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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.

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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