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Tongyi Qianwen Deep Research Launches Financial Analysis Module, Tapping Real-Time Data on 10K Stocks and Millions of Reports
Qwen's "Deep Research" feature has received a major upgrade with the launch of a professional financial analysis module, marking a new milestone in applying Agentic architecture to specialized vertical domains for large models.

This update thoroughly integrates real-time financial data from Tonghuashun, providing access to minute-level market data for roughly 13,000 global stocks and nearly one million corporate financial reports, announcements, and authoritative research papers. By adopting an advanced Agentic architecture, Qwen now enables full-chain autonomous execution, covering demand analysis, path planning, data retrieval, and multi-source information integration.
Users can currently try this feature for free on Qwen's PC and app versions, generating professional-grade in-depth research reports with a single click. Unlike traditional text generation, the system uncovers underlying financial details such as valuation shifts and cost breakdowns, while automatically producing visualized data charts. All key conclusions are traceable to their original sources, significantly boosting report timeliness and reliability. Before delivering the report, the system also presents a clear analytical framework to ensure the research logic is transparent and visible.

As large models evolve from general conversation to specialized agents, this upgrade not only lowers the barrier for everyday investors to access in-depth financial analysis but also highlights AI's practical capabilities in solving complex professional problems through precise scheduling of external plugins and real-time databases. This signals that AI assistants are shifting from simple information processing tools to digital professional consulting experts with rigorous logic and real-time execution abilities.
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Qwen's "Deep Research" feature has received a major upgrade with the launch of a professional financial analysis module, marking a new milestone in applying Agentic architecture to specialized vertical domains for large models.

This update thoroughly integrates real-time financial data from Tonghuashun, providing access to minute-level market data for roughly 13,000 global stocks and nearly one million corporate financial reports, announcements, and authoritative research papers. By adopting an advanced Agentic architecture, Qwen now enables full-chain autonomous execution, covering demand analysis, path planning, data retrieval, and multi-source information integration.
Users can currently try this feature for free on Qwen's PC and app versions, generating professional-grade in-depth research reports with a single click. Unlike traditional text generation, the system uncovers underlying financial details such as valuation shifts and cost breakdowns, while automatically producing visualized data charts. All key conclusions are traceable to their original sources, significantly boosting report timeliness and reliability. Before delivering the report, the system also presents a clear analytical framework to ensure the research logic is transparent and visible.

As large models evolve from general conversation to specialized agents, this upgrade not only lowers the barrier for everyday investors to access in-depth financial analysis but also highlights AI's practical capabilities in solving complex professional problems through precise scheduling of external plugins and real-time databases. This signals that AI assistants are shifting from simple information processing tools to digital professional consulting experts with rigorous logic and real-time execution abilities.
Enovis acquires eCential Robotics for $180M
eCential’s open, modular architecture enables partnerships with technology firms and implant makers. | Source: eCential RoboticsMedical technology firm Enovis Corp. announced a binding offer to acquire eCential Robotics for €155 million (over $180 mi
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