Redis
@Redisinc

See how fast feels

redis.io
Joined January 2014
6,278 Photos and videos
Context. That's the difference between an AI demo and a reliable production agent. The fix? Bringing fragmented context into one place, then adding meaning so an intelligent system can actually use it: redis.io/resources/state-of-…
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Redis retweeted
LangChain
@LangChain
Sep 18
.@redisinc is sponsoring Interrupt NYC! Stop by their booth during the event and go hands-on with their data platform, built for caching, AI, and real-time apps.
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Full breakdown in The state of context engineering report: redis.io/resources/state-of-…
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Your agents should be getting smarter. Build them on fresh data and context that improve over time with Redis Iris: redis.io/iris/
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We've launched a plugin that brings Redis engineering guidance into ChatGPT Work and Codex. Agents building on Redis now get skill-specific instructions loaded only when the work calls for it. 🧵
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more replies
Skills cover data structures, connection pooling, vector search, semantic caching with LangCache, clustering, security, and Redis Agent Memory.
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Install Redis Development through the plugin browser in ChatGPT Work or Codex, or run ‘npx skills add redis/agent-skills’ for other supported agents. Read more: redis.io/blog/put-redis-data…

Put Redis data and engineering guidance to work in ChatGPT Work | Redis

Developers love Redis. Unlock the full potential of the Redis database with Redis Enterprise and start building blazing fast apps.

redis.io
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Redis retweeted
Databricks
@databricks
Sep 14
A recommendation is useless if the user has already clicked away. ⏱️ That's why Databricks and @Redisinc have partnered to deliver in-session personalization by combining Databricks Real-Time Mode (RTM) for continuous processing with Redis for sub-millisecond serving, without managing a separate streaming engine. Explore the joint architecture, performance benchmarks, and code snippets: redis.io/blog/delivering-rea…
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Two systems, one job: continuous compute and instant serving. @Databricks Real-Time Mode computes state as events happen. Redis serves it in sub-millisecond time. Full pattern and code walkthrough here: redis.io/blog/delivering-rea…
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Your agent forgets everything between sessions, retrieval slows down as your data grows, state goes stale, and the LLM bill keeps climbing. Sound familiar?🧵
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Join our 5-part AI tech talk series and fix this, one 15-minute session at a time, building a context-aware app on Redis Iris: redis.io/resources/webinar-s…

AI tech talk series: Agent context layer | Redis

Developers love Redis. Unlock the full potential of the Redis database with Redis Enterprise and start building blazing fast apps.

redis.io
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Vector search is one piece of a production RAG system. Most standalone vector databases only solve that piece. Semantic caching and agent memory usually end up bolted on separately, often meaning Redis gets added anyway. 🧵
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Redis Iris consolidates all three. See how consolidation compares to a standalone vector database: redis.io/en/blog/vector-data…

Top vector database alternatives for RAG pipelines

Compare purpose-built vector databases, relational extensions, search engines, and in-memory platforms for RAG. See how Redis unifies vector search, caching, and agent memory.

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Redis Iris gives a ReAct loop a fast, consolidated context layer instead of three separate systems for memory, retrieval, and caching. ReAct agents reason, act, and observe in a loop. Simple to build, but every tool call re-sends the growing history, and costs stack up fast. 🧵
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See what it takes to run ReAct agents without the cost catching up: redis.io/blog/react-agents-e…

ReAct Agents Explained: Concepts & Practical Uses

Learn how ReAct agents work, how the reasoning-acting loop runs in production, and what it takes to keep these loops fast and cost-effective at scale.

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The response to Redis certifications has been 🔥 Haven't started yet? Don't worry, you can still get 50% off your first certification with code Earlyaccess50. Start your journey here: redis.io/certifications
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Add a filter to a vector search, and results can get worse, not better. It sounds backwards, but a tight filter can make the search skip right past items that would've matched, with nothing to flag it. 🧵
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Redis Search checks filters and similarity in the same step, so this doesn't sneak past you. See what else breaks as vector search scales: redis.io/blog/vector-search-…
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97% of enterprise leaders say context is critical to AI strategy, but only 4% have built for it. Memory resets. Retrieval lags. State goes stale before your agent reads it. And bills nobody budgeted for. Redis Iris fixes the layer underneath the model. 🧵
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Join our 5-part series and build a context-aware app in 15-min sessions: redis.io/resources/webinar-s…

AI tech talk series: Agent context layer | Redis

Developers love Redis. Unlock the full potential of the Redis database with Redis Enterprise and start building blazing fast apps.

redis.io
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