Beyond RAG: Solving the Entity Resolution Problem in AI Applications
Speaker: Steven Renwick, CEO & Co-Founder of Tilores
Duration: 60 minutes | Live Online | Free
About the Workshop
Retrieval-Augmented Generation (RAG) has become a common approach for connecting large language models to external data. However, retrieving relevant information is only part of the problem. What happens when the same customer appears under different names across multiple databases, or when two different people share similar information?
Traditional RAG systems can retrieve semantically relevant documents, but they aren't designed to determine whether different records refer to the same real-world entity. As a result, AI applications can retrieve incomplete customer histories, mix information from different people, or make decisions based on fragmented data.
This is where Entity Resolution becomes important.
In this free technical webinar, Steven Renwick, CEO and Co-Founder of Tilores, will explore how entity resolution works, why it matters for modern AI applications, and how it can be integrated with RAG pipelines to provide more accurate and consistent context.
We'll move beyond theoretical concepts and look at how entity resolution can be applied to real-world AI systems.
What You'll Learn
Where traditional RAG falls short: Why semantic similarity doesn't necessarily establish identity, and how fragmented data affects LLM responses.
Understanding Entity Resolution: How records from different systems can be matched, deduplicated, and linked to represent the same person, organization, or other entity.
How Entity Resolution works: An introduction to deterministic and probabilistic matching, fuzzy matching, and identity graphs.
Combining Entity Resolution with RAG: How to retrieve unified, entity-aware context instead of relying on disconnected records.
Real-world applications: How entity resolution can improve AI-powered customer support, fraud detection, risk management, and enterprise AI agents.
We'll also explore a practical example using Tilores to illustrate how records from multiple sources can be linked and made available to AI applications.
About the Speaker
Steven Renwick is the CEO and Co-Founder of Tilores, a company developing real-time entity resolution technology that helps organizations connect fragmented records across different data systems.
His work focuses on making reliable, unified entity data available to business applications and AI systems, including RAG pipelines and AI agents.
Through Tilores, Steven works on the challenges of identity matching, data quality, and building reliable data infrastructure for enterprise AI applications.
Who Should Attend?
This webinar is designed for AI engineers, data scientists, data engineers, ML engineers, and developers working with RAG systems, enterprise data, or AI agents.
Basic familiarity with LLMs and RAG will be helpful, but previous experience with entity resolution is not required.
Join us to learn why better retrieval is not always enough, and how resolving identities across fragmented data can help build more reliable AI applications.