Chinese financial AI firm raises over RMB 300M in Series B, its third round in a year

A Chinese financial AI company has closed a Series B round of more than RMB 300 million, according to a report published by QbitAI on 14 September. It is the third round the company has raised in the space of a year, an unusual pace at a time when first-tier funding in China has generally become harder to secure.

The investor list spans insurance capital, brokerages, public funds, industrial backers and venture firms. China Insurance Investment, a national-level investment platform for the insurance industry, and GF Xinde, a private fund unit of a major brokerage, joined the round, alongside Qiming Venture Partners, Amber Capital, Jiacheng Capital, CITIC Capital and Zhongding Capital, with China Renaissance again acting as exclusive financial adviser.

The company's product base is an AI investment-research assistant that started with high-frequency entry points such as meeting and information handling before extending into research, analysis and knowledge retention. It now serves more than 120,000 professional users across over 8,000 financial and asset-management institutions, with web traffic that puts it in the first tier of comparable products globally.

In April the company launched PaiWork, an AI investment-research workbench that bundles financial data, research tools, office software and a knowledge base into one working environment, moving AI from single-shot question answering into a complete research process. The company says AI interactions and token consumption on the platform have grown dozens of times over since launch, and that repeat purchases by institutions keep rising.

In June it added iRaB, an evaluation system that tests AI on real investment-research tasks, and started the ORE ecosystem programme with more than 40 brokerage research institutes, data providers and other partners covering data services, professional content and industry skills.

The most notable shift is the arrival of insurance capital. Insurance money spans equities, fixed income and alternative assets, with long research chains and demanding compliance rules, so acceptance there says more about the maturity of financial AI than activity among individual users does.

The company says it will invest further in models and products, broaden its multi-asset client base and deepen industrial collaboration while pushing ahead with an overseas strategy built on local adaptation rather than simply exporting a domestic product. Founder Li Luodan compares AI in serious settings to high-end manufacturing, where the advantage is a system built through long accumulation.

The competition in financial AI is shifting from whether a model can answer a question to whether it can fit workflows, professional standards and shared ecosystems. Whether PaiWork, iRaB and ORE can be reused across more institutions and asset classes — and how the company adapts to different regulatory and data environments abroad — is the most practical test ahead.