AI Application

3 Features of AI Application Development

  • Feature ①
    Support for Deep Learning

    In addition to traditional rule-based AI applications that perform tasks based on inputs, we also develop applications that support Machine Learning and Deep Learning.
    *See the chart below

  • Feature ②
    Cutting-edge Technology
    Utilizing Highly Skilled Talent from Overseas

    NTT DATA INTELLILINK Corporation utilizes overseas engineering resources to achieve the application of AI in business operations, both in terms of global use cases as well as application of cutting-edge technology.

  • Feature ③
    Support in Research & Development

    We can also provide assistance in conducting Proof-of-Concept (PoC) exercises for business application studies and R&D for new technologies.

We support a wide range of AI technologies
and provide AI solutions
to meet a variety of needs

AI Application Use Cases

AI applications are expected to be used in a wide variety of industries.
Below are a few examples of AI application in "finance," "retail and distribution," and "medical and healthcare" fields, where the needs are particularly high.
We can handle projects in other industries as well. Please contact us for more information.


  • FAQs concerning Financial Product Proposals

    Use of Chatbots to address FAQs related to financial product guidance significantly reduces human costs

  • Exchange Rate Forecast

    Highly secure asset management can be achieved by allowing AI to learn and predict the movements of the foreign exchange market

  • Risk Assessment for Loan Review

    In addition to traditional credit checks, AI can be used to predict the likelihood of an individual or company defaulting on its debt by looking at the entire life and huge digital footprint

  • Contract Management

    Automation/Semi-automation of manual tasks to read and write legal contract information

  • Unauthorized Money Transfer Detection

    Detecting multiple rules that are difficult for humans to discover from large amounts of data and predicting future data values

  • Credit Card Fraud Detection

    Detecting increasingly sophisticated credit card frauds with high accuracy

Retail & Distribution

  • Recommendation System

    Providing a personalized shopping experience through analysis of user behavior
    Recommending/Proposing up-sell and cross-sell products to specific customers

  • Image Classification

    Highly accurate identification of dynamic images and creation of predictive models

  • Identification of Similar Products

    AI-based algorithms can be used to search for the most similar products in the same category. Input of product images facilitates search for similar products, thus improving customer purchase rates.

  • Product Classification by Image

    Products can be grouped by giving input of product images. High-level categories of untagged products can be created automatically.

  • Deep Visual-Semantic Alignments

    Deep Neural Networks (CNN and RNN) can be used to create predictive models that generate relevant captions for images.
    This technology can be used to automatically generate product descriptions from images, eliminating a lot of hassle.

Medical and Healthcare

  • Medical Imaging

    Detecting serious diseases and illnesses through medical image analysis. Use in POC for diabetic retinopathy, brain MRI scans, chest x-rays and ultrasound imaging.

  • Application in Medicine Prescription

    With the use of voice-to-text conversion, AI can be used as a facilitator between physicians, patients and pharmacists to improve patient compliance

  • Automatic ICD Coding

    Automation/Semi-automation of ICD coding through textual analysis of information on the relationship between terminological concepts in the field of clinical medicine

    Demo available

  • Text/Image Analysis

    Analyzing various data such as electronic medical records, papers and diagnostic images and using them for diagnostic support and secondary use in new drug development

  • Mental Health Care AP

    In the light of the shortage of mental health professionals, AI-based mental health applications can be utilized to treat patients with mental illnesses and problems

  • Efficient Use of Hospital Resources

    Analyzing patient flow during peak hours to prevent bottlenecks in urgent care