For over three decades, Wind Information has been a leading provider of financial data and terminal services in China. It packages real-time market quotes, data, and analytical tools into a professional software suite—the Wind Terminal—used daily by fund managers, analysts, and traders for data lookup and research.

While it took Wind 30 years to make this terminal a desktop staple for financial professionals, it only took 30 minutes to feel the enthusiasm of users beyond its traditional clientele. In April of this year, with support from Tencent Cloud, Wind launched a personal version of its flagship AI product, Wind AI (also known as Wind Alice), and integrated it with the WeChat platform. Within just half an hour of launch, the pre-allocated resources were exhausted. Ge Zhengqi, Chief Strategy Officer at Wind Information, urgently contacted Tencent Cloud: user numbers far exceeded expectations, requiring immediate capacity expansion.

This half-hour was like a crack in a door being pushed open. Behind the door lies the financial data and research methodologies Wind has accumulated over 30 years. In front of it are the many more people who previously had no access to them. Many B2B companies get stuck here, building deep professional capabilities but struggling to reach a broader user base. While numerous firms are busy using AI for internal efficiency, Wind is looking beyond its own organization, using financial AI to open a door to tens of millions of financial professionals.

Moving Beyond the Terminal, Into WeChat

In the past, using Wind meant sitting in front of a terminal, familiarizing oneself with thousands of pages—a significant barrier to entry. Its capabilities were long concentrated within financial institutions and professional teams, requiring specialized training to master the Wind Financial Terminal. Wind Alice aims to change this approach. Users don't need to learn the software first; they simply need to articulate what they want to do. Alice then finds the data, calls the tools, builds the analytical framework, reflects and verifies, ultimately delivering the work product directly.

Ge Zhengqi once demonstrated a primary market project: evaluating whether a particular new energy vehicle sector was worth investing in. Previously, this would require four or five people. Now, Alice can temporarily assemble an "AI team" for the project task, with multiple financial expert agents respectively calculating market size, sorting comparable companies, and researching policies, finally delivering an Excel file and a PowerPoint presentation ready for a board meeting. "A project that used to take five people a month can now be handed to Alice, integrating hundreds of pages of working papers," Ge said.

In another real-world M&A project—assessing the possibility of a merger between two companies and whether there were more suitable targets—such a project would traditionally require a professional M&A team and multiple intermediaries working for at least half a year. Now, Alice constructs eight financial expert agents to filter through over two hundred potential targets, analyze strategic M&A logic and fit, and then conduct financial analysis and modeling, equity penetration analysis, transaction structure and feasibility design, shareholder communication strategy, and post-merger integration planning.

The first to adopt Alice were quantitative analysts, private equity professionals, and buy-side fund managers, followed by sell-side analysts, financial advisors, individual investors, and financial journalists. Heavy users treat it almost as a portable research assistant, invoking it dozens or even hundreds of times a day. Where they could only focus on a small batch of targets before, the scope they can now track has expanded roughly tenfold.

But a question quickly arose: why would users specifically open it? At this time, various agent tools are proliferating in the market. Financial needs, in particular, rarely appear on schedule—like seeing a news headline about a policy while on the go, needing to quickly verify a company after a phone call, or receiving a sudden task from a boss or client. By the time one gets back to a computer, that moment has often passed. To move beyond the terminal, Alice needed to be where users could easily find it, and WeChat became the most natural choice. Through the WeChat ClawBot plugin, users can assign tasks to Alice as if sending a message to a contact and receive the results back in WeChat.

However, integrating Alice into WeChat was not as simple as connecting an interface. ClawBot was primarily designed for the OpenClaw ecosystem, while Alice is Wind's self-developed Financial Harness Agent, with different architectures and invocation methods. Tencent Cloud collaborated with Wind to adapt the systems, ensuring tasks sent from WeChat could smoothly flow to Alice.

After the channel was established, the test shifted to stability and security. During market open, midday, and post-close periods, financial inquiries flood in. Tencent Cloud dynamically allocates computing power through elastic scaling to handle traffic peaks. To address risks like prompt injection and malicious Skills, Tencent Cloud's AI Agent Security Center provides capabilities for supply chain detection, call auditing, and full-process traceability.

The hard work behind the WeChat integration has paid off. Ge Zhengqi told Tencent Cloud engineers that after connecting to WeChat, users submitted more tasks and used the service more frequently.

Three Decades of Financial Know-How, Embedded into Agent Workflows

It's not just users entering Alice's ecosystem, but also Skills—expertise crystallized from the experience of professional practitioners. For example:

- A Skill from a Private Equity Research Head: A research head covering over 1,000 companies annually and tracking more than 200 segment leaders long-term packaged his multi-year research process into an "In-depth Stock Analysis Skill." This allows Alice to automatically complete analyses of business models, competitive landscapes, industry chains, and price ranges, and output lists of expectation gaps and risks. Work that previously took three teams a month can now be done by one person in half a day.

- A Skill from the Author of "AI Quantitative Trading": The author condensed experience from analyzing thousands of hot topics, 12 million data sets, and over 50 algorithm models into two Skills: "Daily Pre-Market Sentiment Quantitative Analysis" and "Fund Screening Quantitative Radar." These help users assess market sentiment and generate differentiated allocation strategies.

- An "A-Share Limit-Up Review" Skill: An options analyst turned his daily "A-share limit-up review" into a Skill, enabling Alice to automatically scan the entire market, identify hot spots, and analyze strong performers.

Each Skill encapsulates the research methods accumulated by practitioners over years, allowing these methods to directly call upon Wind's professional data and financial tools.

To encourage more methodologies to be formalized, Wind also held an AI Financial Skill Creation Competition. Within three weeks, the community added over 1,600 new Skills. Combined with official skills, the total is nearing 2,000, with votes and usage exceeding 50,000 instances, creating one of the financial sector's richest skill ecosystems.

Moving forward, Wind is opening its capabilities to more people and agents. Wind AI Alice and AIFin Market have opened up Wind's data capabilities, official financial Skills, and the Alice Agent platform. They simultaneously launched the ima Skills Square and Tencent Cloud's SkillHub, making capabilities like financial task execution, earnings report interpretation, and market trend identification available at the click of a button.

In the past, a user had to open Wind for a single use. Now, when an agent receives a task, it might find Wind in the background. Wind is gaining not just more users, but more opportunities to be integrated into task chains.

Facing the AI era, Wind is comprehensively opening up the assets it has accumulated over the past 30 years, serving both humans and AI. Wind is still on its journey, but it has already pushed open a door to tens of millions of investors and a broader AI ecosystem, charting a new path for B2B capabilities to grow outward.