Azure AI Content Safety is Microsoft’s AI-powered service for detecting harmful content in both user-generated and AI-generated text and images. It runs as the built-in content filtering system for all Azure OpenAI and Foundry model deployments, screening both prompts and completions through an ensemble of classification models. The service is available as a standalone API and is deeply integrated into the Microsoft Foundry portal. It went through major expansion, adding prompt injection defense, hallucination detection, copyright protection, and PII filtering alongside its core harm-category classifiers.

In my opinion microsoft did here an great job with this service.

Document Intelligence vs. Content Understanding vs. Mistral OCR 3 vs. GPT-5 vs. Azure Vision

Extracting data from documents is no longer just about “reading” text—it’s about intelligent understanding. Whether you’re digitizing 10,000 invoices, building a real-time app to read street signs, or preparing scientific papers for RAG pipelines, Azure offers a specialized toolkit within its Foundry ecosystem.

In this post, we’ll dive deep into performance, pricing, and capabilities of the leading OCR models in Azure—including the brand-new Mistral OCR 3 and VLM-based approaches with GPT-5.

We’ve all built PowerShell scripts to query Intune, wrapped them in some automation, and called it a day. It works. But with Azure OpenAI Service and models like GPT-4.1 and GPT-5.2 optimized for tool calling, there’s a more interesting approach—building an actual AI agent that can talk to your Intune environment.

Instead of writing a script for every query, you build one agent that understands natural language and calls the Graph API on your behalf. Ask it “which Windows devices are non-compliant?” and it figures out the right API call, executes it, and summarizes the results. It’s not magic—it’s function calling with a nice interface.

In this post, I’ll walk you through two different approaches to building this agent: the classic direct SDK approach and the newer Microsoft Agent Framework. Both use the same underlying Graph API client, but differ in how they orchestrate the AI. Let’s dive in.