GraphRAG Part 3 – Intelligent MVR, Query Routing and Context Generation

Part 3 explores three advanced capabilities that transformed query processing and context generation in the GraphRAG system. First, we introduced … More

GraphRAG Part 2 – Cross-Doc & Sub-graph Extraction, Multi-Vector Entity Representation

Part 2: A deep dive into implementation of cross-documents semantic relations extraction, multi-hop graph traversal queries, and multi-vector (entities, relations, … More

Building a GraphRAG System – Core Infrastructure & Document Ingestion

Part 1: A deep dive into multi-database architecture, AI-powered entity extraction, and intelligent document processing Introduction Traditional RAG systems rely … More

Beyond Vector Search: How GraphRAG Enables Smarter AI Responses

Imagine asking your AI assistant: “Who manages the person leading our AI research project?” A traditional RAG system would struggle … More

RAG at Scale: How Westlaw and LexisNexis Are Redefining Legal Research

Years ago, I had the opportunity to work with LexisNexis on building “LexisNexis™ Portal powered by Plumtree” – an enterprise … More

RAG at Scale: The Hidden Trade-Offs of Single Vector Embedding

Balancing performance and precision in enterprise search and data retrieval A common pattern for improving the quality of AI-assisted content … More

Why LLMs and Humans Think Differently: An Amateur Dive into AI’s Compression Problem

I recently read article “From Tokens to Thoughts: How LLMs and Humans Trade Compression for Meaning” by Yann LeCun and … More