Azure AI Foundry 推出 Deep Research，这是一个基于 API 和 SDK 的产品，利用 OpenAI 的高级代理研究能力，并与 Azure 的企业级代理平台完全集成。Deep Research 允许开发者构建能够深入规划、分析和整合来自网络的信息的代理，从而自动化复杂的的研究任务，生成透明、可审计的输出，并与其他工具和代理无缝组合多步骤工作流程。该服务旨在满足企业需求，提供可编程、可组合和可审计的研究自动化，帮助企业将深度研究直接集成到业务应用中，实现多步骤流程自动化，并对知识进行企业级管理。

💡Deep Research 作为 Azure AI Foundry Agent Service 的一部分，提供 API 和 SDK，使开发者能够构建用于自动化网络规模研究的代理，并支持追踪每个见解和来源。

🤖通过 API，Deep Research 允许开发者构建可被应用程序、工作流或其他代理调用的代理，将深度研究转化为可重用、可生产的服务。

🔗Deep Research 可以与其他服务组合，例如与 Logic Apps 和 Azure Functions 结合，以自动化报告、通知等任务，从而实现复杂的工作流编排。

🛡️Azure AI Foundry 提供安全性、合规性和可观察性，确保客户完全控制和透明地运行和使用研究。

💰Deep Research 模型 o3-deep-research 的定价结构包括输入、缓存输入和输出的定价，以及 Bing 搜索和基础 GPT 模型的额外费用。

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:

• Sign up for the limited public preview to gain early access.
• Visit our documentation to learn more about the feature.
• Visit our learning modules to build your first agent with Azure AI Foundry Agent Service.
• Start building your agents today in Azure AI Foundry.

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.

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