Structuring Unstructured Data for GenAI & LLM Apps

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Multimodal systems blend videos, images, code, text and more. The goal is to return relevant documents - not just text - to user prompts. The next step is to analyze and summarize these documents for better categorization and data augmentation: leveraging not just the surrounding context, but also what's inside these files. The benefits are obvious. In this presentation, the focus is on PDF, PPT and CSV files, to automatically and efficiently extract structure, integrate with standard AI tasks, and deliver enhanced results.

Overview

Join our upcoming webinar to learn about the complexities of handling unstructured data, and practical strategies for converting data in a variety of native formats into standardized format usable for GenAI applications.

We will go over data ingestion from multiple sources, preprocessing unstructured data into a normalized format, metadata extraction, and more. You’ll also learn how to load preprocessed data into SingleStore DB.

You’ll learn:

• Challenges of preprocessing unstructured data
• Building ETL pipelines for unstructured data
• What’s under the hood of Unstructured.io
• Demo: data ingestion, preprocessing and loading into SingleStore

Hands-on workshop for developers and AI professionals, featuring state-of-the-art technology, case studies, code-share, and live demos. Recording and GitHub material will be available to registrants who cannot attend the free 60-min session.

Register here.