Meet Redis LangCache: A Managed Semantic Cache That Cuts LLM API Costs by Up to 90% and Returns Cache Hits Up to 15x Faster
Redis launches LangCache, a managed semantic cache matching LLM prompts by meaning, cutting API costs up to 90% and returning hits up to 15x faster.
Redis LangCache is a fully managed semantic caching service in public preview on Redis Cloud, accessed via a REST API with Python and JavaScript SDKs. It embeds incoming prompts, vector-searches stored entries, and returns a cached response when similarity clears a configured threshold, skipping the LLM call entirely. Redis claims up to 90% cost savings and up to 15x faster cache hits; a demo run showed 0.37 seconds versus 2.232 seconds direct inference (about 6x) with zero LLM tokens. Customer Mangoes.ai reports a 70% hit rate, 70% lower LLM spend, and 4x faster responses on a patient-care voice app.
- Semantic cache matches prompts by meaning, eliminating the full LLM call on hits
- Public preview on Redis Cloud via REST API with Python and JavaScript SDKs
- Redis claims up to 90% cost savings and 15x faster cache-hit responses
- Savings estimate: monthly output token cost multiplied by cache hit rate
- Safe production use requires tuned thresholds, TTLs, tenant isolation, and false-match monitoring
From the original article
4 min read at marktechpost.com
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 […]
By Michal Sutter · marktechpost.com
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