Search is more than simply finding documents. Now, we expect search solutions to provide the answers and to make recommendations. In this webinar, we’ll show you how your organization can use Redis beyond traditional caching use cases. We’ll help you deploy it as a real-time search and recommendation engine.
Search capability is ingrained into our daily life. How many arguments these days are settled with the conclusion, “Just Google it”??! We all expect some type of search functionality in every application and website. Meanwhile, advances in computer vision, natural language processing, large language models, and generative AI have made it possible to extract semantic properties from unstructured data in the form of vector embeddings.
It can be daunting to query this kind of data, which combines K-Nearest Neighbors algorithms and lexical search, unless you have the right tool for the job. When you fail, performance suffers. Web users typically expect search results under one second.
And that’s where we come in. Redis, as an in-memory data platform, is strongly positioned to provide the real-time processing capabilities necessary for this use case. Though its heritage is primarily enterprise caching, the RediSearch module enables querying, secondary indexing, and vector search.
Join us for an interactive session with the Redis Applied AI Engineering team to learn how to build real-time search and recommendation engines for your business.
After the technical session, we will treat you to a tea experience. You will learn about tea from a sommelier, including a bit of history, the best preparation methods, and how to appreciate this great beverage’s place in the global context.
Agenda
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Event Speakers
