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  • Book Overview & Buying Microsoft Foundry in Action
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Microsoft Foundry in Action

Microsoft Foundry in Action

By : Eduardo Sojo
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Microsoft Foundry in Action

Microsoft Foundry in Action

By: Eduardo Sojo

Overview of this book

Unlock the full potential of AI with Microsoft Foundry, Microsoft’s unified platform for building, orchestrating, and operating AI solutions at scale. This hands-on guide walks you through the full AI application lifecycle, from data preparation and model selection to deployment, monitoring, and continuous evaluation. Written by Eduardo Sojo, a former Microsoft consultant and current solutions architect at Databricks with over two decades of experience, the book focuses on practical implementation using the latest Microsoft Foundry portal. You’ll learn to design intelligent workflows, build agents, and apply guardrails to ensure safe, reliable AI behavior in real-world scenarios. Rather than focusing only on models, the book shows how to connect workflows, agents, evaluations, and observability so solutions are not just functional, but production-ready. You’ll explore real-world use cases such as building copilots, integrating external systems like Databricks, and creating multi-agent architectures that work with enterprise data. By the end, you’ll be able to design, build, and operate secure, scalable, intelligent AI solutions using Microsoft Foundry.
Table of Contents (20 chapters)
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1
Part 1: Getting Started with Microsoft Foundry
4
Part 2: Building with AI Models
10
Part 3: Responsible AI
13
Part 4: Use Cases
18
Other Books You May Enjoy
19
Index

Comparing before implementation

We can continue drilling down in comparisons between models, looking for the best for our purposes. For this mission, we have two options that complement each other: Model Leaderboards and Compare models sections.

The Model Leaderboards section in Microsoft Foundry enables users to evaluate the AI models through different dashboards that rank them in categories like Quality, Safety, Throughput (tokens/sec), Estimated cost, among others:

Figure 4.2: Model Leaderboards

Figure 4.2: Model Leaderboards

Also, there is a Trade-off chart that shows quality in models against different variables like Estimated cost, Throughput (tokens/sec), and Safety. This graph shows the position of different models against the variable selected. You can narrow the number of models to compare by selecting the models from the list on the right or leave clear selections to use all available.

Figure 4.3: Trade-off charts

Figure 4.3: Trade-off charts

Finally, there are comparisons based on scenarios, so you can evaluate the models based on...

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Microsoft Foundry in Action
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