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Online Talk

How to Build GenAI apps Faster with Confluent’s Connectors

Visionner

Available On-demand



Generative AI is rapidly changing how we interact with technology, but its effectiveness hinges on access to contextual, trustworthy, up-to-date data. Most modern enterprises will find building and deploying GenAI applications challenging, as data is often locked in siloed, heterogeneous data stores. If your team is grappling with batch-based processing and data silos that bottleneck your AI initiatives, it's time to explore a more efficient approach.

In this upcoming demo webinar, you'll learn how to:

  • Build a real-time knowledge base for RAG architecture on a data streaming platform
  • Leverage Flink SQL for vector embedding, transforming data into AI-ready formats directly within your data pipeline
  • Configure and launch a fully managed sink connector to continuously hydrate MongoDB Atlas Vector Search

Confluent offers an ecosystem of 120+ pre-built connectors built by Kafka experts to seamlessly unlock access to your enterprise data and accelerate GenAI app development. Our connector portfolio enables you to quickly and efficiently integrate a diverse range of data systems with a data streaming platform to continuously update your vector database of choice for real-time RAG implementations.

Don't let data silos and integration challenges hold back your Gen AI initiatives. Register now to learn how Confluent's connector portfolio can accelerate your path to building cutting-edge, contextual GenAI applications.

Mac KhajuriaSenior Product Marketing Manager, Confluent

Mac is a senior product marketing manager at Confluent responsible for go-to-market for Kafka connectors. Prior to Confluent, he led a team of solution architects at Google designing marketing infrastructure for retail customers.

Erick LeeSenior Product Manager, Confluent

Erick Lee is a Product Manager at Confluent focused on Connect. Prior to product management, he worked as a Solutions Engineer partnering with Digital Native customers on building out their data streaming platforms. He started his career at Oracle within the analytics and data warehouse space. Outside of work you'll often time find him rock climbing and enjoying the outdoors.