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MatrixFlow

addressTokyo/Taito-ku/Room 206, Tensho Ueno Suehirocho Building, 2-16-3 Ueno
phone050-5363-9964
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last updated:Feb 02, 2023
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Launch of a "Reliable Generative AI" service that can be used with confidence in business.

We have started providing a reliability-generating AI service based on the requirements of companies using our proprietary generative AI algorithm "TrustExplain."

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 Reliability - Prevention of misinformation caused by lack of knowledge or outdated information - Prevention of misinformation due to inappropriate questioning (prompts) 2.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 improper use of AI, such as the spread of misinformation, increased security risks, and ethical problems. MatrixFlow has been working on language-based generative AI 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 track record 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 fully consider ensuring reliability and compliance in the implementation flow.

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April 27: The importance of on-site knowledge in creating high-precision AI methods.

Webinar Announcement! We will introduce ways to solve business challenges faced by the manufacturing and electronics industries using AI.

MatrixFlow Co., Ltd. will hold a webinar with Daitron Co., Ltd., which has comprehensive capabilities in product 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 the 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 with no code. 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 construction by companies without programming experience, as well as various initiatives utilizing "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 "Thorough Explanation of MatrixFlow."

Introduction to AI Utilization Platforms for Business on March 30, 2023 (Thursday)!

We held a webinar titled "In-Depth Explanation of the No-Code AI Construction Platform MatrixFlow: Let's Experience AI Construction Hands-On!" The webinar 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 information, please refer to the PDF materials or feel free to contact us.

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AI construction platform 'MatrixFlow'

No programming required. You can build AI using just a browser. We offer a white paper explaining the use of AI for demand forecasting and automated machine learning.

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, enabling 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 AutoFlow functionality that automatically builds high-precision AI just by inputting data. ■ Includes an automatic preprocessing feature that completes optimal preprocessing all at once. ■ Discloses the algorithms and parameter settings of the constructed AI. ■ Includes an API creation feature for integration into business operations. ■ Equipped with an explanation feature (XAI) that clarifies why the AI made certain predictions or classifications. <White Paper Available> You can view materials explaining "Application of AI in Demand Forecasting" and "Automated Machine Learning (AutoML)" from the "PDF Download" section.

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[Information] An Era Where Business Professionals Create AI with Automated Machine Learning (AutoML)

In cases where AutoML can be utilized, it is expected that outsourcing costs and labor costs can be significantly reduced!

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 form 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 the model, making it possible to efficiently reduce costs. Please take a moment to read it. 【Contents (partial)】 ■ Should AI be introduced into business? ■ Positioning on the AI hype cycle ■ What are the time and costs associated with PoC? ■ With AutoML, AI can be introduced quickly and on a small scale ■ 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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[Information] How on-site personnel can start AI demand forecasting.

Practical application of highly accurate AI to achieve reductions in waste loss, stockouts, storage costs, and optimization of personnel.

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 high-accuracy, automated AI using AI" aimed at "those who feel challenges with the accuracy, labor intensity, and reliance on individuals in demand forecasting," specifically for practitioners and planning departments in manufacturing, retail, and distribution. We have summarized the information 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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[Data] Food Industry (Manufacturing/Retail/Wholesale)

Utilizing MatrixFlow! Methods and case studies for improving accuracy and efficiency in operations using AI!

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." Moreover, in recent years, even non-experts can utilize IT technologies such as AI, making it possible to address the aforementioned 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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[MatrixFlow Implementation Case] MyREVO Co., Ltd.

The reason why it happened is very clear in relation to the output! A case where the order rate has significantly increased.

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 the 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, the product can suggest what actions to take 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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[MatrixFlow Case Study] Vega Corporation Co., Ltd.

The efficiency of detection has increased with the use of AI, leading to a decrease in fraud! This is an example of how it contributes to the streamlining of operations.

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 was fraudulent during payment, 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 reduction in fraud. Additionally, not only machine learning but also existing rule-based criteria for judgment 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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Introduction to the "AI 0 Project"

Eliminate 3.24 million tons of business-related food waste with AI! We are also starting to recruit joint partners!

As a means to approach food loss, demand forecasting and appropriate price forecasting have been mainstream. However, we now offer a variety of templates for approaches to reduce food loss from different angles, including "demand forecasting" for excess production, "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 food service sectors. 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 will lower the costs associated with food waste. ■ Branding effects are expected by fulfilling corporate social responsibility (CSR). ■ A network for information exchange will expand. *For more details, please refer to the related links or feel free to contact us.

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Consulting services for contracted development and in-house production support.

No experts needed! Reducing various costs such as development expenses, labor costs, and communication costs.

We would like to introduce our consulting service that supports contract development and in-house development 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 any 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 solely with 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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Providing AI technology to Takenaka Corporation's "Social Heat Map".

Transforming location-based social media posts into qualitative evaluations using a unique algorithm! Introduction to technology provision.

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 no-programming-required AI construction platform "MatrixFlow" was used to accelerate development and reduce 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 the qualitative evaluations of 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 no-programming-required AI construction platform "MatrixFlow" was used to accelerate development and reduce costs. *For more details, please refer to the related links or feel free to contact us.

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What is deep learning? Differences from AI and machine learning.

For those who have never learned about AI! An article introducing what deep learning is.

Deep learning, AI, and machine learning. I believe everyone has heard these terms at least once on television or in books. However, there may be few people who 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. It is also a must-read for those who do not understand the difference between deep learning and machine learning, or who want to know about examples of deep learning applications. *For more detailed information, you can view it through the related links. Please feel free to contact us for more details.

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What is AI (Artificial Intelligence)? Examples of problem-solving by industry and business, and why it is important.

Basic knowledge, mechanisms, and examples of use! An article introducing what artificial intelligence can and cannot do.

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 understand and answer the question "What is artificial intelligence (AI)?" in detail. In this article, we will introduce the basic knowledge, mechanisms, examples of applications, and issues related to artificial intelligence (AI). 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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What is the method for developing AI with no code?

For those who want to solve their company's challenges! Introducing development case studies and a free development platform.

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 more detailed information, you can view it through the related links. If you have any questions, feel free to contact us.*

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Methods for predicting call center incoming call volume using AI and Excel.

Time series analysis using machine learning by AI (artificial intelligence)! Introducing AI utilization examples and AI implementation cases.

Call forecasting in a call center refers to predicting the volume of calls received by the center, such as inquiries from customers. 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 state where sufficient customer satisfaction can be provided by appropriately staffing the contact center. In this article, we will introduce methods for achieving call forecasting using Excel and time series analysis with machine learning powered by 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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What is data-driven management? Explanation of necessity and benefits revealed through successful examples.

A brief explanation of what data-driven management is! We will also introduce successful case studies that improved numbers.

Utilizing data in business has become a standard practice for companies today. However, there are not many companies that can effectively leverage 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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