Building the Intelligent Data Layer for AI: Architecting Scalable GenAI Apps

Artificial Intelligence thrives on data — and a modern, resilient database architecture is the foundation of every successful AI application. As GenAI applications are inherently cloud-native, ensuring resilience, scalability, and real-time performance is critical to prevent downtime and deliver seamless user experiences.

In this webinar, explore how to design cloud-native database architectures that meet the evolving demands of AI and GenAI workloads while maintaining transparency, simplicity, and operational excellence. Discover the essentials of vector databases — specifically, how the fast storage, indexing, and retrieval of vector data enables powerful similarity search, machine learning tasks, and smarter AI interactions.

Register now to experience firsthand how YugabyteDB, the leading distributed SQL database, provides the ideal foundation for AI-driven applications by combining advanced pgvector integration with horizontal scalability, continuous availability, and transactional consistency.

Through a live demo, we’ll implement a Retrieval-Augmented Generation (RAG) pipeline that processes and retrieves knowledge from unstructured documents using the Unstructured library, PGVector, and LLMs like GPT.

Whether you're modernizing your data layer or building GenAI applications from scratch, this session will arm you with best practices, real-world strategies, and future-proof architecture patterns.