Operationalizing AI Ontologies
An operational intelligence layer, the ontology, models relationships of entities and actions, enabling “digital twins” for organizations.
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Recent posts
Anonymization in Structured Data: A Guide for IT & Technical Managers
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.
Imagine AI Beyond Chat
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.
Model Context Protocol - Intricacies on the Client Side
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.
Frameworks, Protocols, and Practical Tips for Building AI Agents
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.
The Rise of Reasoning Models: How AI is Learning to Think Step by Step
A concise introduction to reasoning models as the next frontier in AI, highlighting their structured thinking capabilities beyond text prediction.
SAP Databricks – Why is it a big deal?
Learn how the partnership between SAP and Databricks enables real-time analytics and AI capabilities for Fortune 500 companies.