OpenAI's Deep Research is an advanced AI agent integrated into ChatGPT, designed to autonomously conduct comprehensive, multi-step research tasks on the internet.

Introduction

Deep Research leverages OpenAI's latest o3 model to perform in-depth analysis by autonomously browsing and synthesizing information from diverse online sources. It is capable of interpreting and analyzing vast amounts of text, images, and PDFs, enabling it to generate thorough, documented, and clearly cited reports on complex topics. This tool aims to enhance productivity by handling tasks that would typically require extensive human effort.

Key Features

Autonomous Web Browsing

Deep Research can independently search the internet, locate relevant information, and analyze content from various sources, including text, images, and PDFs.

Comprehensive Report Generation

The agent synthesizes gathered data into detailed reports, complete with citations, providing users with well-organized and thorough insights.

Advanced Reasoning Capabilities

Powered by OpenAI's o3 model, Deep Research exhibits enhanced reasoning abilities, allowing it to tackle complex, multi-step tasks effectively.

Use Cases

Market Analysis

Deep Research can conduct extensive market research by analyzing industry trends, competitor strategies, and consumer behavior, aiding businesses in strategic decision-making.

Academic Research

Researchers and students can utilize Deep Research to gather and synthesize information from various academic sources, facilitating literature reviews and hypothesis development.

Financial Reporting

The agent can compile financial data, analyze market conditions, and generate comprehensive financial reports, supporting investment decisions and financial planning. By integrating Deep Research, professionals across various domains can enhance their research capabilities, streamline information gathering processes, and make informed decisions based on comprehensive analyses. (opens in a new window) (opens in a new window) (opens in a new window) Back to main menu Latest Advancements Back to main menu Back to main menu Back to main menu (opens in a new window) (opens in a new window) Back to main menu (opens in a new window) (opens in a new window) (opens in a new window) Back to main menu Brand OpenAI Table of contents (opens in a new window) Share Today, we’re releasing the first set of building blocks that will help developers and enterprises build useful and reliable agents. We view agents as systems that independently accomplish tasks on behalf of users. Over the past year, we’ve introduced new model capabilities—such as advanced reasoning, multimodal interactions, and new safety techniques—that have laid the foundation for our models to handle the complex, multi-step tasks required to build agents. However, customers have shared that turning these capabilities into production-ready agents can be challenging, often requiring extensive prompt iteration and custom orchestration logic without sufficient visibility or built-in support. To address these challenges, we’re launching a new set of APIs and tools specifically designed to simplify the development of agentic applications: The new Responses API (opens in a new window) , combining the simplicity of the Chat Completions API with the tool use capabilities of the Assistants API for building agents Built-in tools including web search (opens in a new window) , file search (opens in a new window) , and computer use (opens in a new window) The new Agents SDK (opens in a new window) to orchestrate single-agent and multi-agent workflows Integrated observability tools (opens in a new window) to trace and inspect agent workflow execution These new tools streamline core agent logic, orchestration, and interactions, making it significantly easier for developers to get started with building agents. Over the coming weeks and months, we plan to release additional tools and capabilities to further simplify and accelerate building agentic applications on our platform. The Responses API is our new API primitive for leveraging OpenAI’s built-in tools to build agents. It combines the simplicity of Chat Completions with the tool-use capabilities of the Assistants API. As model capabilities continue to evolve, we believe the Responses API will provide a more flexible foundation for developers building agentic applications. With a single Responses API call, developers will be able to solve increasingly complex tasks using multiple tools and model turns. To start, the Responses API will support new built-in tools like web search, file search, and computer use. These tools are designed to work together to connect models to the real world, making them more useful in completing tasks. It also brings with it several usability improvements including a unified item-based design, simpler polymorphism, intuitive streaming events, and SDK helpers like response.output_text to easily access the model’s text output. The Responses API is designed for developers who want to easily combine OpenAI models and built-in tools into their apps, without the complexity of integrating multiple APIs or external vendors. The API also makes it easier to store data on OpenAI so developers can evaluate agent performance using features such as tracing and evaluations. As a reminder, we do not train our models on business data by default, even when the data is stored on OpenAI. The API is available to all developers starting today and is not charged separately—tokens and tools are billed at standard rates specified on our pricing page (opens in a new window) . Check out the Responses API quickstart guide (opens in a new window) to learn more. Chat Completions API (opens in a new window) : Chat Completions remains our most widely adopted API, and we’re fully committed to supporting it with new models and capabilities. Developers who don’t require built-in tools can confidently continue using Chat Completions. We’ll keep releasing new models to Chat Completions whenever their capabilities don’t depend on built-in tools or multiple model calls. However, the Responses API is a superset (opens in a new window) of Chat Completions with the same great performance, so for new integrations, we recommend starting with the Responses API. Assistants API (opens in a new window) : Based on developer feedback from the Assistants API beta, we’ve incorporated key improvements into the Responses API, making it more flexible, faster, and easier to use. We’re working to achieve full feature parity between the Assistants and the Responses API, including support for Assistant-like and Thread-like objects, and the Code Interpreter tool. Once this is complete, we plan to formally announce the deprecation of the Assistants API with a target sunset date in mid-2026. Upon deprecation, we will provide a clear migration guide from the Assistants API to the Responses API that allows developers to preserve all their data and migrate their applications. Until we formally announce the deprecation, we will continue delivering new models to the Assistants API. The Responses API represents the future direction for building agents on OpenAI. Developers can now get fast, up-to-date answers with clear and relevant citations from the web. In the Responses API, web search is available as a tool when using gpt-4o and gpt-4o-mini, and can be paired with other tools or function calls. 1 const await responses create 2 model