Multi-Provider Architecture
Build resilient AI applications using multiple providers with intelligent routing and fallbacks
Relying on one model/provider is a single point of failure. Multi-provider architecture lets you: • Fail over during outages • Route based on cost/latency • Use specialized models for specific tasks • Avoid sudden deprecations breaking production Synqly helps you keep the integration stable while your routing evolves.
Architecture Overview
A multi-provider setup typically includes: • A unified gateway (Synqly) • Multiple LLM providers (OpenAI, Anthropic, etc.) • Routing logic • Fallback strategies • Cost and performance controls
Routing Strategies
Common routing strategies include: • Cost-based routing (cheapest model first) • Latency-based routing • Capability-based routing (reasoning vs fast models) • Region-aware routing
Fallback Handling
Fallbacks ensure reliability when providers fail: • Automatic retry on 5xx errors • Provider switching on rate limits • Graceful degradation for users
Best Practices
Best practices: • Always define a fallback provider • Log provider failures explicitly • Avoid provider-specific prompt coupling • Regularly test fallback paths
A Simple Routing Rule
A practical starter approach: • Default route: cheapest safe model • If request is "high importance" → route to best reasoning model • If provider fails (5xx/timeout) → fallback provider Keep it simple first. Optimize only after you have usage data.