We are happy to power one of the most successful and popular development platforms. LangChain's OpenGPT, for #GenAI with #redis vector capabilities. You'll be surprised how simple, fast, accurate, secured and cost-effective GenAI applications can be with LangChain’s OpenGPT &

TL;DR from my interview with AIM: 1. #Redis has been downloaded over 12 million times daily (up from 3.8 million). 2. #Redis Enterprise is used by more than 0.5 billion Indians (in the interview, half a million is written, but it is half a BILLION). 3. Country visitors to

#Redis Vector Library streamlines GenAI development with an efficient client interface & Redis Enterprise boosts performance with real-time vector database capabilities for vector search, LLM caching, & chat history management. @redisinc #GenerativeAI redis.com/blog/introduci…

After 11 incredible years as Redis’s CTO, I'm thrilled to step into the role of President. I'll remain deeply involved in shaping our strategy and executing our tech vision, while also engaging more with our customers and peers. Together with our customers, partners and our

It's been a big week for #redis (and Redis )! After yesterday's license change, we announced today the acquisition of #Speedb, the market's fastest storage engine. We're excited to welcome Speedb team! And here is how we see the future of #redis: redis.com/blog/the-futur…

As part of our efforts to keep #redis awesome, we made Lettuce, the wonderful Java client, an official family member. Thank you, Mark Paluch, for making Lettuce what it is now after 10 years of hard work! redis.com/blog/lettuce-j… Redis

In the #Intel Vision 2024 keynote, Pat Gelsinger (Intel's CEO) showed how RAG architecture should look with Gaudi 2 and #Redis, powered by vector search and semantic caching. The bottom line: much more accurate and relevant results @ x2.3 times faster. youtube.com/watch?v=QB7FoI…

Today, the bright minds of engineers and technologies prevailed. In democracies, they thrive 🇮🇱🇺🇸 המוחות המבריקים של המהנדסים והטכנולוגיות ניצחו היום. בדמוקרטיות הם משגשגים 🇮🇱🇺🇸

#redis (Redis ) and LangChain go beyond simple RAG : redis.io/blog/explore-t…

Semantic Kernel's Kernel Memory now uses #Redis! - another great and straightforward integration that helps LLM applications run faster. redis.io/blog/building-… (Redis)

One of the most requested features from the #redis community is now available as a release candidate - Hash Fields expiration. ( lnkd.in/eMpE9r_G ). Furthermore, we added new bfloat16 and float16 vector data types in #Redis Stack, reducing memory consumption while

Real-time #RAG apps need more than traditional vector DBs. #Redis offers: Vector search up to 50x faster (benchmarks soon) Semantic cache reducing LLM calls by 30% Advanced LLM memory for personalized and more accurate responses Designed for speed, scalability, accuracy, and

Check out our blog for impressive results: #Redis #vector search is up to x50 faster than general-purpose DBs and x15 faster when combining throughput & latency, than special purpose vector DBs and imitators . Essential for #GenAI apps!  redis.io/blog/announcin… Redis

#Redis 7.4 is out! 1. Hash Field Expiration (most requested feature ever!) 2. New vector data types: less memory, higher QPS, lower latency 3. Easier secondary indexing: no special TAG chars, empty field support, new geo search (intersect/disjoint) 4. Time series size reduction

#Redis is evolving to power the GenAI-based modern stack! 1. Caching ➔ Semantic Caching 2. Session Management ➔ LLM Session Management (Contextual Memory) 3. Classification ➔ Semantic Routing Redis #GenAI #ModernStack github.com/redis/redis-vl…

#Redis Cloud is now on #Vercel! Enjoy Redis at speed with the latest data structures, query engine, & full-text search. Plus, Vercel users can now harness Redis for AI: 1️⃣ Fastest vector search 2️⃣ Semantic Caching (save 30%+ on GenAI) 3️⃣ LLM Memory & personalization 4️⃣ Semantic

More amazing tech built on Redis. Paradigm makes data collection fast and easy at any scale. It uses an army of AI agents to collect data and organize it into spreadsheets in seconds, all using natural language prompts. Sign up and see more here: paradigmai.com/join

With Chain Of Thought reasoning (ala openAI o1-preview): intelligence now scales with inference compute Which will cause inference costs to rise significantly Which makes what we are doing at Redis with inference caching / semantic caching so critical to control your AI costs

Amazing!