Deliver Better Product Recommendations with Real-Time AI & Vector Search

Harnessing the power that lies within AI to deliver better product recommendations is becoming a vital strategy for businesses that want to improve customer engagement levels and drive sales. When fueled by real-time data streams, AI has the ability to analyze vast amounts of user data, discern patterns including product similarities, and instantaneously deliver personalized suggestions when consumers are actively engaged. With AI, you can help these consumers navigate today’s never-ending sea of choices and easily find exactly what they need.

Confluent and Rockset power a critical architecture for efficiently developing and scaling AI applications built on real-time streaming data. During this demo webinar, you’ll see an ecommerce company’s real-world product listing embeddings, produced by OpenAI, that capture the underlying meaning of unstructured data like text, audio, images, and videos in a format more easily leveraged by computational models. You’ll see how they’re streamed in real time by Confluent Cloud to Rockset’s vector search database, which returns recommendations in milliseconds.

Watch now to:

  • See firsthand how you can start using and getting business benefits out of predictive AI-powered use cases built with cloud services Confluent and Rockset
  • Learn how to fuel AI algorithms with high-value data streams using Confluent Cloud, a cloud-native data streaming platform built by the original creators of Apache Kafka®
  • See product recommendations created by Rockset, a real-time search and analytics database capable of low-latency, high-concurrency queries on streaming data


Patrick Druley is a Solution Engineer at Rockset
Julie Mills is a Director of Product Marketing at Rockset
Zachary Hamilton is a Senior Solutions Engineer at Confluent
Greg Murphy is a Product Marketing Manager at Confluent

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