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DOUZONE ICT GROUP provides ICT services that lead enterprise informatization.

AI-Powered Lifecycle Support Platform, Insight OFUS

Established a data warehouse (DW) to gather and store institutional data, facilitating retrieval of desired information at any time for assistance.

By analyzing, visualizing, and processing the extracted data, we can generate insights tailored to your objectives and even compile reports.
Insight OFUS Platform
All-in-One Platform for Data to AI
From Raw Data to Insight—Fully Supported
For Business Use
AI Lifecycle
Supporting the AI Lifecycle for Institutional IT Production.
AI Lifecycle
01 Machine Learning
Batch/Real-time data collection & loading
Offering tools for data processing & integration
Providing tools for labeling unstructured data
Setting up data marts specific to each research project
02 Dev
Providing a cloud-based data analysis environment
Providing collaborative data analysis tools
Providing functionality for integrating with data warehouses
Providing features for model training & monitoring
03 OPS
Deploying models & managing versions
Offering cloud-based infrastructure
Providing tools for labeling unstructured data
Setting up data marts specific to each research project
Expected Benefits
By integrating Machine Learning (ML) into DevOps, we optimize both development efficiency and operational stability.

This unified approach eliminates the divide between development and operations, delivering the highest levels of productivity and reliability for institutional data.
  • 01

    Machine Learning

    • Batch/Real-time data collection & loading
    • Provision of data processing & integration tools
    • Provision of unstructured data labeling tools
    • Configuring data marts for specific research projects
  • 02

    Dev

    • Provision of cloud-based data analytics environment
    • Provision of collaborative data analysis tools
    • Provision of data warehouse integration capabilities
    • Provision of model training & monitoring functionalities
  • 03

    OPS

    • Model deployment & version control
    • Provision of cloud-based infrastructure
    • Monitoring & logging features
    • Management of scalable service availability
Key Features of
the Insight OFUS Platform
DW (Data Collection Tool)
Institution-based data loading, searching, cataloging, and management
Supporting rapid access to datasets through integrated search
Cohort Discovery for extracting data with simple condition setup
WIDE (Data Analysis Tool)
Providing a highly flexible data analysis environment for tasks such as deep learning, machine learning, and more
Providing language options customized to user preferences (Python, R)
Providing a collaborative analysis environment through shared access & permission settings
AI Labeling (Data Labeling Tool)
Supporting unstructured data labeling & structured data generation
Supporting editor tools with labeling functionality
Creating shared projects to enable labeling tasks tailored to specific objectives
WE DP (Data Anonymization Tool)
Setting column information and risk types for data anonymization targets
Providing various processing techniques tailored to the purpose of data anonymization
Providing privacy protection model configuration to maintain a level of privacy beyond pseudonymization
SIMULATOR
(Prediction Modeling Tool)
Offering various machine learning models & data-driven prediction models
Improving data accessibility through user-friendly UI/UX designed for non-experts
Providing learning monitoring, performance vertification, and decision-making insights through predictive simulations
WEHAGO BI
(Visualization & Reporting Tool)
User-friendly visualization tool designed for convenient adoption & usage by all
Convenient analysis environment integrated with data from CDW & WIDE
Real-time analysis & charting capabilities for datasets exceeding 1 million records
Explore the Complete AI Lifecycle
with Insight OFUS
From data collection to processing, analysis, model management, and report generation—all in one place.

Data Collection

  • Real-time batch processing of institutional data
  • Data collection utilizing APIs
  • Data story with rapid scalability

Data Management

  • Creation & management of data catalog
  • Categorization & vertification of collected data
  • Data integration in progress

Data Processing & Preparation

  • Data cleansing, integration, transformation, & segmentation
  • Variable extraction & analysis
  • Data labeling
  • Variable storage

Model Training & Tuning

  • Provision of cloud-based Python/R analysis environment
  • Training progress on the established model
  • Model performance evaluation & saving based on prediction execution

Model Management

  • Continuous improvement & version management of stored models
  • Managing model access to control unnecessary access

Model Deployment

  • Integrating the model into production environment & transitioning to executable form
  • Addressing issues arising in the operational environment & enhancing performance
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