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Workflow Troubleshooter Agent – My Supportive Super Hero

Workflow Troubleshooter Agent – My Supportive Super Hero

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Ever had a critical workflow break at the worst possible moment? Picture this: an approval is stuck. A notification never arrives. The business is already waiting. And somewhere in the background, a workflow has silently failed. I’ve been there. You know something’s wrong, but finding the root cause feels like searching for a needle in a haystack. Logs are scattered. Errors are cryptic. And every minute of investigation adds more pressure. That’s when I decided I needed more than alerts…

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Lightweight Monitoring for Critical Workflows

Lightweight Monitoring for Critical Workflows

Some time ago, I built a larger Dataverse solution that included a whole bunch of automated workflow tasks. Everything worked fine during development. Then I deployed the solution and quickly realized a painful truth: all these workflows were running completely unobserved. I found myself waiting for a result that simply didn’t appear. I couldn’t see what went wrong in real time. I only got clarity at the end of the day when one of those delayed summary emails showed up….

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Using AI for Data Correction

Using AI for Data Correction

How do you usually use Generative AI? That’s a question I get asked quite often. Most of the time, my answer is something like this: “I use it to summarize texts. I also draft ideas together with the AI, and it helps me write content more efficiently.” But this is just one piece of the puzzle. In automation scenarios within the Power Platform, I also utilize AI for data correction. Today, I will explain how this process works. In detail,…

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Content Understanding from Power Platform

Content Understanding from Power Platform

In one of my last blog posts I introduced my new friend AI Foundry Content Understanding to you. Here I have explained in detail how you can set up Microsoft’s new AI service offering for your documents. Furthermore, I showed you how I deployed my document analyzer in Azure. As result of this exercise, I got an endpoint that I can now use in one of my use cases. In other words, now I can start working with my custom…

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Copilot Knowledge Sources – OneDrive

Copilot Knowledge Sources – OneDrive

Microsoft says adding knowledge to your Copilot is easy. You then open Copilot Studio and discover a lot of different options. But which should I choose for my data? Is uploading a file the right choice? Should I use Azure AI Search or better connecting a Dataverse table directly? Questions over question that I had as I opened Copilot Studio the first time. What is the right thing on my journey of better RAG for my Copilot Agents? In this…

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AI Foundry – Content Understanding Part 2

AI Foundry – Content Understanding Part 2

In my first blog post about AI Foundry Content Understanding, I have showed you my first impression of this new service offering. In detail, I have used a built-in template for extracting financial details of my travel expense documents. Furthermore, I added new fields to this schema to extract and generate additional information. This worked extremely good for my use case where I want to extract travel information from my passenger itineraries and invoices. This time I show you, how…

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AI Foundry – Content Understanding

AI Foundry – Content Understanding

Wow, what is this? AI Foundry have a new preview offering with the name Azure AI Content Understanding. Microsoft writes; Content Understanding aims to extract structured, meaningful insights from any type of unstructured data. This sounds to me like my well-known friend Azure AI Document Intelligence service. Let me check this out with a real business case that I presented at the ColorCloud conference in Hamburg. In my session “More time thanks to smart automation!” I have shown a Dataverse…

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Recap – Experts Live Germany 2025

Recap – Experts Live Germany 2025

What an amazing week. I had the opportunity to attend and speak at the Experts Live Germany conference. More than 350 experts and community members came together at the congress center at Zoo Leipzig – a fantastic location. The conference itself featured a variety of knowledge across four key tracks. These tracks were Cloud & AI, Hybrid, Workplace & Collaboration, and Identity & Security. It was a great event for professionals eager to explore the latest trends and innovations in these…

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Better RAG – Data Preparation for Copilot – Part 2

Better RAG – Data Preparation for Copilot – Part 2

In my last blog post, I explained you why data preparation for Copilot Agents is necessary. In other words, why we must improve the raw data for RAG (Retrieval Augmented Generation). Today I will delve more into the technical details of the preparation step. Let’s discover together what I can do to improve my raw PDF documents. First, I will explain to you how I extract content as Markdown from these documents with Azure AI Document Intelligence. I’m implementing this…

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Better RAG – Data Preparation for Copilot – Part 1

Better RAG – Data Preparation for Copilot – Part 1

Marketing demos show us: Take your document and put it into a Copilot Studio. As result you have a chatbot solution that answers all questions about the document. But is this really the truth? No, it isn’t. This principle works for some well-structured documents with a limited size. Moreover, when I apply the same principle to lots of documents I will fail and that frustrates my end users. Trust me, I have seen this a lot. For that reason, I…

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