Customer Conversation – Implicit + Neo4j: How to Ensure LLM Accuracy
30 Minutes
Answering complex customer inquiries requires deep product and solution knowledge. Support staff often look at multiple sources to come up with accurate answers. LLMs offer an often far speedier option. However, the answers might not be as complete, precise, or accurate as needed. That’s where knowledge graphs come in.
Implicit, a product support company, knows well how knowledge graphs can make LLM information retrieval more accurate and efficient for their AI platform.
Join us on April 8 to hear John Kanarowski, CEO of Implicit, talk to Neha Bajwa, Neo4j’s VP of Product Marketing, about the power of knowledge graphs built on a graph database. In 30 minutes, you’ll learn:
Implicit, a product support company, knows well how knowledge graphs can make LLM information retrieval more accurate and efficient for their AI platform.
Join us on April 8 to hear John Kanarowski, CEO of Implicit, talk to Neha Bajwa, Neo4j’s VP of Product Marketing, about the power of knowledge graphs built on a graph database. In 30 minutes, you’ll learn:
- Implicit's strategy to streamline LLM information retrieval
- How they sought to quicken response times and improve the accuracy of LLM answers
- Why they chose the Neo4j Graph Database as a solution
Register ASAP for a chance to find out how to make your LLM answers more precise and accurate. You’ll receive access to a recording of the event whether you attend or not.
SPEAKER
John Kanarowski
CEO, Implicit
Neha Bajwa
Vice President, Product Marketing, Neo4j
