Azure tutorials and guides by Microsoft MVP Jannik Reinhard — Logic Apps, Functions, Automation, OpenAI, AI Search and the supporting Azure services for endpoint admins.
This is only a small blog post but maybe for most of you very helpful especially if you work a lot with Microsoft Graph. Often the problem is you want to run multiple calls and then you have to loop through the single items or have a long line of calls.
While writing another blog post, I found out that there is a batch endpoint for MS Graph. In this blog, I will show you how you can use it and give you also an example script.
Azure AI Search: Build a Powerful AI Search Engine is the practical goal of this article: turning enterprise content into a searchable, ranked, and AI-ready knowledge layer with Microsoft Azure AI Search.
This post is a hands-on guide to Build a Powerful AI Search Engine with Azure AI Search. From configuring the indexer to setting up semantic ranking and vector search, the workflow here is the same one I use to build production-grade AI search for real workloads.
The Azure AI search is one of the most powerful search engines at least in my experience. In times of AI and LLMs, the previously boring technology of search engines is now experiencing a new hype. In this blog post, I’ll guide you through deploying and configuring Azure AI Search, and show how it can transform your data into a highly searchable, AI-enhanced resource.
Read More »
In this short blog I want to show you how you can use GPT to get a summarization of the Intune Management Extension log. This script will read the Intune Management Extension Log file in the ProgramData/Microsoft/IntuneManagementExtension/Logs folder and will pass the latest content of the log to GPT.
As GPT and other large language models revolutionize the way we communicate and how we can build custom solutions for companies, the demand for intuitive frontends to deliver these AI capabilities to end-users has never been higher. If you’re wondering whether there’s a seamless way to integrate a bot into Microsoft Teams, you’re in luck! In this blog, I’ll guide you through the process of developing and deploying your own custom bot tailored for Microsoft Teams and the bot framework from Microsoft.
Read More »
You plan to migrate to Intune? Then do this Cloud Native! Use the chance and get rid of your on-premises environment, maintenance of the infrastructure and move this responsibility to Microsoft. In this blog I want to explain what cloud native is and what Intune provides you to make your journey to a success. If you want to validate the provisioning part first, start with a Windows Autopilot test lab.
In the last post I explained how you can build a CoPilot using the Azure OpenAI Studio in this blog post we will do the same with the CoPilot Studio. Here we will also utilize the Azure OpenAI Service. This is similar to the approach I used for my Intune AI Voice Bot, where AI is also used to interact with Microsoft endpoint management scenarios. Let’s have a quick look into this topic as well:
Read More »
This post walks you through how to build a no-code Intune Copilot in Azure OpenAI Studio — using only the Azure portal, your Intune tenant, and a Microsoft Graph app registration. By the end you will have a working chat interface grounded on Intune device data, deployable to Teams or as a custom web app.
The simplest approach to deploying a chatbot is to do so without any coding. If you want to take this idea further into a more advanced agent scenario, you can also check out how to build a Microsoft Intune AI Agent with Foundry. This is precisely what I aim to demonstrate. Such a chatbot can be tailored to utilize your custom documentation, knowledge articles, or any other resources you wish to integrate. This method simplifies the process, making it accessible even if you’re not well-versed in programming. By leveraging existing documents and knowledge bases, you can create a chatbot that is both informative and aligned with your specific needs and content.
Read More »
Remediations play a pivotal role in effective client management, allowing organizations to proactively identify and resolve end-user issues. Additionally, they serve as a valuable tool for enforcing specific settings or configurations that may not be natively supported in Microsoft Intune. However, the process of crafting these scripts can often be intricate and time-consuming.
Imagine a solution where you can simply describe your desired configurations, and a tool generates the necessary scripts for you. If you find this idea appealing and are keen to explore such a solution, this blog is tailored to meet your exact needs.
In this blog post I want to deep dive with you into how LLMs and CoPilots work, give explanations of the most important aspects, and show you some important architecture aspects and concepts. We will not build our own Copilot, but I will also share some reference architectures and a tool I created to answer your questions with information from your own Intune tenant. Let me know if I should also create a second blog post to walk you step by step through the process of implementing your own bot, which uses your own data and an LLM model to help you in your daily business working with Intune.
This post introduces the new and Updated Intune Group Assignment Script. The original was useful but limited; the New version of the Intune Group Assignment Script supports dynamic groups, scope tags, exclusion assignments, and a much cleaner CLI for use in pipelines.
A few months ago I released a script which lists you all assignments of a Microsoft Entra ID group in intune. With this blog post I will release a new version of this script which includes more configuration objects and improves a lot of the code parts.
