[Kiei Inc.] Exhibiting at NexTech Week Spring (Held from Wednesday, April 15 to Friday, April 17)
Kiei Inc. will exhibit at NexTech Week Spring 2026, showcasing its 'Quality and Technology Transfer AI Agent' designed to solve knowledge transfer and unstructured data utilization issues in manufacturing.
📋 Article Processing Timeline
- 📰 Published: April 15, 2026 at 18:00
- 🔍 Collected: April 15, 2026 at 09:31
- 🤖 AI Analyzed: April 19, 2026 at 14:05 (100h 33m after Collected)
Kiei Inc. will exhibit at "NexTech Week Spring (Organizer: RX Japan Ltd.)" to be held at Tokyo Big Sight from Wednesday, April 15 to Friday, April 17, 2026.
We will showcase our latest solution, the 'Quality and Technology Transfer AI Agent', which breaks through the walls of 'technology transfer' and 'unstructured data utilization' faced by the manufacturing industry. We will introduce and demonstrate next-generation AI utilization that interprets 'unorganized on-site data' such as drawings, handwritten documents, and veterans' rules of thumb, fully automating everything from design risk prediction to maintenance and preservation.
■ Event Overview
- Event Name: NexTech Week Spring
- Dates: Wednesday, April 15 to Friday, April 17, 2026, 10:00 - 17:00
- Venue: Tokyo Big Sight
- Organizer: RX Japan Ltd.
■ Recommended for companies and persons in charge with the following challenges:
- "We introduced AI, but it is not fully utilized."
Those whose introduction of packaged AI tools or general-purpose chatbots has become a mere formality because they cannot handle complex operational flows or specialized terminology unique to the field.
- "We feel a sense of crisis about technology drain due to the retirement of veterans."
Those who want to digitize the 'judgment criteria' and 'rules of thumb' in the minds of skilled workers and automate knowledge transfer to younger staff as a system.
- "We have given up on digitizing because of the vast amount of drawings and handwritten materials."
Those who want AI to instantly convert massive amounts of unorganized unstructured data (paper drawings, PDFs, daily reports, etc.) into 'usable knowledge' that can be referenced.
- "We want to reduce losses caused by mistakes in design, processes, and maintenance."
Those who want to utilize past trouble cases as 'living knowledge' to advance risk prediction in the design stage (DRBFM) and initial response on-site with AI.
- "We are in a hurry for 'practical implementation' beyond PoC (Proof of Concept)."
Those who want to implement a 'custom AI with high on-site resolution' capable of being integrated into on-site operations in the shortest possible time, rather than ending with just verification.
■ Exhibition Content (Partial Introduction)
- Design Risk Prediction AI (DRBFM Support)
Automatically extracts risks during design changes from past troubles. Visualizes veterans' rules of thumb and prevents design mistakes before they happen.
- Process Defect Prediction AI (PFMEA Support)
Suggests failure modes based on defect records of similar processes. Suppresses defects during mass production launch and supports vertical startup.
- Equipment Maintenance & Initial Response AI
When a trouble occurs, it instantly presents the cause and procedure from past maintenance records. Minimizes downtime even in the absence of a veteran.
- Structuring and Utilization of Unstructured Data
AI interprets paper drawings, handwritten documents, and PDFs, converting them into usable assets. Transforms disjointed on-site information into 'usable knowledge'.
- On-site Specialized Custom AI Implementation Support
Solves unique on-site challenges that general-purpose AI cannot solve based on interviews. Realizes a demo in a minimum of 2 weeks and practical operation in 3 months.
Click here for exhibition details.
We sincerely look forward to your visit.
Please feel free to contact us if you have any questions or concerns.
We will showcase our latest solution, the 'Quality and Technology Transfer AI Agent', which breaks through the walls of 'technology transfer' and 'unstructured data utilization' faced by the manufacturing industry. We will introduce and demonstrate next-generation AI utilization that interprets 'unorganized on-site data' such as drawings, handwritten documents, and veterans' rules of thumb, fully automating everything from design risk prediction to maintenance and preservation.
■ Event Overview
- Event Name: NexTech Week Spring
- Dates: Wednesday, April 15 to Friday, April 17, 2026, 10:00 - 17:00
- Venue: Tokyo Big Sight
- Organizer: RX Japan Ltd.
■ Recommended for companies and persons in charge with the following challenges:
- "We introduced AI, but it is not fully utilized."
Those whose introduction of packaged AI tools or general-purpose chatbots has become a mere formality because they cannot handle complex operational flows or specialized terminology unique to the field.
- "We feel a sense of crisis about technology drain due to the retirement of veterans."
Those who want to digitize the 'judgment criteria' and 'rules of thumb' in the minds of skilled workers and automate knowledge transfer to younger staff as a system.
- "We have given up on digitizing because of the vast amount of drawings and handwritten materials."
Those who want AI to instantly convert massive amounts of unorganized unstructured data (paper drawings, PDFs, daily reports, etc.) into 'usable knowledge' that can be referenced.
- "We want to reduce losses caused by mistakes in design, processes, and maintenance."
Those who want to utilize past trouble cases as 'living knowledge' to advance risk prediction in the design stage (DRBFM) and initial response on-site with AI.
- "We are in a hurry for 'practical implementation' beyond PoC (Proof of Concept)."
Those who want to implement a 'custom AI with high on-site resolution' capable of being integrated into on-site operations in the shortest possible time, rather than ending with just verification.
■ Exhibition Content (Partial Introduction)
- Design Risk Prediction AI (DRBFM Support)
Automatically extracts risks during design changes from past troubles. Visualizes veterans' rules of thumb and prevents design mistakes before they happen.
- Process Defect Prediction AI (PFMEA Support)
Suggests failure modes based on defect records of similar processes. Suppresses defects during mass production launch and supports vertical startup.
- Equipment Maintenance & Initial Response AI
When a trouble occurs, it instantly presents the cause and procedure from past maintenance records. Minimizes downtime even in the absence of a veteran.
- Structuring and Utilization of Unstructured Data
AI interprets paper drawings, handwritten documents, and PDFs, converting them into usable assets. Transforms disjointed on-site information into 'usable knowledge'.
- On-site Specialized Custom AI Implementation Support
Solves unique on-site challenges that general-purpose AI cannot solve based on interviews. Realizes a demo in a minimum of 2 weeks and practical operation in 3 months.
Click here for exhibition details.
We sincerely look forward to your visit.
Please feel free to contact us if you have any questions or concerns.