Qianwen "In-Depth Research" Upgrade: Access to real-time quotes for 13k stocks, providing institutional-level investment research analysis

On April 7, Alibaba’s AI assistant Qianwen announced an upgrade to its “in-depth research” professional capabilities, adding new modules such as financial analysis. It has been connected to real-time intraday stock quotes for 13k stocks and about one million public company earnings reports. Notably, as the industry generally trends toward paid services, the Qianwen team has chosen to make this advanced AI capability free for all users.

For a long time, there has been a significant information gap between retail investors and professional institutions. For example, to analyze a company’s financial report, a retail investor would need to pay an annual fee of tens of thousands of yuan to access a professional financial terminal. When searching for free research reports, the information is fragmented and outdated. If they try to calculate valuations themselves, they may not understand financial ratios.

Qianwen has attempted to change this situation. Through a partnership with Tonghuashun, Qianwen has connected minute-level real-time quote data for more than 13k stocks, and integrated about one million earnings reports, announcements, and research reports from authoritative institutions. A rough estimate suggests that this is equivalent to a professional analyst’s 20 years of reading volume.

The core technical support for this upgrade is the deep application of Qianwen’s Agentic architecture. Unlike traditional AI Q&A, the Agentic architecture gives the system the ability to plan and execute autonomously: after users state their research needs, the system will parse the intent, plan the analysis path, independently call real-time quote and financial report data, and then integrate multi-source information to form a conclusion. Before the official report is output, the system also first displays the analysis framework, making the entire research logic clearly transparent, significantly reducing the “black-box” feel of AI.

Based on this architecture, the research reports generated by Qianwen have timeliness, depth, and traceability. Not only can they pull the latest quotes and institutional views in real time, they can also dig into underlying financial details such as valuation changes and cost breakdowns, and all key data clearly indicate the original sources. In addition to text reports, the system automatically generates visual data charts and supports exporting in Word/PDF format, making it more user-friendly. For investment beginners, Qianwen preloads analysis instruction templates—just replace the stock name to start deep research with one click.

An important context that cannot be ignored is that, due to extremely high computational cost, the deep research feature is pushing the entire industry toward a paid model. Qianwen chose to go the opposite way.

“We observe that the use of deep research shows clear signs of professionalization and PC-scenario characteristics—the number of PC users is twice that of mobile users,” said the product manager of the deep research product. “This indicates that users treat it as a serious product. For a long time, information asymmetry in capital markets has kept retail investors at a disadvantage. We hope AI technology can be used to break down this barrier, rather than create new ones.”

Currently, the upgraded Qianwen “in-depth research” capability has been fully launched on both the PC side (qianwen.com) and the Qianwen app.

(Editor-in-charge: Zhang Xiaobo ）

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