Multi-provider routing and fallback: how it works and when to use it
Multi-provider routing and fallback, load-balances and fails over across providers on error class, with retries using exponential backoff and jitter. Here's how Crowkis does it and why it matters for cost and safety.
Production LLM traffic is deeply repetitive, and repetition is exactly what a bill is made of. Multi-provider routing and fallback is how Crowkis load-balances and fails over across providers on error class, with retries using exponential backoff and jitter.
How it works
Crowkis load-balances and fails over across providers on error class, with retries using exponential backoff and jitter. It runs inside one Redis-compatible engine, so it composes with semantic caching, agent memory, and the other intelligence layers instead of being a separate service you wire together.
Why it matters
Repetitive LLM workloads are where the money is, and semantic caching can cut costs up to 60-70% on repetitive workloads. Multi-provider routing and fallback is part of what makes that reuse safe rather than reckless, the difference between a cache you trust in production and one you audit after every incident. It's one self-hosted binary, Redis-compatible, free to run.
Infrastructure earns the critical path one boring, verifiable feature at a time.