Requesty: The Intelligent AI Model Router
Maximize reliability and performance with automatic failover and load balancing across 500+ LLM models. Never go offline. Always get an answer.
Automatic Failover Policies
Ensure 99.9% uptime for your AI applications. When one model fails (timeout, error, rate limit), Requesty automatically routes to your backup models in millisecondsâno manual intervention required.
How It Works
Your primary model gets the request.
If it fails (timeout, error, etc.), the router immediately tries the next model.
This continues until one model delivers the results you need.
Why Fallback Routing Matters
99.9% Uptime
Eliminate single points of failure. If OpenAI goes down, instantly switch to Anthropic, Google, or AWS Bedrock
Handle Rate Limits
Automatically route overflow traffic to alternative models when you hit provider rate limits
Cost Optimization
Start with cheaper models, fall back to premium ones only when needed
Frequently Asked Questions
What is a fallback policy and how does it work?
A fallback policy is an automatic re-routing mechanism. When your primary model fails (timeout, error, rate limit), Requesty immediately routes the request to the next model in your chain. This continues until a model successfully responds. You only pay for the successful request.
How does load balancing maintain conversation consistency?
Requesty maintains routing consistency per trace_id. This means the same user or conversation always hits the same model, ensuring coherent multi-turn interactions. Configure your distribution (e.g., 50% Model A, 30% Model B, 20% Model C) and each trace_id is consistently routed based on those weights.
Can I use fallback policies for A/B testing?
Yes. Combine fallback policies with load balancing for A/B testing. Route 90% to your production model and 10% to an experimental model, then measure quality, latency, and cost in parallel. If the experimental model fails, it automatically falls back to your production model.
What happens if all models in my fallback chain fail?
If all models in your fallback chain fail, Requesty returns an error response with details about each attempt. You can configure the maximum number of retry attempts and timeout thresholds per model in your policy settings.
How does latency-based routing determine which model is fastest?
Requesty tracks P50, P90, and P99 latency across all models in real-time. Based on actual observed performance (not marketing claims), the system recommends the fastest models for your specific workload and automatically shifts traffic to lower-latency options.
Can I combine fallback, load balancing, and regional routing?
Yes. You can create policies that combine multiple routing strategies. For example: load balance between EU-only models (regional routing) with automatic fallback to secondary EU models if primary fails. This gives you geographic compliance with maximum reliability.
How do I ensure model compatibility in my fallback chain?
Make sure each model in your fallback chain supports the same parameters (temperature, max_tokens, response_format, etc.). Requesty validates compatibility when you create policies and warns you if models don't match your request parameters.
Does auto-caching work with fallback policies?
Yes. You can control caching behavior per request with the auto_cache flag. Set auto_cache: true to cache responses, or auto_cache: false to always fetch fresh responses. Caching works across your entire fallback chain, potentially serving cached responses from any model in the chain.
How quickly does failover happen?
Failover happens in milliseconds. When a model fails (timeout, error, or rate limit), Requesty immediately routes to the next model in your chainâno manual intervention required. This ensures 99.9% uptime for your AI applications.
Can I route based on request complexity?
Yes. Use load balancing to route simple queries to fast, cheap models (GPT-3.5, Gemini Flash) and complex queries to premium models (GPT-4, Claude Sonnet). You can also implement custom routing logic based on prompt length, user tier, or any metadata you send.