BerriAI / litellm
github.com·3d ago
Developer Tools
Databricks Blog·Sep 1·5 min read
Operationalizing Genie Ontology in Your Data Stack
TL;DR
Genie Ontology enhances enterprise AI by integrating business context with existing data assets, enabling AI agents to provide more accurate and relevant answers. This approach combines modeled business semantics with inferred context, improving the understanding of business operations.
✦ Why It Matters
Start implementing Genie Ontology today to improve the accuracy of your AI agents' responses.
Key Takeaways
- Establish a clean data foundation for AI agents.
- Enrich metadata with clear descriptions and tags.
- Model business logic using Metric Views in Unity Catalog.
- Regularly evaluate and improve the AI context for accuracy.
How It Works
Genie Ontology combines modeled business semantics with context learned from existing data assets. It ranks this context by authority and relevance, ensuring AI agents retrieve the most useful information at answer time.
The process involves creating a semantic layer that defines relationships and metrics, allowing agents to join tables correctly and reducing errors in data interpretation.