3 Features of AI Application Development
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
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.
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
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
Providing a personalized shopping experience through analysis of user behavior
Recommending/Proposing up-sell and cross-sell products to specific customers
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
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
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