
Operationalizing AI Ontologies
An operational intelligence layer, the ontology, models relationships of entities and actions, enabling “digital twins” for organizations.
Check out our blog for our latest thoughts on data, AI, and digital products.
Explore topics
An operational intelligence layer, the ontology, models relationships of entities and actions, enabling “digital twins” for organizations.
We’ve put together a simple guide on what we believe is a must have security functionality: anonymizing structured data effectively. Let’s ensure your data is both perfectly secure and fully usable for business operations.
Regardless of advances in human-computer interaction, typing at least a part of our commands remains a staple. Now, ChatGPT is pretty much synonymous with AI-human interaction. But are these just remnants of a very strong mental model, or is it the most effective way to interface with computers? It might be both.
MCPs are all the rage. The right implementation can make or break your agentic project, and there are quite a few things to consider under the hood. We’re breaking down how data is passed around from Business Agents to MCP servers, and all the client-side intricacies you need to be aware of when implementing MCPs.
Peek into the practical side of AI agent development. We cover key frameworks like LangGraph, essential protocols like the new MCP and A2A, and tips to help developers build effective AI agents.
A concise introduction to reasoning models as the next frontier in AI, highlighting their structured thinking capabilities beyond text prediction.
Learn how the partnership between SAP and Databricks enables real-time analytics and AI capabilities for Fortune 500 companies.