New plan "Mojitori Plus" is here! From paper to data! The first step towards in-house DX with Mojitori - Announcement of archive distribution.

Easily manage inventory and equipment inspections with AI-OCR! Read text from images and PDFs and save it directly to kintone.

☆New☆ Update Information 2024.12 Support for reading multiple lines has been added. 2024.10 [Major Update] PDF reading capability has been added. 2024.8 Search character specification is now possible with adjacent reading and bottom reading. 2024.6 Added "Bottom Reading" function that can read below specified characters. 2024.4 Mojitori can now be used without a camera. "Mojitori" is a kintone plugin that can extract characters arranged in a specific format from photos and PDFs. It improves work efficiency by reducing transcription tasks and preventing input errors. 【It shines in these situations!】 ■ Equipment management: Alignment with management numbers ■ Inventory management: Item input for stocktaking ■ Checking of product labels ■ Input of values during inspections ■ Business card information registration ■ Identity document registration For more details, please download the catalog below and contact us.

• Document and Data Management

Automatically read step counts from images and reduce transcription work.

♦Background Our company has implemented a program that allows employees to earn rewards based on their average steps per month to promote health. Each month, participants in the program copy the step count screen from their personal healthcare apps, convert it into an image, and register it as evidence in the kintone app. However, since the person in charge visually assesses the results from images of step count screens that differ in format across various apps, it has required about four hours of labor each month. ♦Challenges - The step count screens that serve as evidence vary by individual. - There is a risk of oversight in verification since the person in charge checks visually. - The monthly burden on the person in charge is significant. ♦Solution - Introduced Mojitori. - Reviewed the app's structure to make it easier to apply. ♦Effects of Implementation - Since it can read different screens, we were able to improve operations without significantly changing the current process. - Automatic input has helped prevent human errors. - Reduced labor by 50 hours annually.

• Document and Data Management

Achieving reduced human error risk and improved traceability through digitization from paper-based management.

♦Background At ISS Yamazaki Machinery, we are engaged in the task of cutting rod-shaped steel materials to lengths suitable for forging in our factory. In the process of cutting steel materials, we used to manually check information such as material type, diameter, and charge number (manufacturing number) visually, and manage it on paper cutting instruction sheets. Following incidents of non-conformance due to misidentification of steel material information on-site, we have been advancing business reforms aimed at supplementing visual checks and improving traceability. ♦Challenges - Misconceptions and misidentifications due to visual checks - Difficulty in investigating causes when foreign materials are mixed or non-conformances occur ♦Solution - Implemented a non-visual check function using kintone × Mojitori ♦Effects of Implementation - Supplemented visual check omissions through photo capture and automatic input - Strengthened evidence through photographic records and improved traceability - Expanded to other departments and factories, currently utilized in various operations

• Document and Data Management

[Speaker] Daisuke Imaizumi, President and CEO, Infra Commons Inc. [Key Lecture Content] The "Software-Defined Warfare" led by the U.S. Department of Defense is establishing a new model of warfare centered on AI, autonomous drones, and real-time command and control. This seminar will explain the U.S. strategic shifts, including the Replicator concept, JADC2, and the rise of Palantir and Anduril, while delving into the essence of the structural transformation facing Japan's defense industry. Through the establishment of Anduril's Japanese subsidiary, the "purely domestic drone" concept, and Palantir's data infrastructure and generative AI deployment, we will present how companies like Mitsubishi Heavy Industries, Kawasaki Heavy Industries, Fujitsu, and NEC can play a central role in Japan-U.S. collaboration. We will provide practical insights for existing industries to carve out paths as "co-creation partners" rather than "enemies" in the AI and software-driven era. This is a must-see lecture for rethinking the future of the defense industry.

[Key Lecture Content] 1. Quantum Technology Opening the Future: The Cutting Edge of Quantum Communication Promoted by the Ministry of Internal Affairs and Communications Yuichiro Yano, Deputy Director, Research Promotion Office, Technology Policy Division, International Strategy Bureau, Ministry of Internal Affairs and Communications 1. Basics of Quantum Technology and the Role of the Ministry of Internal Affairs and Communications 2. The Future Brought by Quantum Technology and Government Strategy 3. Research and Development and Quantum Security Bases 4. Social Implementation of Quantum Technology and Use Cases 5. International Initiatives and Future Prospects 6. Q&A / Business Card Exchange 2. The Value and Potential of Quantum Cryptography in the Post-Quantum Era Go Kato, Director, Quantum ICT Research Laboratory, Future ICT Research Institute, National Institute of Information and Communications Technology 1. The Origin of the Security of Quantum Cryptography 2. Current Status of Quantum Cryptography Devices 3. Current Issues and Potential of Quantum Cryptography Technology 4. Long-term Prospects for Future Technological Development of Quantum Cryptography 5. Q&A / Business Card Exchange

[Key Lecture Content] 1. Trends and Future Prospects of Physical AI Hiroshi Kondo, Deputy Director and Expert, Advanced Technology Lab, Japan Research Institute, Ltd. 1. What is Physical AI? 2. Technological trends of generative AI behind Physical AI 3. Examples and research trends of Physical AI 4. Future prospects 5. Q&A / Business card exchange 2. The Future Opened by Physical AI: NVIDIA's Initiatives and Prospects Ken Arai, Senior Manager, Robotics Developer Relations, Enterprise Business Division, NVIDIA Corporation 1. What does NVIDIA perceive as "Physical AI"? 2. Accelerated computing supporting technological evolution 3. The role of digital twins and the importance of synthetic data generation 4. Learning and inference of Physical AI models 5. Implementation examples of Physical AI 6. Q&A / Business card exchange

We are pleased to announce the archive distribution of our seminar titled "New Plan 'Mojitori Plus' Debuts! From Paper to Data! The First Step in Internal DX with Mojitori." 'Mojitori' allows you to convert text from photos, images, PDF files, and more into data, automatically inputting it into various fields in kintone. In this seminar, we will clearly explain the basic functions and usage of Mojitori. Additionally, we will provide detailed explanations about the Plus plan and the document-focused Mojitori, which were added in the major update in November. 【Recommended for】 - Those who are struggling with frequent transcription errors due to manual data entry. - Those who wish to digitize documents currently stored on paper. 【Timetable】 - Overview of Mojitori's functions - Overview of Mojitori Plus's functions - Details and pricing of each plan - Q&A session We look forward to your registration.

Innovating material development at the nano level through high-speed molecular simulation and machine learning With the advancement of molecular simulation technology, it has become possible to handle nano-level phenomena through computer simulations. Additionally, the combination of simulation and machine learning is expanding the range of possibilities. Schrödinger supports the enhancement of analytical power, efficiency, and reduction of development time in your material development using the latest molecular simulation and machine learning technologies, as well as techniques that integrate both. At our exhibition booth, specialized technicians will explain the latest technologies and answer questions from attendees. *During the event, we will hold a seminar at our booth. Theme: "Seeing Inside Materials at the Nano Level" - New Material Development through Simulation and Machine Learning We will introduce examples of predicting physical property values of various materials on a computer. You can experience each software firsthand. 【Exhibition Information】 Exhibition Name: nano tech Dates: January 28-30, 2026 Venue: Tokyo Big Sight, West Hall 3 Booth Number: 3W-H07 Exhibition Zone: [Materials] Material Zone