According to @OpenAI on Twitter, Deep Research now lets users connect to apps in ChatGPT, perform site-specific searches, track real-time research progress with the ability to interrupt and add follow-ups or new sources, and view fullscreen reports. As reported by OpenAI’s official announcement, these capabilities streamline end-to-end research workflows inside ChatGPT, enabling enterprise teams to validate sources faster, centralize citations, and export report-style outputs for stakeholders. According to OpenAI’s post, the real-time progress tracking and mid-run intervention reduce iteration cycles for tasks like competitive analysis, literature reviews, and due diligence, while app connections and targeted site search improve data coverage and retrieval precision for business research.

According to @AravSrinivas, Perplexity has launched an Advanced version of its Deep Research platform, delivering state-of-the-art results on both external and internal benchmarks. This update positions Perplexity as the top performer in deep research tools, surpassing competitors in accuracy, usability, and reliability across all sectors, as reported by God of Prompt on Twitter. This breakthrough highlights practical advancements in AI-driven research and offers significant business opportunities for organizations seeking enhanced data analysis and decision-making capabilities.

According to GeminiApp on Twitter, Deep Research now enhances AI-powered learning by integrating dynamic visuals such as charts, diagrams, and animations. This feature allows users not only to read in-depth analyses but also to visualize complex concepts, improving comprehension and engagement. The update demonstrates a growing trend in AI-driven educational tools that focus on data visualization and interactive learning, presenting new business opportunities for edtech companies to develop advanced AI content platforms that cater to both corporate training and academic markets (source: GeminiApp, Twitter).

According to Google DeepMind, Deep Research is now the first AI agent available through the new Interactions API, which offers a single endpoint for managing complex agentic workflows. This innovation enables developers to streamline the integration of AI-driven research and automation tasks through a unified API, reducing overhead and accelerating deployment of advanced AI solutions in business environments. The Interactions API is designed to facilitate easier scaling and management of multiple AI agents, opening new opportunities for enterprises to enhance productivity and automate research-intensive processes (Source: Google DeepMind, Twitter, Dec 11, 2025).

According to @NotebookLM, the Deep Research feature in NotebookLM has now been officially rolled out to 100% of users, enabling advanced AI-powered source discovery and research capabilities. This update allows users to leverage artificial intelligence for comprehensive analysis, information extraction, and synthesis directly within their research workflow, streamlining the process for professionals across academia, business, and technology. The widespread availability of this feature positions NotebookLM as a competitive AI tool for increasing productivity and accuracy in information gathering (source: @NotebookLM on Twitter, Nov 18, 2025).

According to NotebookLM on Twitter, the newly launched Deep Research feature utilizes AI to browse hundreds of websites, automatically generating organized research reports and providing an annotated list of sources for deeper exploration (source: @NotebookLM, Nov 13, 2025). This advancement streamlines research automation by integrating seamless information gathering and citation management, aimed at knowledge workers, students, and businesses seeking efficient, trustworthy research solutions. Deep Research presents significant business opportunities for AI-driven research assistants, targeting the growing demand for reliable content curation and productivity tools in the digital economy.

According to @perplexity_ai, workspace admins can now leverage the Model Context Protocol (MCP) beta to build custom deep research connectors. This empowers organizations to integrate proprietary systems and various third-party apps, enabling teams to search, reason, and act on internal knowledge alongside web results and pre-built connectors (source: @perplexity_ai, 2024-06). Available to Team, Enterprise, Edu admins, and Pro users, this advancement opens new business opportunities for organizations seeking to enhance AI-driven knowledge management and workflow automation.