Make Your Enterprise Data LLM-Ready With Unstructured.io and AstraDB
Join DataStax and Unstructured.io where we’ll show you how to convert just about any document into LLM-ready data and create data pipelines of embeddings for a vector database and similarity searches.
Data preparation is a notorious time sink for anyone building a RAG (retrieval augmented generation) or generative AI app.
Why? Enterprise data can come in a huge variety of difficult-to-use plaintext, image, and document types, including HTML, PDF, CSV, PNG, PPTX, and more.
How can you make this fast and easy? Join DataStax and Unstructured.io where we’ll show you how to convert just about any document into LLM-ready data and create data pipelines of embeddings for a vector database and similarity searches.
In this 45-minute session we will show you how to:
- Make complex PDFs, HTML, CSVs, PPTX data ready for any LLMs
- Chunk and embed the data into vectors Astra DB
- Use your data in a simple chatbot using the Vercel AI SDK and Next.js
To wrap up, we’ll host a live Q&A where you can ask technical questions. Can't make it live? Register anyway and we'll share the replay!