AI (Artificial Intelligence) will be utilized to achieve digital transformation.


AI technology is used to improve operations and operational efficiency.


IoT Data Utilization

Not only can sensor data acquired by IoT systems be visualized, but AI analysis can also discover invisible relationships.
In addition, by multiplying operational data and time-series data acquired from other devices, it is possible to predict equipment failures and other problems.


Human Resources and Workplace Reform

By analyzing employee attendance, traffic flow data, and human resource data using AI technology, the activity status of employees can be quantified.
By predicting employee motivation, health risk, retirement risk, and other factors, the system can be used to improve corporate productivity and reform work styles.


EC and Purchasing Analysis

In retail and e-commerce sites, it is necessary to forecast daily demand and purchases from various angles. AI analysis of customer POS data, behavioral data, and site browsing logs can be used to discover new KPIs.


Financial and Insurance Services

In financial and insurance services, it is important to find valuable data from huge amounts of big data.
Increasing profitability can be achieved by forecasting financial risks and improving the efficiency of screening and underwriting operations.


Knowledge modeling
by machine learning


AI-based inference and
KPI discovery


Highly automated

AI Service Product Information

Build AI systems utilizing AWS and GCP machine learning tools.

Amazon Web Services
  • Amazon Machine Learning Machine Learning Platform
  • Amazon Lex Conversational Interface
  • Amazon Polly Text to Speech Conversion Service
  • Amazon Rekognition Image Analysis Services
  • Amazon SageMaker Machine Learning Services
Google Cloud Platform
  • Cloud Machine Learning Engine Predictive analytics engine
  • Cloud Vision API Image Recognition API
  • Cloud Translation API Language Translation API
  • Cloud Natural Language API Natural Language Analysis API
  • Cloud AutoML Vision Machine Learning Services

We provide total support for planning, design, and operation of AI systems.

Study Phase
  • Organize AI system implementation
    objectives and requirements
  • Organize existing systems
  • Consideration of improvement measures by AI
Design Phase
  • Determination of implementation policy
  • Selection of learning model - supervised/unsupervised
  • Platform Selection
  • Algorithm and API selection
  • Prototype Verification
Introduction Phase
  • Building an AI Environment
  • Learning Model Implementation
  • system development
  • Modification of existing systems
  • API Customization
Operation Phase
  • Implementation of business operations
  • Measurement of Effectiveness
  • Review of operational flow
  • Improved accuracy and functionality