Neo4j Live: Data-Driven Career Guidance with GraphRAG

Learn how using Neo4j and Graph RAG (Retrieval Augmented Generation), combined with public data and network analysis, can enhance data-driven decision-making in career guidance and talent management. Pedro Parraguez, CEO of Pattrnz, takes us behind the scenes of building WorkMentor.ai, focusing on the broader implications of AI on HR and career development.

Key takeaways include:

– Addressing career development challenges through innovative data solutions.
– The impact of GraphRAG in transforming traditional approaches to HR analytics.
– The role of Neo4j’s APOC and GDS utilities in optimizing organizational data.
– Strategies for integrating AI and deciding between embeddings and LLM chat completions.
– Future trends in people analytics and the expansion of AI-driven career tools.

Guest: Pedro Parraguez, CEO of Pattrnz

APOC https://development.neo4j.dev/labs/apoc/
GDS https://development.neo4j.dev/docs/graph-data-science/current/algorithms/
GraphRAG https://bit.ly/4cXkxhO

0:00 – Introduction and greeting the audience
1:17 – Pedro shares his journey into graphs and graph databases
2:24 – Founding Pattrnz and the role of graphs in their products
3:14 – Discussion on early work with Neo4j and graph technology
4:47 – Conversation on career guidance and how graphs are applied in HR
7:00 – Pedro begins the live demo of Pattrnz and how it works
19:01 – Explanation of using graph technology to create team recommendations
58:02 – Real-world example of identifying sustainability ambassadors using graph data

#neo4j #graphrag #graphdatabase #genai #llm #hr #career #mentor