Cole Tramp's Microsoft Insights

Overview

In today’s rapidly evolving AI landscape, selecting the right model for your application is both a technical and strategic decision. Whether you're building a custom copilot, deploying an agent, or enhancing enterprise workflows, the model you choose will directly impact performance, cost, and user experience. This article walks through a structured approach to model selection, starting with your goals, evaluating the need for multimodality, and leveraging benchmark data from Azure AI Foundry to make informed decisions.

Start with Your Objective

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Overview

Welcome to Azure AI Foundry, where artificial intelligence doesn’t just live, it thrives, flexes, and occasionally shows off. If you’ve ever wanted to build apps that talk, see, read, translate, and even judge your content choices, this is your playground. Azure AI Foundry is Microsoft’s curated suite of AI services designed to supercharge your applications with intelligence that is as scalable as it is sophisticated.

Whether you're building a chatbot that flirts with sarcasm or a vision model that spots a cat in a haystack, Azure AI Foundry has the tools to make it happen. It is cloud-native, enterprise-ready, and developer-approved.

The AI Dream Team: Services in Azure AI Foundry

Here’s the lineup of services that make Azure AI Foundry the T-Swift of cloud AI platforms:

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Overview

As AI becomes increasingly embedded in the modern workplace, Microsoft has introduced a suite of tools designed to empower users at every level of technical expertise. Among these are Copilot, Copilot Studio, and Azure AI Foundry. Each serves a distinct purpose in the AI development and deployment lifecycle. Understanding the differences between these tools is essential for organizations looking to harness AI effectively and strategically.

Copilot (M365): Built-In Intelligence for Everyday Users

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