Session
Beyond RAG: Why Enterprise AI Needs a Correlation Graph
Abstract
Foundation models have dramatically improved enterprise AI, but most production systems still struggle with fragmented enterprise knowledge, inconsistent context, and unreliable reasoning. Search retrieves documents, vector databases retrieve similar content, and knowledge graphs represent facts—but none continuously model how enterprise state evolves.
This session introduces the Correlation Graph, a new architectural layer that captures enterprise state through Baseline, Change Events, Context, and Weight, enabling AI systems to reason with institutional intelligence rather than isolated retrieval.
We'll explore how Correlation Graphs complement RAG and knowledge graphs to support explainable AI, decision provenance, and agentic workflows in production.
Rajni Sharma
A visionary tech leader building the next intelligence layer for the enterprise—where AI reasons with context, relationships, and organizational memory.
Los Gatos, California, United States
Links
Please note that Sessionize is not responsible for the accuracy or validity of the data provided by speakers. If you suspect this profile to be fake or spam, please let us know.
Jump to top