Organizing Brownfield Data Across Multiple Plants.
A Practical Guide to Grounding Enterprise AI: RAG vs GraphRAG vs GraphAI
Explore three key approaches to grounding enterprise AI: RAG, GraphRAG, and GraphAI, and discover how to choose the right fit ...
Unity Catalog + Kobai: A Knowledge Graph Should Not Introduce a Second Governance Model
Discover how Kobai integrates seamlessly with Unity Catalog to ensure governance continuity, enabling trusted enterprise AI ...
What Is an Ontology? And Why Domain Experts, Not Engineers, Should Own It
Discover how Kobai's solutions enhance Databricks Lakehouse with semantic intelligence and knowledge graphs, streamlining AI ...
Kobai on Databricks Marketplace: What This Means for Lakehouse-Native AI
Discover how Kobai's solutions enhance Databricks Lakehouse with semantic intelligence and knowledge graphs, streamlining AI ...
Knowledge Graphs 101: What They Are, What They’re Not, and When You Need One
A knowledge graph is an architectural pattern — a way of representing data as interconnected entities with explicit meaning and ...
Your Lakehouse has the Data. Here’s What Unlocks the Full Potential of AI on top of It.
Kobai adds meaning, relationships, and governed AI reasoning to the data foundation you’ve already built without moving ...
What Is a Knowledge Graph — and Why Does It Matter on Databricks?
Discover how knowledge graphs enhance data meaning within Databricks, enabling better analytics, AI reasoning, and ...
From Lakehouse Platform to Enterprise Intelligence
Learn how the evolution from Data Lakehouse to Enterprise Intelligence Platform is transforming data management and enabling ...
Why Knowledge Graphs Don’t Need a Graph Database Anymore
Discover how Lakehouse architecture is revolutionizing knowledge graphs by eliminating the need for separate graph databases.
Why AI on the Lakehouse Still Needs a Semantic Layer
AI on the Databricks Lakehouse: Discover how adding a semantic layer to a Lakehouse architecture enhances enterprise AI systems.
