Late last year, Redis and Microsoft announced Azure Managed Redis (public preview) , a fully-managed, scalable, in-memory data store that gives Azure developers everything they need to b...

In today’s API economy, milliseconds matter. See how Redis Cloud takes Apigee from great to exceptional. APIs are the backbone of modern apps. Google Cloud’s Apigee gives teams the tool...

See how Redis and Arhasi make CCAI faster, smarter, and more cost effective Google’s Contact Center AI (CCAI) has transformed how businesses engage with their customers. It uses convers...

Redis Cloud, the most powerful, scalable managed Redis service, just tripled your productivity, writing fast apps faster. As devs, having the right tools at your fingertips while buildin...

Today, we announced two new offerings for AI developers to help them build better apps. Redis LangCache, a new fully-managed semantic caching service for AI apps and agents, provides a h...

Redis is excited to announce the introduction of vector sets, a groundbreaking data type designed for vector similarity. Inspired by the core principles of Redis and developed by the ori...

Welcome to “What’s new in two,” your quick hit of Redis releases you might have missed in the past month. We’re covering the latest developments from March and expanding on what I covere...

Colab Notebook on Github Retrieval-augmented generation (RAG) is often overhyped, leading to unmet expectations after implementation. While it may seem straightforward—combining a vecto...

Today, we’re excited to introduce langgraph-checkpoint-redis, a new integration bringing Redis’ powerful memory capabilities to LangGraph. This collaboration gives developers the tools t...

Why Redis stands out for GenAI & vector search GenAI is more powerful than ever, but most apps still feel slow. Users expect instant responses, but latency and inefficiencies get in the...

As more and more companies get GenAI apps into production, we’re seeing increasing requests from customers for larger vector databases. We see use cases for a billion or more vectors and...

Full Colab NoteBook on Github. Evaluating information retrieval (IR) systems is essential for informed design decisions and understanding system performance. Successful companies like A...

Welcome to “What’s new in two,” your quick hit of Redis releases you might have missed in the past month. We’re covering the latest developments from February and expanding on what I cov...

Full Notebook on GitHub. Modified Notebook on GitHub. To build an effective question-answering system like RAG for finance, you need a model that understands the industry’s vocabulary....

We’re happy to announce the integration of Mem0 with Redis, a powerful combination that enhances the capabilities of AI agents by providing efficient and scalable memory management. Mem0...

When users sit down to watch a movie on Netflix, they face a problem untold numbers of Netflix users have faced before: What to watch next? Luckily, the fact that so many users face this...

We’re happy to announce the third milestone of Redis 8.0, our most advanced and performant offering yet. As we progress toward the general availability (GA) release, we’re committed to ...

Unless you’ve been off the grid the past two years, you’ve likely come across the term “vector database” in conversations about GenAI. I joined Redis in 2022, pre-ChatGPT, when vectors ...

Semantic caching is changing how we optimize systems reliant on large language models (LLMs). By using vector embeddings, it enables faster, cost-effective responses for similar queries....

You know that mix of excitement and uncertainty when you’re starting something new? That’s exactly how I felt when I set out to build a Retrieval Augmented Generation (RAG) pipeline usin...

You know that mix of excitement and uncertainty when you’re starting something new? That’s exactly how I felt when I set out to build a Retrieval Augmented Generation (RAG) pipeline usin...