Memgraph invites you to their event

Microchip Optimizes LLM Chatbot with RAG and a Knowledge Graph

About this event

There's often a gap between the people who manage data and those who use it to make decisions. This gap exists because using the data typically requires technical skills, like writing database queries. William Firth from Microchip Technology will show how Large Language Models (LLMs), augmented with Retrieval Augmented Generation (RAG) techniques, such as a knowledge graph, can bridge this gap, making it easy for anyone to access and understand data in real-time.

William will share a case study on how Microchip uses LLMs enriched with RAG using a Memgraph knowledge graph to create a contextual chatbot. This was inspired by the need to quickly answer complex business questions, such as "Why is this customer's sales order late?" William will discuss the implementation process, the advantages it has brought to the table, and the unforeseen challenges encountered with a real-world chatbot.

Hosted by

  • Team member
    Maya Natarajan VP, Product Marketing @ Memgraph

    Maya is VP of Product Marketing at Memgraph and is passionate about all things graph. She holds a PhD in Chemical Engineering from Rice University and started her career in the biotechnology area, where she was in R&D focusing on cardiovascular drugs. She has five patents to her name.

  • Guest speaker
    William Firth Senior Data Scientist @ Microchip Technology Inc.

    William Firth is a Data Science Lead at Microchip Technology Inc. Firth joined Microchip in 2017 after earning his degree in Mechanical Engineering from Rice University. He served as Manufacturing and Operations Manager for Microchip's Government Systems Synchronization and Timing division for four years.


Fastest, Most Affordable Graph Database. Light & Powerful. Tuned for Dynamic Analytics Environments.

Memgraph is a dynamic, lightweight graph database optimized for analyzing data, relationships, and dependencies quickly and efficiently. It offers a rich suite of pre-built deep path traversal algorithms and a library of traditional, dynamic, and ML algorithms tailored for advanced graph analysis.