

Neo4j developer advocate who turns scattered data into clear steps for building better AI apps
Session
Workshop
Date
Monday, November 30
Level
Intermediate
// AI Engineering Skill /
Grounding models with data
// 01 / Bio
Jennifer Reif is a Developer Advocate at Neo4j, speaker, and writer who helps developers make better use of their data. An avid developer and problem-solver, she explores databases, data modeling, and emerging technologies like AI through hands-on experiments, sharing what she learns at conferences and digital channels around the world. With a background in CMIS and a knack for untangling complex systems, Jennifer focuses on turning scattered data and complex topics into clear, understandable actions to build better applications.
// 02 / The session
Find the wrong evidence before your users do
Abstract
Your agent just gave a customer the wrong refund decision and attached a real company policy to prove it. Now the customer has a screenshot. The passage matched the question. It came from a policy version that didn’t apply to that customer on that date.
In this hands-on workshop you’ll pull apart how that happened and repair it with the simplest approach that works. Then you’ll take on a harder case, where the answer depends on connections across customer, product and policy data. A small set of checks shows when the system has found applicable evidence, and when it should stop.
What you’ll learn
Spot evidence that matches but doesn’t apply
Use graph connections across your data
Know when an agent should stop
What to bring
Laptop
Free Neo4j Aura instance
set up before the session
GitHub account
Skills you’ll practice
// 03 / For attendees
Keep learning
Go deeper on what this session covers.
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