Accelerating AI Utilization of Proprietary Corporate Data, AI-Powered Data Modeling Tool "Mode-ai" Launched. Automatically Analyzes Knowledge from Existing Documents, Drastically Reducing Engineers' Cognitive Load.
Data Nomination Partners Inc. has launched "Mode-ai," an AI-driven data modeling tool designed to accelerate AI utilization of proprietary corporate data. By automatically analyzing existing documents and structures, Mode-ai significantly reduces engineers' cognitive load and streamlines the creation of AI-Ready data infrastructure using their proprietary AIR-DML™ language. A limited-time campaign offers all features for free until September 2026.
📋 Article Processing Timeline
- 📰 Published: April 7, 2026 at 19:10
- 🔍 Collected: April 7, 2026 at 10:30
- 🤖 AI Analyzed: April 18, 2026 at 08:29 (261h 59m after Collected)
On April 7, 2026, Data Nomination Partners Inc. (CEO: Hiroaki Handa), a company that provides data management support, will begin offering "Mode-ai (Mode-AI)," an AI-driven data modeling tool. This new service dramatically streamlines the construction of AI-Ready data infrastructure by having AI analyze and structure a company's unique, complex business and data structures. The core of this technology is our proprietary next-generation context engineering language, "AIR-DML™ (AI-Ready Data Modeling Language)".
[Mode-ai Service Introduction]
https://data-mination.com/solutions/mode-ai
[Mode-ai Use Case Introduction]
https://data-mination.com/solutions/mode-ai/usecases
■ Background of Development: Wanting to Free Engineers from "Document Deciphering"
This tool condenses nearly 20 years of expertise cultivated on the front lines of data management. In modern system development, the semantic layer of data, filled with a company's unique knowledge, tends to be highly specialized, leading to increased cognitive burden and career stagnation for engineers. This structural issue is the fundamental reason why generative AI remains merely an idealistic concept, a "distant dream," and cannot overcome the chasm to practical application.
"Mode-ai" generates data models with just a few clicks, based on "existing table definition documents," which are ubiquitous in IT environments across Japan. When starting new projects or tackling new challenges, it reduces document analysis time by 90%, providing an environment where engineers can concentrate on "solving business problems," which is their true focus.
■ Key Features and Characteristics of "Mode-ai"
1. AI-Driven Data Model Generation
Simply import existing table definition documents from Excel, CSV, etc., and the AI analyzes the data structure, visualizing complex relationships.
2. Natural Language Requirement Definition Support
Automatically generates a draft data model as a basis for consideration from natural language inputs such as "Please create the standard data structure for the XX system." It can be used casually even without specialized knowledge.
3. Promotion of AI-Ready Data Conversion
By formalizing specialized knowledge into explicit formats (diagrams, etc.), AI agents can understand the context, accelerating the construction of high-quality data infrastructure (AI-Ready) essential for utilization.
(Image captions translated as informative text):
- Example of data model generation using natural language "ERP Data Model"
- Automatic modeling starting from table definition document import
- MCP server setup procedure for AI agents
■ Limited-Time Campaign: All Features Offered Free Until End of September 2026
"Mode-ai" is designed for casual use by system engineers and IT engineers, requiring no specialized data modeling knowledge. It features data model generation by importing existing documents like table definition documents and draft generation via natural language.
To allow more users to experience productivity improvements, we are running a campaign offering all "Mode-ai" features for free until the end of September 2026. Basic features will continue to be offered permanently free of charge even after the campaign period.
■ Future Developments
Through the provision of "Mode-ai," Data Nomination Partners Inc. aims to contribute to productivity improvements for all system development sites, accelerating business activities and enhancing the freedom of individual careers.
■ Data Nomination Partners Inc.
- Representative Director: Hiroaki Handa
Engaged in data utilization for IoT platforms for over 10 years in the information systems department of a major manufacturing company. Formalized the question "How to build a foundation that can be effectively utilized" into a paper, winning the Grand Prize for the 54th Japan IBM User Paper. Leveraging acquired experience at a major SI company, implemented end-to-end operations from deal acquisition to customer delivery as a data management consultant. Established and led a cross-group data management organization at a major advertising agency's tech company, receiving the President's Award. Became independent in March 2026 and launched a data management consulting business for corporations.
- Related Sites:
- Data Nomination Partners: https://data-mination.com/
- AI Powered Data Modeling Tool "Mode-ai": https://mode-ai.io/
- Contact: hiroaki.handa@data-mination.com
[Mode-ai Service Introduction]
https://data-mination.com/solutions/mode-ai
[Mode-ai Use Case Introduction]
https://data-mination.com/solutions/mode-ai/usecases
■ Background of Development: Wanting to Free Engineers from "Document Deciphering"
This tool condenses nearly 20 years of expertise cultivated on the front lines of data management. In modern system development, the semantic layer of data, filled with a company's unique knowledge, tends to be highly specialized, leading to increased cognitive burden and career stagnation for engineers. This structural issue is the fundamental reason why generative AI remains merely an idealistic concept, a "distant dream," and cannot overcome the chasm to practical application.
"Mode-ai" generates data models with just a few clicks, based on "existing table definition documents," which are ubiquitous in IT environments across Japan. When starting new projects or tackling new challenges, it reduces document analysis time by 90%, providing an environment where engineers can concentrate on "solving business problems," which is their true focus.
■ Key Features and Characteristics of "Mode-ai"
1. AI-Driven Data Model Generation
Simply import existing table definition documents from Excel, CSV, etc., and the AI analyzes the data structure, visualizing complex relationships.
2. Natural Language Requirement Definition Support
Automatically generates a draft data model as a basis for consideration from natural language inputs such as "Please create the standard data structure for the XX system." It can be used casually even without specialized knowledge.
3. Promotion of AI-Ready Data Conversion
By formalizing specialized knowledge into explicit formats (diagrams, etc.), AI agents can understand the context, accelerating the construction of high-quality data infrastructure (AI-Ready) essential for utilization.
(Image captions translated as informative text):
- Example of data model generation using natural language "ERP Data Model"
- Automatic modeling starting from table definition document import
- MCP server setup procedure for AI agents
■ Limited-Time Campaign: All Features Offered Free Until End of September 2026
"Mode-ai" is designed for casual use by system engineers and IT engineers, requiring no specialized data modeling knowledge. It features data model generation by importing existing documents like table definition documents and draft generation via natural language.
To allow more users to experience productivity improvements, we are running a campaign offering all "Mode-ai" features for free until the end of September 2026. Basic features will continue to be offered permanently free of charge even after the campaign period.
■ Future Developments
Through the provision of "Mode-ai," Data Nomination Partners Inc. aims to contribute to productivity improvements for all system development sites, accelerating business activities and enhancing the freedom of individual careers.
■ Data Nomination Partners Inc.
- Representative Director: Hiroaki Handa
Engaged in data utilization for IoT platforms for over 10 years in the information systems department of a major manufacturing company. Formalized the question "How to build a foundation that can be effectively utilized" into a paper, winning the Grand Prize for the 54th Japan IBM User Paper. Leveraging acquired experience at a major SI company, implemented end-to-end operations from deal acquisition to customer delivery as a data management consultant. Established and led a cross-group data management organization at a major advertising agency's tech company, receiving the President's Award. Became independent in March 2026 and launched a data management consulting business for corporations.
- Related Sites:
- Data Nomination Partners: https://data-mination.com/
- AI Powered Data Modeling Tool "Mode-ai": https://mode-ai.io/
- Contact: hiroaki.handa@data-mination.com