Innovation in focus

Recently, the GienTech Agent Innovation Competition concluded successfully, featuring dozens of intelligent solution proposals across financial service delivery, business transformation, marketing growth, risk control, data analysis, and operational efficiency. Focusing on financial research and data analysis scenarios, GienTech introduced Stats-AI: the Excel/WPS Intelligent Data Mining Assistant.

In financial institutions, tasks such as investment research, risk assessment, customer segmentation, operational reporting, and marketing modeling all rely heavily on data processing and analytical capabilities. Traditionally, these tasks have depended on specialized tools such as Python, VBA, SAS, and SPSS, creating high learning barriers and complex workflows. As a result, business users often have data at hand but lack an efficient way to turn it into timely insight.

Core Capabilities

Embedded directly into Excel/WPS, Stats-AI allows users to launch tasks through natural language input or table selection, without switching systems or mastering programming languages. It is designed to support the full workflow of:

· Data aggregation and cleansing 

· Quantitative analysis and modeling 

· Chart generation and visualization 

· Automated report output 

It also emphasizes a familiar spreadsheet-based experience, helping reduce repetitive data preparation and report-making while improving analysis efficiency. The solution also highlights capabilities such as code transparency/export, plug-in extensibility, and AI assistance at the individual cell level, strengthening flexibility for different user needs.

Core Architecture cell

Stats-AI is powered by a large-model collaborative engine built on multi-agent coordination. According to the solution design, planning agents handle intent understanding and task decomposition, while execution agents manage API calls and computational processing, with additional support for data processing, analysis, visualization, and modeling. The solution also proposes a dual-loop “planning-and-code-diagnosis” mechanism to improve execution reliability.

Industry focus

The solution is tailored for banking, securities, and insurance scenarios, with built-in knowledge matrices covering risk management, anti-fraud, marketing analysis, compliance monitoring, and NLP applications, supported by 10,000+ accumulated data mining and modeling use cases.

Overall, Stats-AI is designed to lower the barrier to financial data analysis and provide a lightweight, intelligent alternative in the era of large models.

For further inquiries, please contact us.