Solution Lab: Entity Resolution for AI: Building Trusted Context for Generative and Agentic AI
Webinar Speaker: Fern Halper, TDWI VP Research, Senior Research Director for Advanced Analytics
Date: Wednesday, December 2, 2026
Time: 9:00 a.m. PT / 12:00 p.m. ET
As organizations move from traditional AI to generative and agentic AI, providing the right business context is becoming increasingly important. AI systems need more than access to enterprise data. They need to understand what that data represents, how information is connected, and which customers, products, suppliers, and other entities they are working with.
Yet enterprise data is often fragmented across CRM, ERP, customer service, and other systems. The same customer or supplier may appear under different names and identifiers, with inconsistent or incomplete information. Without reliable entity resolution, AI applications may fail to connect relevant information, generate incomplete responses, or take action based on an inaccurate understanding of the entities involved. Entity resolution is therefore an important component of context engineering, helping organizations establish consistent identities and provide AI systems with more complete, accurate business context.
In this TDWI Solution Lab, TDWI will provide an independent perspective on the emerging enterprise context layer, the role of entity resolution in supporting AI, and relevant TDWI research. A specialist from Redpoint Global will demonstrate how entity resolution technologies can identify, match, and connect records across enterprise systems to provide trusted context for generative and agentic AI. Redpoint Global will also join TDWI for a discussion of how organizations can incorporate these capabilities into their broader data and AI architectures.
Data, analytics, and AI leaders will learn:
- Why entity resolution is becoming increasingly important for generative and agentic AI
- How entity resolution helps AI systems recognize and connect customers, products, suppliers, and other entities across disparate data sources
- How entity resolution fits into the broader enterprise context layer alongside semantic technologies, knowledge graphs, and retrieval approaches
- What capabilities to consider when evaluating entity resolution solutions for enterprise AI