetch the complete documentation index at: https://routerdocs.hivenet.com/llms.txt > Use this file to discover all available pages before exploring further. # Why Hivenet Router > Understand when a self-hosted inference router is the right fit and what Hivenet Router adds between clients and model servers. Hivenet Router gives applications one stable inference endpoint while model servers, hardware, and capacity change behind it. You operate the routing layer yourself and decide which providers, models, and agents may serve each request. ## What it solves Without a router, every client must know where models run, which endpoint is healthy, and how to recover when capacity disappears. That logic quickly spreads across applications. Hivenet Router keeps it in one place. Use it to: * expose OpenAI-compatible and Anthropic-compatible request paths * route requests by model, capability, policy, and reported capacity * apply fallback chains when a preferred target is unavailable * enforce API-key, model, request, token, and occupancy limits * protect capacity with admission control before work reaches a backend * observe routing decisions, agent health, latency, and errors centrally ## When it fits Hivenet Router is a strong fit when you run your own inference servers, operate a mixed fleet, or need policy and observability that should not live in every client. It is also useful when clients need one endpoint while the serving topology changes independently. A direct connection may be simpler for a single static backend with one trusted client and no need for routing policy, shared quotas, or failover. ## Operational boundary The router coordinates requests; it does not replace the inference engines that execute them. Agents report model and hardware capacity, while routing policies decide which healthy targets are eligible. Admission control decides whether eligible capacity can accept more work. See how routers, agents, and inference engines work together. Compare Hivenet Router with hosted Hivenet inference and compute services. Learn how policies, candidates, and fallback behavior shape a request. Understand request limits and occupancy protection.