Digitalized Data Acquisition & Management

 iLabPower platform provides an integrated data acquisition and management solution, covering project management, electronic notebooks(ELN), inventory & instrument management, and sample inspection processes.

Cross-Source Data Fusion & Cleaning

The Scientific Data Hierarchy(SDH) Platform helps scientists efficiently summarize and clean data from various sources, including iLabPower, LIMS, ERP, spreadsheets, databases, and more. This enables the establishment of a unified data view and facilitates the identification of key process parameters.

Establishing Data Hierarchy

The Scientific Data Hierarchy platform(SDH) allows scientists, even with minimal IT knowledge, to build their own data hierarchy, enhancing their understanding of key data structures and relationships.

Identification & Optimization of Critical Quality Attributes & Critical Process Parameters

Using MaxFlow AI platform, enterprises can build their own prediction and optimization models. This platform enables data-driven and model-driven identification and optimization of key process parameters.

Enhanced Optimization with DOE and Machine Learning

Using DOE (Design of Experiments) and machine learning, we can quickly identify the optimal process & formulations. The incorporation of machine learning algorithms significantly enhances optimization efficiency, surpassing traditional DOE methods! By leveraging advanced algorithms, our approach not only accelerates the discovery process but also ensures more accurate and reliable results, making it an invaluable tool for modern material science and chemical industry applications.

Intelligent Data-Driven R&D, Exceeding Traditional Limits

The MaXFlow molecular simulation and artificial intelligence platform significantly lowers the application threshold for molecular simulation and AI. Combined with the SDH scientific data hierarchy platform, it offers powerful data fusion and analysis capabilities from various data sources, helping enterprises establish their own machine learning models and R&D data banks.