On Demand: Accurate, Explainable GenAI With Neo4j and Google Cloud

40 minutes

Relying on vector-search RAG alone might not get the best GenAI results. Vector search by itself misses out on context and deeper meaning. It doesn’t catch the nuanced specifics of the data relationships between people, places, and things.

However, combining knowledge graphs, LLMs, and vector-search RAG retains crucial context. It also uncovers hidden connections and relationships between data entities to enrich your context further. Your GenAI app can then provide results with:

  • Accuracy
  • Rich context
  • Deep explainability

Watch this on-demand Google 101 webinar about how to get better GenAI results using the Neo4j Graph Database with Google Cloud offerings, such as VertexAI and Gemini. In 40 minutes, you’ll learn how to:

  • Work with the Neo4j Graph Database
  • Uncover hidden connections for deep insights
  • Get better results using Google Cloud, VertexAI, and Gemini


SPEAKER

Ben Lackey Image

Ben Lackey
Director of Global Cloud Channel Architecture, Neo4j

Ben leads the partner architecture team at Neo4j, working closely with our cloud partners to build better-together solutions, making it easier for our customers to quickly get value from Neo4j. He has a Masters degree in Statistical Learning Theory. During his career, he’s worked on everything from original work in polychotomous support vector machines to real-time bond pricing systems.
Maruti C Image

Maruti C
Partner Engineering Lead, Google Cloud

Maruti C is a Partner Engineering Lead at Google Cloud. He works with technology partners to help them succeed and helps organizations use Google Cloud's analytics and database products effectively. Maruti plays a key role in developing strategic relationships to build a strong partner ecosystem, and in delivering cutting-edge solutions.

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