Enterprise AI Case Study
Anchoring Enterprise GenAI with Knowledge Graphs
How Pfizer achieved 75% faster onboarding (3 months → 3 weeks) using GraphRAG architecture with Neo4j knowledge graphs.
Jonathan Lowe (Pfizer) & Stephen Chin (Neo4j)
•AI Engineer Summit 2024•~20 minutes
75%
Onboarding Time Reduction
3 months → 3 weeks with GraphRAG
30%
GenAI Projects Abandoned
Gartner prediction for 2025
20→3
Manufacturing Worker Tenure
Years (2019 → 2024) - Crisis
<50%
Enterprise Readiness
Reached production (audience poll)
"What used to take 3 months to consolidate, understand, clean up took three weeks or less for a new project. Traversal becomes so much easier in terms of data search and performance gets better. But I found that team performance also took a really big boost from using that tech."
— Jonathan Lowe, Technology Transfer Specialist, Pfizer
On the impact of GraphRAG with Neo4j on enterprise onboarding
The Transformation: Before & After GraphRAG
Before GraphRAG
- • Data consolidation: 3 months
- • Complex data traversal
- • Knowledge at risk (retiring workforce)
- • Lengthy new project setup
After GraphRAG
- • Data consolidation: 3 weeks (75% faster)
- • Easy data traversal
- • Knowledge captured in graph
- • Rapid deployment (3 weeks or less)
Video Reference
Anchoring Enterprise GenAI with Knowledge Graphs
Speakers: Jonathan Lowe (Pfizer), Stephen Chin (Neo4j)
GraphRAG
Neo4j
Pfizer
enterprise-ai
knowledge-graphs
Companies & Technologies
Companies
Technologies
Neo4j
GraphRAG
Knowledge Graphs
Vector Databases
LLMs
Microsoft GraphRAG