How to make big data intelligence simpler? GBase AI has the answer.

Today, we are proud to introduce the production-ready product of the GBase AI platform—GBase AI Studio.

GBase AI Studio

is a modeling studio built for business users

GBase AI Studio

GBase AI Studio is a modeling studio built for business users. It provides a graphical workflow. Business users can design machine learning models on the canvas through simple drag-and-drop operations, and GBase AI Studio will display the models and mining results graphically.

GBase AI Studio

Powerful algorithmic capabilities behind the scenes

Such a simple front-end must be backed by a complex engineering backend.

GBase AI Studio features a full data mining workflow, enabling the construction of complex data mining pipelines through parallel and serial combinations of multiple algorithms and processing steps. It has a comprehensive built-in set of algorithms, including machine learning algorithms, deep learning algorithms, data processing and result evaluation algorithms, graph analysis algorithms, etc. Advanced capabilities include streaming machine learning, weak supervision analysis, relational analysis, and more.

GBase AI Studio

Rich application scenarios

With years of experience across multiple industries, GBASE has accumulated extensive domain expertise. Through big data and AI technologies, GBase AI Studio delivers outstanding performance in many areas.

Scenario 1: Stock analysis

Pain points:

Stock fluctuations occur constantly—how to identify abnormal fluctuations;

Massive high-frequency transaction data—how to analyze it quickly and effectively;

Requires specialized stock domain knowledge;

Analysis results need to be interpretable.

Solution: Stock robot

△ Based on GBase UP, perform massive data collection and management;

△ Apply the advanced industry ΔP/Δt methodology to detect abnormal fluctuations;

△ Use advanced ensemble learning algorithms to effectively fuse results;

△ Combine expert rules and news events to guide result interpretation, generating readable reports.

Value:

Real-time data collection and management for massive data, solidifying the data foundation;

Effective fusion of multiple algorithms to improve analysis accuracy;

Combination of various business metrics and time windows to increase anomaly detection coverage;

Built-in expert rules to enhance interpretability of results.

Scenario 2: Listed company relationship analysis

Pain points:

How to quickly analyze massive relationship data;

Complex relationships among listed companies and diverse data sources;

Data from different sources have varying structures and ambiguities—how to fuse them;

Among numerous relationship types, how to discover and identify abnormal correlations.

Solution: Company graph

△ Based on GBase UP, extensively collect data from multiple external sources

△ Use advanced knowledge graph technology for disambiguation, fusion, and layer building

△ Apply parallel in-database graph analysis algorithms for massive relationship analysis

△ Leverage advanced industry relationship analysis models based on relationship + time multi-dimensional analysis

Value:

Powerful multi-source data collection and management functions to solve data challenges;

High-performance computing mechanisms to increase analysis efficiency;

Advanced knowledge graph technology to effectively fuse multi-source data and build a solid data foundation;

Professional entity-relationship analysis models to gain deep and accurate insights into data value.

Beyond these scenarios, GBase AI Studio also plays a vital role in transaction analysis, credit card user profiling, technology supervision platforms, DaaS service platforms, data analysis platforms, and many other use cases.