[Webinar] How to Protect Sensitive Data with CSFLE | Register Today
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.
As an attendee, you will:
P.S. Set up a meeting with Confluent after the webinar and build your own custom Nike shoes – while supplies last*.
*By invitation only. Limit one pair of shoes (up to $200) per company. This promotion is not sponsored, promoted, endorsed by, or associated with NIKE, Inc. All customers are subject to verification by Confluent. Promotional offer ends Oct. 12, 2023. Only available in the US and Canada. I agree that by signing up for this event, I am consenting to provide my registration information to Confluent and to the co-sponsor of the event. Confluent and the co-sponsor may send me emails about their products, services and/or events and will process my information in accordance with their privacy policy (see Confluent Privacy Policy and the event details for applicable privacy policies of our co-sponsor. Event Co-sponsor: Rockset (Rockset Privacy Policy)