Meet Redis LangCache: A Managed Semantic Cache That Cuts LLM API Costs by Up to 90% and Returns Cache Hits Up to 15x Faster
Production LLM applications rarely receive a question nobody has asked before. Support assistants and RAG pipelines field the same intents thousands of times a day, each phrased differently, and most stacks treat every phrasing as a fresh, fully billed request. Redis LangCache is a fully managed semantic caching service that sits between the application and the model, matches incoming prompts against previously answered ones by meaning rather than exact text, and returns the stored response whe
Redis LangCache is a semantic caching service that sits between an application and a language model to avoid redundant API calls when users ask similar questions phrased differently. Instead of treating paraphrases as new requests that require full model processing, LangCache generates an embedding of incoming prompts and searches for semantically similar previously-answered questions in its cache, returning stored responses when matches are close enough. When a cached response is returned, users avoid paying for input and output tokens and receive responses up to 15x faster than re-querying the model, with reported cost savings up to 90% depending on cache hit rates and traffic patterns. The service requires careful configuration of similarity thresholds and expiration policies to prevent incorrect matches, and it is currently available as a public preview on Redis Cloud through a REST API.
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