Redis LangCache
A semantic cache for LLM calls: before an app calls its model, LangCache embeds the prompt, looks for a semantically similar prompt already answered and returns the stored response, with configurable similarity thresholds, TTLs and eviction, through a REST API.
Find alternatives to Redis LangCache
What it does
- Vector search
Features 5
- Fully managed semantic cachingReturns a cached response when a similar response has already been made, via REST API.
- REST APIManaged service accessible via REST API from any language with no database management.
- Embedding model selectionUse default models or bring your own vector tool for embeddings.
- Adaptive controlsAuto-optimize settings for precision and recall.
- Cache management controlsControl data access, privacy and eviction protocols.
Sources
- Pricing
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No LangCache rate is published: the page offers "Try it for free" and "Talk to sales", and redis.io/pricing/ does not name it. The docs say private-preview participation "is free" with usage limits; that covers the preview, not a standing free tier.
- Description
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Official documentation · 10 Oct 2026
"LangCache checks whether a semantically similar prompt has been answered before and returns the cached response instantly: no LLM call required." It generates embeddings itself and lets the user configure "similarity thresholds, TTLs, and eviction policies".
- What it does
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Official documentation · 10 Oct 2026
LangCache "calls an embedding model service to generate an embedding for the prompt" and matches it against stored embeddings.
- Sold within
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"Iris is composed of five tools", LangCache among them; on Redis Cloud a LangCache service is created for an existing Redis Cloud database. No page read says whether it is billed separately or included. Read: the LangCache page and docs, the Iris docs and redis.io/pricing/.
- Name
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Official documentation · 10 Oct 2026
Redis LangCache: "Save 90% on API costs and shorten response times with intelligent, Redis-based semantic caching for AI."
- URL
- Deployment
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Official documentation · 10 Oct 2026
Managed on Redis Cloud, or self-managed on Kubernetes with a licence key from Redis.
Also from Redis
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Redis Search API service
Vector search and hybrid (vector + exact-match) query engine built into Redis, marketed as "the world's fastest vector database" for GenAI apps and RAG pipelines at billions-of-vectors scale.
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Redis Iris Infrastructure service
Redis's context engine for AI agents, bundling Context Retriever, Agent Memory, LangCache, Data Integration and Redis Search into one runtime that keeps agents supplied with live business data, memory and cached answers, managed on Redis Cloud or self-managed on Kubernetes.
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Redis Agent Memory API service
A memory service for AI agents that keeps each conversation as ordered session events with automatic summarisation, extracts durable facts into long-term memory in the background, and retrieves them across sessions by semantic, keyword or hybrid search.
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Redis Context Retriever API service
A schema-first context layer that turns a modelled set of business entities, fields and relationships into generated retrieval tools agents call over MCP, so agents read live operational data through governed, row-filtered lookups rather than writing SQL.
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Redis Copilot Developer tool
An AI assistant in Redis Insight and the Redis docs that answers questions about Redis commands and concepts and, connected to a user's own database, turns plain-language requests into Redis search queries over that data.
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