NVIDIA Blueprint: Enterprise RAG

NVIDIA's AI Blueprint for RAG is a foundational guide for developers to build powerful data extraction and retrieval pipelines. It leverages NVIDIA NeMo Retriever models to create scalable and customizable RAG (Retrieval-Augmented Generation) applications.

This blueprint allows you to connect large language models (LLMs) to a wide range of enterprise data, including text, tables, charts, and infographics within millions of PDFs. The result is context-aware responses that can unlock valuable insights.

By using this blueprint, you can achieve 15x faster multimodal PDF data extraction and reduce incorrect answers by 50%. This boost in performance and accuracy helps enterprises drive productivity and get actionable insights from their data.

• Creating and managing document collections through an intuitive UI
• Uploading and processing multimodal PDF documents containing text, tables, and charts
• Interacting with an AI chatbot capable of interpreting and answering questions about complex data
• Understanding how the RAG pipeline processes and retrieves information
• Exploring observability features through Zipkin traces
• Learning about the available SDK capabilities for custom integrations

What you will interact with:

• NVIDIA Enterprise RAG Blueprint
• NVIDIA NIM microservices

Under the covers, you will be running on:

• AI Proving Ground's GPUaaS
• AI Proving Ground's LLMaaS