Decodable acquisition, managed semantic caching service, and different updates to Redis for AI strengthen Redis’ capabilities as a real-time context engine for agentic programs
Redis, the world’s quickest knowledge platform, introduced a significant enlargement of its AI technique at Redis Launched 2025.
In his keynote, Redis CEO Rowan Trollope introduced Redis’ intention to amass real-time knowledge platform Decodable, the general public preview of Redis’ new LangCache service, and a number of other different enhancements to Redis for AI that make it simpler for builders to construct brokers with dependable, persistent reminiscence. Collectively, these strikes speed up Redis’ evolution from the quickest in-memory knowledge retailer to a necessary infrastructure layer for AI, delivering the context and reminiscence that clever brokers rely on.
“As AI enters its subsequent section, the problem isn’t proving what language fashions can do; it’s giving them the context and reminiscence to behave with relevance and reliability,” mentioned Rowan Trollope, CEO of Redis. “As know-how turns into ever extra reliant on LLMs, the strategic funding we’re making in Decodable’s platform will make it simpler for builders to construct and increase knowledge pipelines and convert that knowledge into context inside Redis, so it’s quick and all the time out there in the suitable place on the proper time.”
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Based by knowledge infrastructure veteran Eric Sammer, Decodable is a serverless platform that simplifies real-time knowledge ingestion, transformation, and supply. Its know-how replaces weeks of customized pipeline engineering with a declarative service that scales robotically.
“Becoming a member of Redis permits us to take Decodable’s imaginative and prescient additional and get there sooner,” mentioned Eric Sammer, founder and CEO of Decodable. “Collectively, we may give builders a seamless technique to join and act on their knowledge in actual time—unlocking AI programs which can be extra succesful, responsive, and deeply embedded within the workflows they serve.”
Redis additionally introduced the general public preview of LangCache, a fully-managed semantic caching service which cuts the latency and token utilization for LLM-dependent purposes by as a lot as 70%, and introduced a number of updates to its AI infrastructure instruments, together with hybrid search enhancements, integrations with agent frameworks for AutoGen and Cognee.
LangCache public preview
LangCache is Redis’ fully-managed semantic caching answer that shops and retrieves semantically related calls to LLMs for chatbots and brokers, saving roundtrip latency and drastically chopping token utilization.
The efficiency and value enhancements are substantial:
- As much as 70% discount in LLM API prices, particularly in high-traffic purposes
- 15x sooner response occasions for cache hits in comparison with reside LLM inference
- Improved end-user expertise with decrease latency and extra constant outputs
LangCache is in public preview at present.
New agent integrations and agent reminiscence
It’s now simpler to make use of Redis with present AI frameworks and instruments. Our ecosystem integrations let builders retailer their knowledge the best way they need, with no need to write down customized code. New integrations with AutoGen, Cognee, plus new enhancements with LangGraph increase how builders can use Redis’ scalable, persistent reminiscence layer for brokers and chatbots.
Construct with:
- AutoGen as a framework whereas getting the fast-data reminiscence layer of Redis and construct with present templates
- Cognee to simplify reminiscence administration with built-in summarization, planning, and reasoning utilizing Redis as your spine
- LangGraph with new enhancements to enhance your persistent reminiscence and make your AI brokers extra dependable
Different Redis for AI enhancements
With the speedy emergence of AI brokers, Redis is making certain that its customers have the flexibility to construct high-quality brokers utilizing Redis for AI. Redis integrations with fashionable AI agent frameworks allow customers to construct brokers sooner and with extra reliability. Key agent-focused capabilities embrace:
- Hybrid search enhancements. Redis now contains Reciprocal Rank Fusion, a way to unify textual content and vector rankings right into a single, extra related consequence set.
- Quantization. Redis now helps int8 quantized embeddings. Compress float vectors to eight‑bit integers for a smaller reminiscence footprint and sooner search efficiency for 75% reminiscence financial savings and 30% sooner search speeds in massive‑scale AI purposes
Redis Cloud and Redis Open Supply updates
Redis additionally introduced a number of updates to Redis Cloud and Redis Open Supply, together with:
- Redis 8.2 GA. Bringing an enormous leap in efficiency with 35% sooner instructions versus Redis 8.0, 37% smaller reminiscence footprint, and enhancements to Redis Question Engine, together with 18 knowledge constructions together with vector units, and 480+ instructions like hash discipline expiration.
- Redis Information Integration (RDI) public preview on Cloud. Preserve Redis caches contemporary and in-sync with supply databases utilizing easy-to-setup, zero-code knowledge pipelines. Velocity up legacy knowledge to grow to be actual time in minutes.
- Redis Perception out there on Cloud. Act on Redis knowledge straight from a browser. Visualize and minimize debugging time from hours to minutes, with out having to open a terminal and context change, to maintain on high of Redis efficiency.
Redis is the world’s quickest knowledge platform. From its open supply origins in 2011 to turning into the #1 cited model for caching options, Redis has helped greater than 10,000 prospects construct, scale, and deploy the apps our world runs on. With multi-cloud and on-prem databases for caching, vector search, and extra, Redis helps digital companies set a brand new commonplace for app pace.
Positioned in San Francisco, Austin, London, and Tel Aviv, Redis is internationally acknowledged because the chief in constructing quick apps quick.
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