[Kiei Inc.] Exhibiting at AI Expo Spring 2026 (Held on April 7th-8th)
Kiei Inc. will exhibit at AI Expo Spring 2026 on April 7-8, showcasing their AI agent for quality and technology transfer tailored for the manufacturing industry.
📋 Article Processing Timeline
- 📰 Published: April 7, 2026 at 17:23
- 🔍 Collected: April 7, 2026 at 09:00
- 🤖 AI Analyzed: April 21, 2026 at 01:35 (328h 35m after Collected)
Kiei Inc. will exhibit at "AI Expo Spring 2026" (organized by Ice Smiley Inc.), which will be held at the Tokyo International Forum on April 7th (Tue) and 8th (Wed), 2026.
We will showcase our latest solution, the 'Quality and Technology Transfer AI Agent,' which breaks through the barriers of 'technology transfer' and 'unstructured data utilization' faced by the manufacturing industry. We will provide demonstrations on next-generation AI utilization that interprets "unorganized frontline data"—such as drawings, handwritten documents, and veterans' rules of thumb—to automate everything end-to-end, from design risk prediction to maintenance and preservation.
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## ■ Event Summary
- Event Name: AI Expo Spring 2026
- Dates: April 7, 2026 (Tue) 10:00 - 18:00 / April 8 (Wed) 10:00 - 17:00
- Venue: Tokyo International Forum, Hall E
- Organizer: Ice Smiley Inc.
---
## ■ Recommended for companies and personnel with the following challenges:
- "We introduced AI but aren't fully utilizing it"
For those whose deployment has become a dead letter because packaged AI tools and generic chatbots cannot handle the complex workflows and specialized terminology unique to the factory floor.
- "We feel a sense of crisis regarding the brain drain due to retiring veterans"
For those who want to systematically automate the transfer of knowledge to younger staff by converting the "decision-making criteria" and "rules of thumb" in skilled workers' heads into digital assets.
- "We have a massive amount of drawings and handwritten materials and have given up on digitizing them"
For those who want to instantly transform large amounts of unorganized, unstructured data (paper drawings, PDFs, daily reports, etc.) into "usable knowledge" that AI can reference.
- "We want to reduce losses caused by mistakes in design, processes, and maintenance"
For those who want to use past trouble cases as "living knowledge" to elevate design-stage risk prediction (DRBFM) and initial on-site responses using AI.
- "We are rushing toward 'actual operation' beyond just PoC (Proof of Concept)"
For those who want to implement, in the shortest possible time, a "custom AI with high frontline resolution" that can be integrated into on-site operations, rather than ending at the verification stage.
---
## ■ Exhibition Content (Partial selection)
- Design Risk Prediction AI (DRBFM Support)
Automatically extracts risks during design changes from past trouble data. Visualizes veterans' rules of thumb to prevent design errors proactively.
- Process Defect Anticipation AI (PFMEA Support)
Suggests failure modes based on defect records of similar processes. Suppresses defects during the start of mass production and supports vertical startup.
- Equipment Maintenance & Initial Response AI
Instantly presents causes and procedures from past maintenance records when trouble occurs. Minimizes downtime even when veterans are absent.
- Structuring and Utilizing Unstructured Data
AI reads paper drawings, handwritten documents, and PDFs, converting them into usable assets. Transforms scattered frontline information into "usable knowledge."
- Frontline-specific Custom AI
We will showcase our latest solution, the 'Quality and Technology Transfer AI Agent,' which breaks through the barriers of 'technology transfer' and 'unstructured data utilization' faced by the manufacturing industry. We will provide demonstrations on next-generation AI utilization that interprets "unorganized frontline data"—such as drawings, handwritten documents, and veterans' rules of thumb—to automate everything end-to-end, from design risk prediction to maintenance and preservation.
---
## ■ Event Summary
- Event Name: AI Expo Spring 2026
- Dates: April 7, 2026 (Tue) 10:00 - 18:00 / April 8 (Wed) 10:00 - 17:00
- Venue: Tokyo International Forum, Hall E
- Organizer: Ice Smiley Inc.
---
## ■ Recommended for companies and personnel with the following challenges:
- "We introduced AI but aren't fully utilizing it"
For those whose deployment has become a dead letter because packaged AI tools and generic chatbots cannot handle the complex workflows and specialized terminology unique to the factory floor.
- "We feel a sense of crisis regarding the brain drain due to retiring veterans"
For those who want to systematically automate the transfer of knowledge to younger staff by converting the "decision-making criteria" and "rules of thumb" in skilled workers' heads into digital assets.
- "We have a massive amount of drawings and handwritten materials and have given up on digitizing them"
For those who want to instantly transform large amounts of unorganized, unstructured data (paper drawings, PDFs, daily reports, etc.) into "usable knowledge" that AI can reference.
- "We want to reduce losses caused by mistakes in design, processes, and maintenance"
For those who want to use past trouble cases as "living knowledge" to elevate design-stage risk prediction (DRBFM) and initial on-site responses using AI.
- "We are rushing toward 'actual operation' beyond just PoC (Proof of Concept)"
For those who want to implement, in the shortest possible time, a "custom AI with high frontline resolution" that can be integrated into on-site operations, rather than ending at the verification stage.
---
## ■ Exhibition Content (Partial selection)
- Design Risk Prediction AI (DRBFM Support)
Automatically extracts risks during design changes from past trouble data. Visualizes veterans' rules of thumb to prevent design errors proactively.
- Process Defect Anticipation AI (PFMEA Support)
Suggests failure modes based on defect records of similar processes. Suppresses defects during the start of mass production and supports vertical startup.
- Equipment Maintenance & Initial Response AI
Instantly presents causes and procedures from past maintenance records when trouble occurs. Minimizes downtime even when veterans are absent.
- Structuring and Utilizing Unstructured Data
AI reads paper drawings, handwritten documents, and PDFs, converting them into usable assets. Transforms scattered frontline information into "usable knowledge."
- Frontline-specific Custom AI