GenAI and Graphs: An Introduction to Building GenAI Apps
30 Minutes
How can you tap into GenAI’s vast potential? To build GenAI apps for the enterprise, you must solve common issues like hallucinations and lack of context.
Early adopters have seen promising results by combining GenAI with graph, a technology made to handle billions of connections. Once you ground your LLM with a knowledge graph and add vector search to the mix, you can easily generate accurate, explainable responses.
To grasp the fundamentals of this technology and see what it can do for your GenAI apps, join us for this 30-minute on-demand webinar. You'll learn:
- The main features of the Neo4j graph database that set it apart
- How knowledge graphs ground LLMs in company-specific data
- Why native vector search is crucial
- How to integrate Neo4j with ecosystem tools like LangChain, LlamaIndex, Haystack, and Ollama
We’ll also explore how Neo4j lets you add new data – even unstructured data – without rebuilding a schema from scratch.
If you want to develop GenAI apps that your organization can rely on, don’t miss this webinar.
SPEAKER
Zachary Blumenfeld
Product Specialist
Zach helps empower the field with Neo4j’s industry-leading graph data science capabilities. Zach is a graph enthusiast who helps data scientists, engineers, and business leaders understand and implement graph analytics to solve challenging business problems. He has first-hand experience with a wide range of modern-day analytical challenges, including criminal fraud detection, identity resolution, and recommendation systems. Serving in both data science and software developer capacities, Zach has applied graph computing to law enforcement and government entities in support of missions that counter drug trafficking, human smuggling, money laundering, and child exploitation. He has led the development and deployment of full-stack graph systems designed to facilitate broad search and analytical query requirements.
