NTT DATA Intellilink and NTT DATA MSE Develop Generative AI Solution to Transform Embedded Development Processes through Knowledge Transfer
NTT DATA Intellilink and NTT DATA MSE have jointly developed a generative AI solution that transforms embedded software development. By sharing expert knowledge via AI agents, it aims to reduce the burden on engineers and accelerate talent development.
📋 Article Processing Timeline
- 📰 Published: April 8, 2026 at 00:30
- 🔍 Collected: April 7, 2026 at 16:00
- 🤖 AI Analyzed: April 20, 2026 at 21:23 (317h 22m after Collected)
NTT DATA Intellilink Corporation (Headquarters: Chiyoda-ku, Tokyo; President: Tohru Fujiwara; hereinafter 'NTT DATA Intellilink') and NTT DATA MSE Corporation (Headquarters: Kohoku-ku, Yokohama City, Kanagawa Prefecture; President: Tohru Fujiwara; hereinafter 'NTT DATA MSE') have jointly developed a solution that upgrades and transforms the embedded software development process by utilizing AI agents.
In this solution, all kinds of knowledge, including industry standards, internal know-how, and the experience and intuition of individual engineers, can be shared via AI agents and utilized throughout the entire embedded software development process, such as design, implementation, review, and verification. As a result, the workload on highly specialized engineers is reduced, transforming the structure into one where intermediate and junior engineers can proactively respond. This accelerates the skill improvement of engineers, optimizes talent allocation across the entire organization, and improves the ability to respond to customers.
By combining the knowledge of NTT DATA Intellilink, which has expertise in the latest generative AI technologies and the formalization of tacit knowledge, and NTT DATA MSE, which has the development capabilities and on-site experience of handling everything from planning and design to implementation and verification in the embedded software domain, we will build an AI agent that deeply understands customers' business processes and support the transformation of the development process.
[Background]
To ensure that embedded software operates reliably on hardware such as automobiles and industrial equipment, its development requires advanced design judgments based on the characteristics of both hardware and software. Such judgments necessitate the knowledge and experience of highly specialized engineers, resulting in a structure that relies heavily on manual work at each stage. Consequently, the burden is concentrated on specific engineers, leading to overwork and schedule delays. Other challenges include the risk of retirement due to the aging of engineers and the omission of considerations caused by development relying on the 'intuition' of experienced personnel.
Although there has been a demand to address these challenges for some time, a sufficient solution has not yet been reached. The background behind this includes a decrease in opportunities for technology sharing due to shorter product development cycles, and a decrease in opportunities for comprehensive understanding of hardware and software as long-term product lifecycles make maintenance and differential development the primary focus. Additionally, highly specialized technology tends to become tacit knowledge and is often not adequately documented.
Given this background, we have decided to support problem-solving using AI agents by combining the strengths of NTT DATA MSE, which possesses on-site knowledge cultivated in embedded software development, and NTT DATA Intellilink, which has technical expertise in the latest generative AI domain and know-how in formalizing tacit knowledge.
[Features]
Figure 1: Solution Overview Diagram
1. Integrating standard processes, standards, and legal regulations necessary for embedded development into AI agents
Standard processes advocated by organizations such as IPA (Information-technology Promotion Agency, Japan) and JASA (Japan Embedded Systems Technology Association) are integrated into AI agents using RAG (Retrieval-Augmented Generation) technology (*1).
2. Building industry-specific AI agents reflecting industry and sector-specific know-how
Based on the development support experience accumulated by NTT DATA MSE through actual embedded software development, regarding legal regulations and standard specifications in industries and sectors...
In this solution, all kinds of knowledge, including industry standards, internal know-how, and the experience and intuition of individual engineers, can be shared via AI agents and utilized throughout the entire embedded software development process, such as design, implementation, review, and verification. As a result, the workload on highly specialized engineers is reduced, transforming the structure into one where intermediate and junior engineers can proactively respond. This accelerates the skill improvement of engineers, optimizes talent allocation across the entire organization, and improves the ability to respond to customers.
By combining the knowledge of NTT DATA Intellilink, which has expertise in the latest generative AI technologies and the formalization of tacit knowledge, and NTT DATA MSE, which has the development capabilities and on-site experience of handling everything from planning and design to implementation and verification in the embedded software domain, we will build an AI agent that deeply understands customers' business processes and support the transformation of the development process.
[Background]
To ensure that embedded software operates reliably on hardware such as automobiles and industrial equipment, its development requires advanced design judgments based on the characteristics of both hardware and software. Such judgments necessitate the knowledge and experience of highly specialized engineers, resulting in a structure that relies heavily on manual work at each stage. Consequently, the burden is concentrated on specific engineers, leading to overwork and schedule delays. Other challenges include the risk of retirement due to the aging of engineers and the omission of considerations caused by development relying on the 'intuition' of experienced personnel.
Although there has been a demand to address these challenges for some time, a sufficient solution has not yet been reached. The background behind this includes a decrease in opportunities for technology sharing due to shorter product development cycles, and a decrease in opportunities for comprehensive understanding of hardware and software as long-term product lifecycles make maintenance and differential development the primary focus. Additionally, highly specialized technology tends to become tacit knowledge and is often not adequately documented.
Given this background, we have decided to support problem-solving using AI agents by combining the strengths of NTT DATA MSE, which possesses on-site knowledge cultivated in embedded software development, and NTT DATA Intellilink, which has technical expertise in the latest generative AI domain and know-how in formalizing tacit knowledge.
[Features]
Figure 1: Solution Overview Diagram
1. Integrating standard processes, standards, and legal regulations necessary for embedded development into AI agents
Standard processes advocated by organizations such as IPA (Information-technology Promotion Agency, Japan) and JASA (Japan Embedded Systems Technology Association) are integrated into AI agents using RAG (Retrieval-Augmented Generation) technology (*1).
2. Building industry-specific AI agents reflecting industry and sector-specific know-how
Based on the development support experience accumulated by NTT DATA MSE through actual embedded software development, regarding legal regulations and standard specifications in industries and sectors...