Anthropic has enhanced its AI assistant Claude with two new capabilities: an agent-based research function and Google Workspace integration, both designed to significantly expand the chatbot’s research capabilities.
According to Anthropic, the research function goes well beyond the existing web search feature. Claude conducts multiple sequential searches and independently determines what to investigate next. In short, this is Anthropic’s version of Deep Research.
The second addition is integration with Google Workspace. Claude can now access Gmail and Google Calendar in addition to Google Docs, giving the assistant deeper insight into the user’s work context.
Users can ask Claude to compile meeting notes, identify action items from email threads, and search relevant documents for additional context. Claude delivers these insights with inline citations, so users can verify sources.
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For Claude Enterprise administrators, Anthropic offers an additional cataloging function. When activated, Claude uses a specialized index of an organization’s documents to find information – even when it’s hidden in extensive documents or spread across multiple files.
Availability of the new features
The research function is available as an early beta for Max, Team, and Enterprise plans in the US, Japan, and Brazil. Before introducing this research function, Claude had already received a simpler web search feature that was initially available as a feature preview for paying users in the US. Web search is now also available in Brazil and Japan. The Google Workspace integration is available to all paying users as a beta version.
Anthropic emphasizes that this is just the beginning of further updates. In the coming weeks, the company plans to expand the range of available content sources and give Claude the ability to conduct even more in-depth research.
Similar functions are already known from Perplexity, ChatGPT, Google Gemini or Grok. The major AI chatbots are increasingly aligning in terms of pricing and features – capabilities like internet search, deep research, or code rendering are quickly copied from one another, meaning a feature advantage often lasts only a few weeks.
The real differences between the platforms are mainly found in the quality of the AI models and the user interface, though these subtle distinctions can typically only be properly assessed by experts.
