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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.
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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.
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.
Memgraph is an open source graph database built for teams who expect highly performant, advanced analytical insights - as compatible with your current infrastructure as Neo4j (but up to 8x faster). Memgraph is powered by an in-memory graph database built to handle real-time use-cases at enterprise
