Key Points
- Microsoft launches Deep Research in Azure AI Foundry, a new tool for automating complex web research tasks at scale.
- Deep Research uses OpenAI’s technology and Bing Search to create transparent, source-backed insights for businesses.
- Azure AI Foundry now offers flexible cloud-based agents that can be embedded into apps, workflows, and systems for enterprise-wide use.
Microsoft has rolled out a major update to its Windows Azure cloud platform with the introduction of Deep Research in the Azure AI Foundry service. The tool is designed to help businesses automate large-scale web research, making it faster, more reliable, and easier to integrate into their systems. According to reports from insiders, this preview version marks a step forward in Microsoft’s push to provide cloud-based AI solutions tailored for enterprise needs.
Azure AI Foundry is a newer setup within Microsoft’s ecosystem focused on helping companies build and manage AI agents. The key idea here is that Deep Research allows developers to create agents (think of them as smart software tools) capable of planning, analyzing, and synthesizing information from across the internet. These agents go beyond simple web searches by combining OpenAI’s advanced models—like GPT-4o and GPT-4.1—with Bing Search to generate detailed, auditable reports. This is especially important for industries like finance or healthcare, where accuracy and compliance are critical.
One bold feature of Deep Research is its ability to work with other Azure tools. For instance, it can be paired with Azure Functions or Logic Apps to build multi-step workflows. Imagine an agent that first researches market trends, then compiles a presentation, and finally sends the results via email—everything automated without human intervention. Microsoft says this composable architecture makes research a core part of enterprise processes instead of a one-off task.
The system works in steps. First, the agent clarifies the user’s query, using GPT-series models to scope the task. Then, it turns to Bing Search to gather recent, high-quality web data. This helps avoid outdated or incorrect info. Next, the o3-deep-research model (Microsoft’s new tool) performs the research, analyzing sources and building nuanced responses. Finally, the output includes not just answers, but also a record of each step, source links, and any clarifications made during the process. This transparency is a big plus for regulated industries and high-stakes business decisions.
Pricing details were also shared. Deep Research charges are based on token usage: $10 per 1M input tokens, $2.50 for cached input, and $40 per 1M output tokens. Additional costs apply for Bing Search and the GPT models supporting the agent. Microsoft notes these rates are competitive, emphasizing that the tool is meant for enterprise-scale automation, where even small savings add up over time.
Azure AI Foundry is positioning itself as a go-to platform for businesses aiming to reduce the complexity of enterprise AI. The service lets companies embed, extend, and control research workflows using cloud-based tools. Early users are testing the feature for tasks like competitor analysis, market tracking, and compliance reporting. The integration of OpenAI’s research capabilities with Microsoft’s cloud infrastructure is seen as a strategic move to attract businesses that want AI-powered decisions without the headaches of managing custom solutions.
Developers can now access Deep Research through a limited public preview. Microsoft has created guides and tutorials to help teams get started, urging them to sign up for early access. The company expects to share customer success stories once more users begin deploying the service.
For now, the focus remains on flexibility and governance. Unlike typical chatbots, Deep Research agents can grow with a company’s needs, connecting to future data sources as they become available. Microsoft’s push into cloud-based, programmable research tools highlights its broader goal to lead in enterprise AI, blending cutting-edge models with secure, scalable infrastructure.
The feature is part of Microsoft’s growing Azure AI Foundry initiative, which aims to cut down the time and effort required to build and manage AI systems. As more companies rely on data-driven decisions, cloud-based automation like this could become a key differentiator in the tech industry.
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You might also like: Why Choose Azure Managed Applications for Your Business & How to download Azure Data Studio.
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