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With more than 12.3 million stock accounts, the Vietnamese market has no shortage of tools, but data, analytics and trading remain fragmented. FinAlpha is building an ecosystem intended to connect these layers into a more seamless data-to-decision journey for investors.
FinAlpha’s ecosystem is structured around four product layers designed to standardize data, surface relevant information, generate analysis in Vietnamese, and bring execution closer to the research process.
At the base is FinData, the data infrastructure behind the ecosystem. It operates 70+ data tools and 80+ pipelines that continuously collect information, including real-time prices, order books, and foreign money flow in a session, as well as financial statements of listed companies. FinData also covers 34 macroeconomic indicators in Vietnam and a global commodity group.
Its role is to standardize data so that AI layers above can query immediately, rather than repeatedly fetching from multiple sources.
On top of FinData is FinRadar, a news radar layer. The system automatically collects articles from domestic financial sources and international political-economic events, then uses AI to assess the impact of each piece of news on specific stocks and the likelihood of spread to other tickers within the same sector.
Instead of reviewing dozens of news items daily, users can prioritize content directly related to the stocks they follow.
The third layer is FinStock, positioned as an “AI analyst” for Vietnamese stocks. It uses a multi-agent architecture that translates a natural Vietnamese question into a more structured analytical framework, rather than stopping at a short answer.
The final layer is FinOMS, the execution component. It is designed to move beyond a research-focused AI tool by pulling data, analytics and trading closer together within the same interface.
One practical implementation of this direction is StockGuru, the brand version of FinStock deployed with VPBankS during the 2024–2025 period. The system has over 13,000 active users and more than 70,000 AI queries.
For tasks such as quick lookups of a stock’s financial picture, processing time was reduced from tens of minutes to under a minute.
The case study highlights that Vietnamese users require more than a Vietnamese-speaking AI layer. The system also needs to understand domestic listed company data, how users phrase questions, and the market’s rhythm. FinAlpha states it chose to expand from data infrastructure into the analytics and execution layers rather than only deploying a chatbot on third-party data.
Details, demos and free trial registration are available at the FinAlpha homepage: www.finalpha.ai
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