Hey Neo4j Community! 
Just launched LookInsight AI - an email automation platform that uses
Neo4j knowledge graphs to eliminate AI hallucinations.
Live Demo: https://lookinsight.ai
The Problem
LLMs make stuff up. When handling customer emails, ChatGPT might promise
"90-day refunds" when your policy is actually 14 days. Dangerous for businesses.
The Solution
I use Neo4j to store business rules, policies, and product information as
a knowledge graph. Before the AI responds, it queries Neo4j to constrain
responses to verified facts only.
Results (tested on 20,000 real emails from Kaggle)
94% accuracy- 4-second response time
- Zero hallucinations
- VIP customer auto-detection via graph relationships
Tech Stack
- Neo4j - Knowledge graph for business rules & policies
- FastAPI - Backend API
- React - Frontend
- OpenAI GPT-4 - Response generation
- LangChain - Orchestration
How Neo4j Helps
The graph structure models complex relationships:
Before generating any response, I query Neo4j to fetch relevant context
and constraints. This grounds the LLM in verified information only.
Would Love Community Feedback On:
- Better ways to structure the knowledge graph schema
- Performance optimization for real-time queries
- Anyone else solving hallucination problems with graphs?
Happy to share more technical details!
Try the demo: https://lookinsight.ai
- Manohar
hello@lookinsight.ai