Routing, chaining, and orchestrating multiple AI models
Multi-model orchestration is the practice of routing queries to different AI models based on cost, latency, capability, or task type. Tools like LiteLLM (unified API gateway), LangChain, LlamaIndex, and Haystack enable model routing, RAG pipelines, agent workflows, and cost optimization across dozens of providers.
Single OpenAI-compatible API for 100+ models — route between providers with automatic fallback and load balancing
Retrieval-Augmented Generation: embed your docs, index in a vector DB, and query with any LLM for factual answers
Automatically route to cheapest model that meets quality threshold — save 70%+ vs always using frontier models
Build multi-step AI agents with tool use, memory, and iterative reasoning using any supported LLM backend
Multi-Model Orchestration's API now features enhanced rate limiting and quota management for improved performance and stability.
Multi-Model Orchestration now supports advanced prompt templating for dynamic and reusable AI workflow components.
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$0
Open-source MIT license
$50+/mo
Hosted solution
Ingest, index, and query structured + unstructured data with 100+ data connectors and retrieval strategies
Automatic failover between providers with configurable retry strategies and provider health monitoring
The Multi-Model Orchestration API's batch processing endpoint has been updated to support asynchronous operations and offer enhanced control.
Custom
LangChain's observability platform