Workshop Intermediate

Building Knowledge Graph RAG agent systems

Rejected

Session Description

* Knowledge graphs are used in development to structure complex data relationships, drive intelligent search functionality, and build powerful AI applications that can reason over different data types.

• Knowledge graphs can connect data from both structured and unstructured sources (databases, documents, etc.), providing an intuitive and flexible way to model complex, real-world scenarios.

• Unlike tables or simple lists, knowledge graphs can capture the meaning and context behind the

data, allowing you to uncover insights and connections that would be difficult to find with conventional databases.

• This rich, structured context is ideal for improving the output of large language models (LLMs),

because you can build more relevant context for the model than with semantic search alone.

References

https://neo4j.com/developer-blog/knowledge-graph-rag-application/

Session Categories

FOSS

Speakers

Jayita Bhattacharyya Data Scientist | Deloitte

Jayita holds close to 4 years of experience in software development. Passionate about AI/ML space and keen to adopt new technologies to solve real-world problems. She collaborates with her team to integrate AI seamlessly into existing software products, addressing immediate needs with tailored solutions. With a deep passion for the AI/ML landscape, Jayita is pretty active in the hackathon arena with her last win including ATMECS GenAI Challenge. As an official code-breaker and hackathon wizard, she frequently shares her insights on cutting-edge technologies through her blogs, demonstrating her commitment to advancing the field and educating others.