With the rise and widespread use of generic generative AI models, their presence is becoming ubiquitous. Using an out-of-the-box model is not enough to stand out or deliver unique results. Your only advantage over competitors is your data. Whether it's Gen AI, Machine Learning, Business Intelligence, or simple data visualization, the results are only as good as your data.

Data is continuously generated with varying degrees of importance, urgency, and freshness. This data needs to be collected, processed, analyzed, and fed into your AI system to deliver valuable insights and provide timely and accurate responses.

The challenge is to design a scalable, reliable, secure, and cost-effective data processing architecture that minimizes complexity and meets these constraints.

In this session, attendees will learn how to architect highly scalable and cost-effective data processing pipelines that power AI systems. We'll explore real-world use cases and best practices for orchestrating serverless workflows that seamlessly handle diverse data streams to empower custom, fine-tuned AI models.