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    Home»IoT»Introducing Deep Research in Azure AI Foundry Agent Service
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    Introducing Deep Research in Azure AI Foundry Agent Service

    big tee tech hubBy big tee tech hubJuly 9, 2025005 Mins Read
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    Introducing Deep Research in Azure AI Foundry Agent Service
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    Announcing the public preview of Deep Research in Azure AI Foundry—an API and SDK-based offering of OpenAI’s advanced agentic research capability.

    Unlock enterprise-scale web research automation

    Today we’re excited to announce the public preview of Deep Research in Azure AI Foundry—an API and software development kit (SDK)-based offering of OpenAI’s advanced agentic research capability, fully integrated with Azure’s enterprise-grade agentic platform.

    With Deep Research, developers can build agents that deeply plan, analyze, and synthesize information from across the web—automate complex research tasks, generate transparent, auditable outputs, and seamlessly compose multi-step workflows with other tools and agents in Azure AI Foundry.

    AI agents and knowledge work: Meeting the next frontier of research automation

    Generative AI and large language models have made research and analysis faster than ever, powering solutions like ChatGPT Deep Research and Researcher in Microsoft 365 Copilot for individuals and teams. These tools are transforming everyday productivity and document workflows for millions of users.

    As organizations look to take the next step—integrating deep research directly into their business apps, automating multi-step processes, and governing knowledge at enterprise scale—the need for programmable, composable, and auditable research automation becomes clear.

    This is where Azure AI Foundry and Deep Research come in: offering the flexibility to embed, extend, and orchestrate world-class research as a service across your entire enterprise ecosystem—and connect it with your data and your systems.

    Deep Research capabilities in Azure AI Foundry Agent Service

    Deep Research in Foundry Agent Service is built for developers who want to move beyond the chat window. By offering Deep Research as a composable agent tool via API and SDK, Azure AI Foundry enables customers to:

    • Automate web-scale research using a best-in-class research model grounded with Bing Search, with every insight traceable and source-backed.
    • Programmatically build agents that can be invoked by apps, workflows, or other agents—turning deep research into a reusable, production-ready service.
    • Orchestrate complex workflows: Compose Deep Research agents with Logic Apps, Azure Functions, and other Foundry Agent Service connectors to automate reporting, notifications, and more.
    • Ensure enterprise governance: With Azure AI Foundry’s security, compliance, and observability, customers get full control and transparency over how research is run and used.

    Unlike packaged chat assistants, Deep Research in Foundry Agent Service can evolve with your needs—ready for automation, extensibility, and integration with future internal data sources as we expand support.

    How it works: Architecture and agent flow

    Deep Research in Foundry Agent Service is architected for flexibility, transparency, and composability—so you can automate research that’s as robust as your business demands.

    At its core, the Deep Research model, o3-deep-research, orchestrates a multi-step research pipeline that’s tightly integrated with Grounding with Bing Search and leverages the latest OpenAI models:

    1. Clarifying intent and scoping the task:
      When a user or downstream app submits a research query, the agent uses GPT-series models including GPT-4o and GPT-4.1 to clarify the question, gather additional context if needed, and precisely scope the research task. This ensures the agent’s output is both relevant and actionable, and that every search is optimized for your business scenario.
    2. Web grounding with Bing Search:
      Once the task is scoped, the agent securely invokes the Grounding with Bing Search tool to gather a curated set of high-quality, recent web data. This ensures the research model is working from a foundation of authoritative, up-to-date sources—no hallucinations from stale or irrelevant content.
    3. Deep Research task execution:
      The o3-deep-research model starts the research task execution. This involves thinking, analyzing, and synthesizing information across all discovered sources. Unlike simple summarization, it reasons step-by-step, pivots as it encounters new insights, and composes a comprehensive answer that’s sensitive to nuance, ambiguity, and emerging patterns in the data.
    4. Transparency, safety, and compliance:
      The final output is a structured report that documents not only the answer, but also the model’s reasoning path, source citations, and any clarifications requested during the session. This makes every answer fully auditable—a must-have for regulated industries and high-stakes use cases.
    5. Programmatic integration and composition:
      By exposing Deep Research as an API, Azure AI Foundry empowers you to invoke research from anywhere—custom business apps, internal portals, workflow automation tools, or as part of a larger agent ecosystem. For example, you can trigger a research agent as part of a multi-agent chain: one agent performs deep web analysis, another generates a slide deck with Azure Functions, while a third emails the result to decision makers with Azure Logic Apps. This composability is the real game-changer: research is no longer a manual, one-off task, but a building block for digital transformation and continuous intelligence.

    This flexible architecture means Deep Research can be seamlessly embedded into a wide range of enterprise workflows and applications. Already, organizations across industries are evaluating how these programmable research agents can streamline high-value scenarios—from market analysis and competitive intelligence, to large-scale analytics and regulatory reporting.

    Pricing for Deep Research (model: o3-deep-research) is as follows: 

    • Input: $10.00 per 1M tokens.
    • Cached Input: $2.50 per 1M tokens.
    • Output: $40.00 per 1M tokens.

    Search context tokens are charged input token prices for the model being used. You’ll separately incur charges for Grounding with Bing Search and the base GPT model being used for clarifying questions.  

    Get started with Deep Research

    Deep Research is available now in limited public preview for Azure AI Foundry Agent Service customers. To get started:

    We can’t wait to see the innovative solutions you’ll build. Stay tuned for customer stories, new features, and future enhancements that will continue to unlock the next generation of enterprise AI agents.

    A woman sits at a table with a Microsoft tablet and a cell phone. She smiles at the tablet.

    Azure AI Foundry

    Get enterprise AI without enterprise complexity.





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