This Week in Neo4j: LLMs, Vectors, Metadata Management, Streamlit and more

Welcome to This Week in Neo4j, your weekly fix for news from the world of graph databases! This week was challenging to find something not about LLMs, Vectors and the like, but you can find a video on Metadata Management and findings from building a finance app with Streamlit and Neo4j. Join our Neo4j Research panel! Sign up to share your experiences with a researcher and influence the future of Neo4j products. What’s in it for you? A chance to connect directly with product development teams, get paid compensation, hear about what we are working on, and more! I hope you enjoy this issue, Alexander Erdl  
Dattaraj leads the AI Research Lab at Persistent and drives thought leadership in AI/ML across the company. The team explores state-of-the-art algorithms in Computer Vision, Natural Language Understanding, Probabilistic Programming and more. Connect with him on LinkedIn. In his session at NODES “NeoGenAI: Ontology Guided Loading of Business Data in Graph Database” Dattaraj demonstrates a systematic approach to populating a knowledge graph based on a standard ontology (like FIBO, insurance risk) enabling you to build a knowledge graph guided by ontology in a standardised manner.
Karina Isla-Rios
LLMS: Enhancing Interaction between Language Models and Graph Databases via a Semantic Layer
Tomaz Bratanic explains how Knowledge Graphs offer a versatile representation of structured and unstructured data. An innovative approach involves using Large Language Models (LLMs) to extract parameters from user inputs and apply predefined Cypher templates or functions, enhancing consistency and robustness.
VECTOR DATABASE: Tutorial: Semantic Search, RAG and Index Vector Databases
In her tutorial, Erica Brown compares Vector Databases and Graph Databases for RAG, to learn more about the technology and its implementation.
METADATA MANAGEMENT: Anansi – Visual Metadata Management Tool
Data integrity increasingly becomes a challenge due to the surge in volume within data-driven enterprises. Anansi is a Visual Data Lineage Tool to simplify data webs and ensure effective decision-making, quality assurance, and compliance.
INTEGRATION: Streamlit + Neo4j Integration for Financial Insights
  Vaibhav Koneti launched a project merging Streamlit’s interactive UI and Neo4j’s graph database capabilities into a dynamic Income and Expense Tracker. He takes us on his development journey for advanced financial insights.
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