Contact Center Intelligence one month in: what to prepare before the GA dates
Reflections on Contact Center Intelligence one month after the preview, and what architects should prepare before the general availability dates.
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Notes from real projects. What worked, what didn't, and why — no marketing spin.
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Agent FinOps in the Microsoft Ecosystem - Rev2
A living article on Copilot and agent costs. Where Copilot, Cowork, Copilot Studio, and Foundry agents show their costs, which controls actually stop spending, how to charge costs back, and what Microsoft has changed recently.
Written by
Holger Imbery
Understanding Microsoft Copilot Licensing - Rev2
A living article on what Copilot costs. What the Copilot license costs, how Copilot Credits work, which features use them, and what Microsoft has announced next.
Written by
Holger Imbery
Understanding Microsoft Power Platform Licensing Rev.7
A practitioner's reference for Power Platform core, Copilot Studio, Dataverse, Dynamics 365 Contact Center, and Dynamics 365 Customer Service.
Written by
Holger Imbery
Add User Authentication to Topics
Learn how to add user authentication to specific topics in Microsoft Copilot Studio, enhancing security for sensitive information access.
Written by
Holger Imbery
Copilot Control System - Governing and Administering Copilot and AI Agents
The Copilot control system is an enterprise governance framework for managing AI assistants at scale. It provides comprehensive tools for securing AI data, administering copilots and agents, and measuring business impact. With this unified control system, organizations can confidently deploy Microsoft Copilot while maintaining compliance with security standards, managing permissions, and tracking adoption metrics. This article explores how different stakeholders—from IT admins to business leaders—use the control system to enable responsible AI innovation while mitigating risks
Written by
Holger Imbery
Autonomous Agents - The Future of Automation
Autonomous agents transform enterprise automation by combining AI-driven intelligence with real-time adaptability. Unlike traditional automation, these systems can perceive, decide, and act independently, continuously learning from data to optimize processes. This article explores how technologies like Microsoft's Copilot Studio are leading this evolution and why implementing autonomous agents is becoming a strategic imperative for forward-thinking organizations.
Written by
Holger Imbery
Agentic AI and Microsoft’s Autonomous Agents - An In-Depth Comparison
A comprehensive analysis of agentic AI and Microsoft's autonomous agents, exploring their unique features, use cases, and technological underpinnings.
Written by
Holger Imbery
Measuring for Improvement - Capturing Telemetry in Microsoft Copilot Studio with Azure Application Insights
Learn how to effectively capture and analyze telemetry data in Microsoft Copilot Studio using Azure Application Insights.
Written by
Holger Imbery
Empowering AI Agents with Deep Reasoning in Microsoft Copilot Studio
Microsoft Copilot Studio's new deep reasoning models significantly advance AI agent capabilities, enabling complex problem-solving, logical analysis, and multi-step decision-making. This feature empowers organizations to build virtual agents that can analyze unstructured data, make contextual recommendations, and support sophisticated business processes—all while maintaining accuracy and thoughtful analysis. Learn how deep reasoning models are transforming AI agents from simple Q&A tools into powerful decision-support systems for business intelligence, operations, education, and customer support.
Written by
Holger Imbery
Hello, I’m Holger
I connect enterprise AI architecture with practical implementation, and share what I learn along the way.
I’m a Principal Architect at NTT DATA, Microsoft MVP and Microsoft Certified Trainer (MCT), based in Berlin. My work focuses on agentic AI, intelligent automation, and the Microsoft ecosystem. I help organizations move from promising demonstrations to secure, scalable, well-governed solutions. That means connecting technology choices with business processes, enterprise data, operational ownership, and measurable outcomes.