Agentic RAG

The 2025 Progress Data Platform Summit in Washington, D.C. covered AI, data integration and responsible governance. Read about what you may have missed.

A knowledge graph is a set of interconnected data. Exploring a knowledge graph and finding new connections across your data can be an exciting experience.

In today’s information-rich world, tapping into the most valuable knowledge within an organization can still be a challenge. It’s locked in the images of a product catalog, scattered across a multi-page table in a financial report, or split between diagrams and charts in a dense research paper. Standard extraction tools or basic RAG pipelines can only get you so far, often missing the nuance and context that’s critical for your business.

Retrieval Augmented Generation (RAG) has emerged as a powerful paradigm for grounding Large Language Models (LLMs) in factual, relevant information. However, the true power of RAG hinges on a critical element: sufficient context.