Deep research in AI chatbots: Which platforms truly offer it and what changes among industry leaders in 2025

The evolution of advanced research: from browsing to multi-agent Deep Research

In recent months, the concept of research in AI chatbots has undergone a true revolution... If in the past, “browsing” tools were limited to checking a handful of web sources in real time, today the “Deep Research” function means a completely new way of querying the web and documents. It is no longer just about finding information, but about organizing multi-step research, orchestrating AI agents that consult dozens or hundreds of sources, synthesize the material, and return detailed reports, often with precise citations, charts, and the option to export results. All this happens in an automated session that can last minutes instead of just seconds. Thus, 2025 marks the transition from simple web search to a real orchestration of artificial intelligences dedicated to in-depth analysis.

ChatGPT Deep Research: the new frontier of advanced research with structured reports and citations

Today, ChatGPT stands out by launching its own native “Deep Research” feature, available in Plus, Team, Enterprise, and Education plans. This mode, selectable directly from the interface (both web and mobile), enables a multi-step search that can last up to 15 minutes. ChatGPT’s AI agents analyze up-to-date web sources, extract data from documents, compare contradictory information, and produce detailed and referenced reports, with clear citations to the sources of every claim. Users can upload files, include specific data, and customize the research. Compared to traditional browsing, Deep Research offers an unmatched depth of analysis, designed for those who need well-structured syntheses based on reliable sources.

Gemini Deep Research: analysis of large volumes and transparent visualization of reasoning processes

Google Gemini 2.5 Pro has also introduced its own “Deep Research” mode, available in Gemini Advanced. The Gemini agent can process up to 1 million tokens in a single session and, when this feature is activated, scans hundreds of sites, compares data, and produces extended reports, often convertible into interactive Canvas or audio summaries. An innovative aspect is the “reasoning panel” that shows users the logical steps and research paths, offering transparency about how each result was reached. While it lacks code execution, Gemini stands out for its ability to handle multiple files simultaneously, analyze massive datasets, and return multimodal analyses on text, images, and documents.

Claude Research: teams of AI agents and document research with a focus on accuracy

Anthropic has developed for Claude Opus 4 (and Team/Enterprise versions) the “Research” function, which uses teams of Claude agents to conduct iterative research on the web and within uploaded documents, especially on Google Workspace. Even though the term “Deep Research” is not explicitly used, the principle is the same: research occurs over several steps, with each agent handling a specific aspect (e.g., source verification, critical analysis, final synthesis), and the end result is a detailed report with references. Claude excels in clarity of explanation and logical deduction, making it ideal for those who need to delve into complex topics or compare different versions of the same subject.

Perplexity Deep Research: source transparency as a key strength

Perplexity AI has also adopted the term “Deep Research” for a function that runs for several minutes, autonomously consults dozens of web sources, aggregates news, and returns a detailed dossier with links to sources and the option to export the result as a PDF. This feature is especially appreciated in the academic and fact-checking world, where it’s essential to demonstrate the origin of every piece of data. While it has a more limited context compared to giants like Gemini or Grok, Perplexity remains one of the most transparent and accessible tools for quickly verifying information and comparing multiple versions of the same news.

Grok DeepSearch: web-scale and real-time distributed research

The Grok platform by xAI has carved out an important niche with its “DeepSearch” function (and the more recent “DeeperSearch”), allowing for distributed, large-scale research, sifting through the web in real time and returning structured reports. Grok includes the ability to execute code during research, useful for quantitative analysis and automated data verification, and aims to offer an “open source intelligence” approach especially appreciated by those working in technology and security. Access, however, is reserved for X Premium+ or “SuperGrok” subscribers, with still rather strict limits on the number of searches.

Let's see a Table for Deep Research features in major AI chatbots (July 2025)

Chatbot	Feature name	Access	Code	Search duration	Live citations	Distinctive notes
ChatGPT	Deep Research	Plus/Team/Ent/Edu	✅	15 min	✅	File upload, rich reports, Python
Gemini 2.5 Pro	Deep Research	Advanced	❌	20 min	✅	Canvas, multi-file, reasoning panel
Claude Opus 4	Research	Max/Team/Ent beta	❌	10 min	✅	Multi-agent, Workspace, explanation
Perplexity Pro	Deep Research	Pro/Web/iOS/Android	❌	2-4 min	✅	Direct citations, PDF export
Grok 3	DeepSearch	X Premium+	✅	10 min	✅	OSINT, code execution, distributed search

Why the Deep Research function marks a turning point for work and study

The real difference compared to the past lies in the ability to delegate not just finding an answer to an AI agent, but the entire research process: from gathering sources to fact-checking to structured, documented synthesis. In professional scenarios—from financial analysis to legal report preparation, to comparing regulatory standards—these new modes save hours of manual work and offer transparency guarantees, thanks to precise citations for each piece of data. All this comes with the possibility to customize research, upload personal documents, integrate calculation code, or visualize the agents’ reasoning processes.

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