MatrixFlow List of Products and Services

Recently, AI platforms such as ChatGPT and Azure are widely used in business, but they lack consideration in the following aspects, raising concerns about risks. 1. Reliability - Prevention of misinformation caused by lack of knowledge or outdated information - Prevention of misinformation due to inappropriate questioning (prompts) 2. Explainability and reasoning MatrixFlow's "Reliable Generative AI Service" is designed to address these challenges, enabling companies to utilize AI more safely and effectively. It prevents issues arising from the inappropriate use of AI, such as the spread of misinformation, increased security risks, and ethical problems. MatrixFlow has been working on both language-based and image-based generative AI for over two years, even before the emergence of Midjourney, Stable Diffusion, and ChatGPT. Our strengths lie in our knowledge and achievements in both types of generative AI, as well as providing "MatrixFlow" as a SaaS service, giving us extensive experience in the business implementation of AI. We also thoroughly consider ensuring reliability and compliance in the implementation flow.

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MatrixFlow Inc. will hold a webinar with Daitron Inc., which has comprehensive capabilities in manufacturing and sales integration, titled "Building AI with No Code! The Key to Creating High-Precision AI Lies in On-Site Insights." In this seminar, we will explain tips for generating ideas and planning to utilize AI in business settings, as well as methods for collecting and organizing data, and creating and operating AI without coding. With the no-code AI tool "MatrixFlow," you can create and utilize AI on your own in less than a month. We will also introduce case studies of AI development by companies without programming experience and various initiatives using "MatrixFlow" by our user, Daitron. [Event Overview] ■ Date: April 27, 2023 (Thursday) 13:30 - 14:30 ■ Location: Online (scheduled to be held as an MS-Teams live event) ■ Capacity: Up to 100 participants ■ Registration Deadline: April 20, 2023 (Thursday) by 17:00 *For more details, please refer to the PDF document or feel free to contact us.

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We held a webinar titled "In-Depth Explanation of the No-Code AI Development Platform MatrixFlow: Experience AI Development Hands-On!" The session included a company introduction, product presentations such as "What is MatrixFlow?", "Features of MatrixFlow", and "Benefits of In-House Development", as well as hands-on activities. For more details, please feel free to contact us. 【Program】 ■ Company Introduction ■ Product Introduction - What is MatrixFlow? - Features of MatrixFlow - Benefits of In-House Development ■ Hands-On - Automated Classification of Chatbot Inquiries (Natural Language Processing) *For more details, please refer to the PDF materials or feel free to contact us.

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Utilizing data in business has become a standard practice for companies today. However, not many companies are effectively leveraging data. For those who feel they are not making effective use of data, I would like to introduce the concept of "data-driven management." In this article, I will briefly explain what data-driven management is and present successful case studies where data-driven approaches have led to numerical improvements. If you are looking to increase sales or improve costs by utilizing data, please consider this as a reference. *You can view the detailed content of the article through the related links. For more information, feel free to contact us.*

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Call forecasting in a call center refers to predicting the volume of incoming calls, such as inquiries from customers, that the center will receive. One of the major factors that increase the operational costs of a call center is the labor costs of communicators. Ideally, operations should be conducted in a way that provides sufficient customer satisfaction by appropriately staffing the contact center. In this article, we will introduce methods for achieving call forecasting using Excel and time series analysis through machine learning with AI (artificial intelligence). *For more detailed information, please refer to the related links. Feel free to contact us for further inquiries.*

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In recent years, the term "NoCode" has been frequently heard among developers both domestically and internationally. NoCode refers to a method of developing websites and web services without the need for coding. There is a growing movement to use this NoCode development method to create AI (artificial intelligence). This article aims to explain what can be achieved with NoCode for those who want to develop AI to solve their company's challenges. We will also introduce examples of AI developed using NoCode, so please take a look for reference. *For detailed content of the article, you can view it through the related links. For more information, feel free to contact us.*

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When you think of "AI," what comes to mind? Perhaps image recognition, voice recognition, or autonomous driving? Many people are likely familiar with the terms artificial intelligence and AI, as they often appear in science fiction works. However, there may be few who can answer the question "What is artificial intelligence (AI)?" with a detailed understanding of its meaning. In this article, we will introduce the basics of artificial intelligence (AI), its mechanisms, examples of its applications, and related issues. We will also explain the history of its development and research, as well as what artificial intelligence can and cannot do, so please take a look. *You can view the detailed content of the article through the related links. For more information, feel free to contact us.*

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Deep learning, AI, machine learning. I believe everyone has heard these terms at least once on television or in books. However, there may be few who truly understand what they refer to and why they are attracting attention. In this article, I will provide a simple explanation of what deep learning is for those who have never studied AI. This is a must-read for those who do not understand the difference between deep learning and machine learning, as well as for those who want to know about examples of deep learning applications. *For more detailed content of the article, you can view it through the related links. Please feel free to contact us for more information.

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MatrixFlow Co., Ltd. provided AI technology for part of the development of the "Social Heat Map" offered by Takenaka Corporation. In the development of the algorithm, the use of the no-code AI construction platform "MatrixFlow" has enabled faster development and reduced development costs. The qualitative evaluation data related to "people" generated from this technology provision is expected to contribute to higher-quality urban development. The "Social Heat Map" is a tool that analyzes social media posts with location information using AI, visualizing qualitative evaluations such as what people thought and felt when they actually visited those places. [Overview] - Provided AI technology for part of the development of the "Social Heat Map" offered by Takenaka Corporation. - In the development of the algorithm, the use of the no-code AI construction platform "MatrixFlow" has enabled faster development and reduced development costs. *For more details, please refer to the related links or feel free to contact us.

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We would like to introduce our consulting service for contract development and in-house development support using the no-programming-required AI development tool 'MatrixFlow.' Our product simplifies data processing, machine learning model creation, evaluation, and tuning, making it possible to build AI easily without programming. We will explain how to use the tool and support you until you can develop and utilize AI on your own. 【Features】 ■ Support from AI introduction and development to in-house production ■ Achieve everything from development to in-house production using only MatrixFlow ■ Reduce various costs such as development expenses, labor costs, and communication costs ■ Anyone can perform daily model updates using only mouse operations *For more details, please refer to the related links or feel free to contact us.

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As an approach to food loss, demand forecasting and appropriate price forecasting have been mainstream. However, we now offer a variety of templates for approaches to reducing food loss from different angles, including "demand forecasting" to address overproduction, "appropriate price forecasting" to prevent unsold inventory, "combination optimization" to avoid excess raw materials, and "anomaly detection" in production lines to prevent losses in the production process. Through this project, we aim to solve issues in Japan's food industry and contribute to the achievement of the SDGs in collaboration with businesses in the food manufacturing, wholesale, retail, and dining industries. It is possible to exchange information among partner companies, including the introduction of cases that have directly led to the reduction of food loss. 【Features】 ■ Reducing food loss helps cut costs associated with food waste. ■ Branding effects are expected by fulfilling corporate social responsibility (CSR). ■ A network for information exchange is expanding. *For more details, please refer to the related links or feel free to contact us.

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We would like to introduce a case where Vega Corporation, which operates an e-commerce business (LOWYA) that offers trendy furniture and interior items at low prices, and a cross-border e-commerce platform (DOKODEMO) that sells Japanese products overseas, has implemented "MatrixFlow." The company faced a significant operational challenge in detecting and determining whether the use of a credit card during payment was fraudulent, in order to prevent unauthorized purchases. After the introduction of our product, the efficiency of detection improved through the use of AI, leading to a decrease in fraud. Additionally, not only machine learning but also existing rule-based criteria were used in conjunction, allowing for more efficient checks than before. [Challenges] ■ Felt limitations in manual fraud detection and considered the introduction of AI ■ Wanted to conduct checks more efficiently and accurately for thousands of orders per day *For more details, please refer to the related links or feel free to contact us.

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In February 2022, MyREVO Co., Ltd., which provides data analysis services related to school management for universities and vocational schools, introduced "MatrixFlow." The company faced an issue where the machine learning process for the ingested data was overly automated, making it impossible to explain to customers the logic behind the outputs. After implementing our product, even without a deep understanding of machine learning, customers can grasp the significance of the outputs simply by looking at the impact values. Additionally, we can now propose what actions should be taken based on those outputs, significantly increasing the order rate. [Challenges] - The machine learning process for the ingested data was overly automated. - It was not possible to derive next actions from the outputs. *For more details, please refer to the related links or feel free to contact us.*

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Since the COVID-19 pandemic, a major transformation has occurred in the food industry. As a result, the food industry faces various challenges common to manufacturing, wholesale, and retail sectors, including "low profit margins and growth rates," "rising costs of raw materials, labor, and logistics," "increased quality standards," "efficiency in inventory management (reducing food waste)," and "responding to complex sales channels from procurement to distribution." Additionally, in recent years, even non-experts can utilize IT technologies such as AI, making it possible to address the above challenges more efficiently. This document introduces methods for solving challenges faced by food companies using AI. [Contents (partial)] ■ Challenges in the food industry ■ Solutions to challenges in the food industry using AI ■ Current status and key points of AI utilization *For more details, please refer to the PDF document or feel free to contact us.

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The use of "AI" as a means for demand forecasting is increasing. However, it is often perceived that utilizing this "AI" is not easy at all. In this document, we introduce "methods and examples of building highly accurate and automated AI using AI" for "practical personnel and planning departments in manufacturing, retail, and distribution industries who feel challenges with the accuracy, workload, and reliance on individuals in demand forecasting." We have summarized the content in a way that is easy to understand even for those without AI knowledge, and we hope that after reading this document, you will be able to actually utilize it as a method for demand forecasting. [Contents (partial)] ■ Understanding demand forecasting with AI ■ How to create demand forecasting AI ■ Current status and key points of AI utilization (Appendix) *For more details, please refer to the PDF document or feel free to contact us.

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This document explains the reasons why one should learn "problem-solving methods using AI" without learning programming. AutoML refers to the means and concepts for automating the design and construction of machine learning models, which are the core technology of current AI. It can automate the processing (preprocessing) of data into a format usable for machine learning, the selection of machine learning algorithms, the adjustment of variables for model creation (analysis and prediction), and even the operation of models, making it possible to efficiently reduce costs. Please take a moment to read it. 【Contents (partial)】 ■ Should businesses adopt AI? ■ Positioning on the AI hype cycle ■ What are the time and costs associated with PoC? ■ AutoML allows for quick and small-scale AI implementation ■ What is machine learning? (Reference material) *For more details, please refer to the PDF document or feel free to contact us.

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The AI construction platform 'MatrixFlow' requires no programming and offers various prediction and classification templates. With just a browser, even beginners can easily build and implement AI. It can handle numerical, text, and image data, allowing for the creation of machine learning models for various industries and roles, such as employee turnover prediction, defect detection, sales forecasting, high performer analysis, demand forecasting, and advertising/marketing effectiveness prediction. We listen to your goals for AI implementation and any challenges you may face, and we propose AI solutions suitable for each specific situation. 【Features】 - Equipped with the AutoFlow function that automatically builds high-precision AI just by inputting data. - Includes an automatic preprocessing function that completes optimal preprocessing all at once. - Discloses the algorithms and parameter settings of the constructed AI. - Features an API creation function for integration into business operations. - Includes an explainability feature (XAI) that explains why the AI made specific predictions or classifications. <Currently offering a white paper> You can view a document explaining "Application of AI in Demand Forecasting" and "Automated Machine Learning (AutoML)" available for PDF download.

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