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This document is an introductory material that thoroughly explains the types and roles of AI agents, as well as the benefits of their implementation. It includes a wealth of information on the differences between AI agents and generative AI, the characteristics of AI agents, and advantages such as addressing labor shortages, managing complex tasks, and reducing costs. Additionally, it presents an overview of AI agents, step-by-step procedures, and effective implementation approaches tailored to different company sizes, including large corporations and small businesses. Feel free to download it if you are interested. [Contents (partial)] ■ What is an AI agent ■ Characteristics of AI agents ■ Types and roles of AI agents ■ Benefits of implementing AI agents ■ Overview of AI agents and step-by-step procedures *For more details, please download the PDF or feel free to contact us.

This document introduces case studies of AI agent implementation in the medical and healthcare industry. It includes examples of using conversational AI agents for patient interaction, remote medical support, and patient management, as well as achievements in immediate response during emergencies. Additionally, case studies from the manufacturing, logistics, finance, and retail industries are also presented. If you are interested, please feel free to download it. [Contents (partial)] ■ What is an AI agent ■ Features of AI agents ■ Types and roles of AI agents ■ Benefits of implementing AI agents ■ Overview of AI agents and step-by-step procedures *For more details, please download the PDF or feel free to contact us.

This document introduces examples of AI agent implementation in the retail industry. It includes use cases such as visualizing customer movement through in-store camera data to improve product placement and display methods, as well as achievements like increasing inventory turnover rates. Additionally, we also present implementation examples from the manufacturing, logistics, finance, and healthcare industries. If you are interested, please feel free to download it. [Contents (partial)] ■ What is an AI agent ■ Features of AI agents ■ Types and roles of AI agents ■ Benefits of implementing AI agents ■ Overview of AI agents and step-by-step procedures *For more details, please download the PDF or feel free to contact us.

This document introduces examples of AI agent implementation in the financial industry. It covers use cases such as investment decision support that combines news, social media, and market data, as well as improvements in risk management quality and advancements in investment decision-making and customer response. Additionally, examples from the manufacturing, logistics, retail, and healthcare industries are also presented. If you are interested, please feel free to download it. 【Contents (partial)】 ■ What is an AI agent ■ Features of AI agents ■ Types and roles of AI agents ■ Benefits of implementing AI agents ■ Overview of AI agents and step-by-step procedures *For more details, please download the PDF or feel free to contact us.

This document introduces case studies of AI agent implementation in the logistics industry. It presents various use cases such as monitoring traffic and weather to optimize delivery routes in real-time, improving picking efficiency, and reducing labor burdens. Additionally, case studies from the manufacturing, finance, retail, and healthcare industries are also included. If you are interested, please feel free to download it. 【Contents (partial)】 ■ What is an AI agent ■ Features of AI agents ■ Types and roles of AI agents ■ Benefits of implementing AI agents ■ Overview of AI agents and step-by-step procedures *For more details, please download the PDF or feel free to contact us.

This document introduces examples of AI agent implementation in the manufacturing industry. It showcases use cases such as real-time data acquisition and analysis from the field, autonomous responses for early detection and resolution of anomalies, and consistent decision-making and actions without waiting for human instructions. Additionally, examples from the logistics, finance, retail, and healthcare industries are also presented. Feel free to download it if you are interested. [Contents (partial)] ■ What is an AI agent ■ Features of AI agents ■ Types and roles of AI agents ■ Benefits of implementing AI agents ■ Overview of AI agents and step-by-step procedures *For more details, please download the PDF or feel free to contact us.

This document summarizes the challenges and solutions related to the implementation of AI agents. If there are issues with the variability in response quality, we present numerous challenges and solutions, such as monitoring, regular updates, and the selection of training data. Additionally, we introduce case studies of AI agent implementations and effective implementation approaches based on company size. If you are interested, please feel free to download it. [Contents (partial)] ■ What is an AI agent ■ Features of AI agents ■ Types and roles of AI agents ■ Benefits of implementing AI agents ■ Overview of AI agents and step-by-step procedures *For more details, please download the PDF or feel free to contact us.

This document introduces effective implementation approaches for AI agents based on company size. For large enterprises, it aims for a phased company-wide rollout by a specialized team, while for medium-sized companies, it suggests a gradual implementation in collaboration with external partners, providing a wealth of information. Additionally, it includes various information such as the features, types, and roles of AI agents, as well as the benefits of implementation. If you are interested, please feel free to download it. [Contents (partial)] ■ What is an AI agent ■ Features of AI agents ■ Types and roles of AI agents ■ Benefits of implementing AI agents ■ Overview of AI agents and phased procedures *For more details, please download the PDF or feel free to contact us.

This document provides a thorough explanation of the procedures for introducing and operating AI agents. We present a wealth of information, starting with the introduction procedures such as understanding business processes, setting goals and KPIs, and collaborating with stakeholders, as well as the implementation of pilot introductions, effectiveness verification, feedback, and the planning for full-scale implementation. Additionally, we introduce effective introduction approaches based on company size, as well as the types and roles of AI agents. If you are interested, please feel free to download it. [Contents (partial)] ■ What is an AI agent ■ Features of AI agents ■ Types and roles of AI agents ■ Benefits of introducing AI agents ■ Overview of AI agents and step-by-step procedures *For more details, please download the PDF or feel free to contact us.

This document summarizes the benefits of introducing AI agents. We present numerous advantages, including cost reduction, improved operational efficiency and productivity, enhanced decision-making and actions based on information, and addressing labor shortages and complex responses. Additionally, we provide case studies of AI agent implementation and effective approaches for introduction. If you are interested, please feel free to download it. [Contents (partial)] ■ What is an AI agent ■ Features of AI agents ■ Types and roles of AI agents ■ Benefits of introducing AI agents ■ Overview of AI agents and step-by-step procedures *For more details, please download the PDF or feel free to contact us.

This document summarizes and introduces the types and roles of AI agents. It includes a wealth of information on simple reflex-type agents that can be used for customer support and routine tasks, as well as model-based reflex-type agents used for inventory management and autonomous driving. Additionally, it discusses the benefits of implementing AI agents, the overall picture and step-by-step procedures, as well as the challenges and solutions related to the introduction of AI agents. If you are interested, please feel free to download it. [Contents (partial)] ■ What is an AI agent ■ Features of AI agents ■ Types and roles of AI agents ■ Benefits of implementing AI agents ■ Overall picture and step-by-step procedures for AI agents *For more details, please download the PDF or feel free to contact us.

This document summarizes the features of AI agents. AI agents are capable of making autonomous decisions based on the situation and environment, managing tasks and priorities, and even self-managing resource allocation. They also possess continuous learning abilities aimed at improving performance while adapting to their environment, among many other features. Additionally, we provide explanations of what AI agents are, their types and roles, the benefits of implementing them, as well as an overview and step-by-step procedures related to AI agents. If you are interested, please feel free to download it. [Contents (partial)] ■ What is an AI agent ■ Features of AI agents ■ Types and roles of AI agents ■ Benefits of implementing AI agents ■ Overview and step-by-step procedures for AI agents *For more details, please download the PDF or feel free to contact us.

This document provides a detailed explanation of AI agents. It includes a comparison table of the differences between AI agents and generative AI, as well as a wealth of information such as the adoption rates of AI agents. Additionally, we also introduce the features, types, roles of AI agents, and the benefits of implementing them, so feel free to download it if you are interested. 【Contents (partial)】 ■ What is an AI agent ■ Features of AI agents ■ Types and roles of AI agents ■ Benefits of implementing AI agents ■ Overview of AI agents and step-by-step procedures *For more details, please download the PDF or feel free to contact us.

AIsmiley released the "AI Agent Chaos Map 2025" on Monday, February 17, 2025. A total of 51 services are included. "AI Agents" refer to AI technologies capable of handling a wide range of tasks. They not only utilize advanced natural language processing through LLMs (large language models) but also enable problem-solving and interactions with external entities. AI agents possess the ability to make independent decisions and judgments, evolving through dialogue, making them a step ahead of generative AI. They are gaining attention in various fields as a means to maximize the effectiveness of generative AI, and their usage is expected to expand even further in many scenarios in the future. *For detailed content of the article, please refer to the related link. For more information, feel free to download the PDF or contact us.*

The company AIsmiley, which operates one of Japan's largest AI portal media platforms, has released the "Generative AI Chaos Map for Domestic Services" on November 13, 2023, as part of its initiative to promote the use of generative AI services, including ChatGPT. The map features a total of 258 products. This chaos map categorizes and maps generative AI services into 11 categories, including "Chatbots," "Customer," "Marketing," "Search Systems," "Image Generation," and "Music Generation." A list (Excel) of the service URLs and vendors referenced during the creation of the map will be provided free of charge to representatives of companies considering the implementation of generative AI services after requesting the chaos map materials. *For more detailed information, you can view it through the related links. For further details, please download the PDF or feel free to contact us.*

AIsmiley will release the "Generative AI Sales Support Chaos Map - Latest Edition -" on October 3, 2024, which compiles tools such as document creation AI and role-play AI to streamline sales activities. A total of 70 services will be listed. The "Generative AI Sales Support Chaos Map - Latest Edition -" is a document created by AIsmiley after a major overhaul in about three years, summarizing generative AI services that enhance corporate sales activities. It supports sales teams by automating document creation, meeting minutes, and inquiries, allowing them to focus on interactions with customers. *For more details, you can view the article through the related links. For more information, please download the PDF or feel free to contact us.*

AIsmiley published the "Data Analysis and Mathematical Optimization AI Chaos Map" on February 7, 2025 (Friday). A total of 46 services are included. With the advancement of AI and the sophistication of data analysis technologies, the utilization of data by companies has become essential. However, simply accumulating data does not generate value. What becomes important is to leverage AI and data analysis, and to incorporate methods of mathematical optimization. *For detailed information, you can view it through the related links. For more details, please download the PDF or feel free to contact us.

AIsmiley Co., Ltd., which operates the AI portal media "AIsmiley," has released the "AI Chaos Map for Manufacturing Industry 2025," which organizes trends in the use of AI in the manufacturing sector, on May 7, 2025. The total number of products listed is 110. With the evolution of AI technology, solutions to on-site challenges in the manufacturing industry are beginning to change significantly. Technological inheritance due to labor shortages and the retirement of skilled workers, prevention of equipment troubles, and ensuring stable quality are challenges that have entered the practical phase with the use of generative AI, robotics, anomaly detection, and image recognition. *For more details, you can view the article through the related link. For further information, please feel free to download the PDF or contact us.

AIsmiley Co., Ltd., which operates the AI portal media "AIsmiley," has organized an advanced service for utilizing AI in sales and back-office operations in Japan and published the "AI Utilization Chaos Map for Sales and Back Office" on May 30, 2025. A total of 84 products are listed. With the advancement of AI technology, the efficiency and sophistication of sales and back-office operations are rapidly progressing. Automation of personalized tasks and routine work, utilization of knowledge, and optimization of communication both internally and externally have reached practical stages with the advent of generative AI and AI agents. *For more detailed information, please refer to the related links. For further inquiries, feel free to download the PDF or contact us directly.*

Aismiley Co., Ltd., which operates the AI portal media "AIsmiley," has released the "Regional AI Implementation Case Chaos Map" on June 4, 2025, which allows for an overview of the trends in AI adoption accelerating across municipalities and companies nationwide by region. The number of AI implementation cases is a total of 71. We conducted a survey of actual AI implementation cases from Hokkaido to Kyushu and Okinawa at the prefectural level. This document, organized by implementation location, purpose of use, and AI category, is structured to allow for a quick understanding of the differences and trends in initiatives by region. *For more detailed information, you can view it through the related links. For more details, please download the PDF or feel free to contact us.

The company Aismiley, which operates the AI portal media "AIsmiley," has released the "Marketing Support AI Service Chaos Map," which organizes trends in the use of AI in marketing operations, on July 23, 2025. The total number of listed products is 118. As 2025 is said to be the year of AI agents, the evolution of generative AI and the emergence of AI agents are rapidly expanding the use of AI in marketing practices. Support is now possible across the entire spectrum of marketing activities, not only limited to traditional data analysis and advertising optimization but also including content generation, customer engagement, campaign design, and demand forecasting. *For more detailed information, you can view it through the related links. For more details, please download the PDF or feel free to contact us.

Ice Miley has published a "Comparison Chaos Map of On-Premises AI vs. Cloud AI," which organizes advanced AI service forms in AI implementation, on September 16, 2025. The total number of listed products is 63. When considering the introduction of AI, many companies struggle with the choice of "whether to go with cloud-based or on-premises." Both options have their features, and it is important to choose the form that is suitable for the company's situation and objectives. *For more detailed information, you can view it through the related link. For more details, please download the PDF or feel free to contact us.*

The company Aismiley, which operates the AI portal media "AIsmiley," has released the "RAG Solution Chaos Map," which summarizes advanced RAG solution services that can be utilized across a wide range of industries, on October 8, 2025. A total of 84 products are listed. RAG refers to a mechanism that combines generative AI with external databases to produce accurate and reliable answers and analysis results. In recent years, the introduction of RAG has been advancing in various business areas such as knowledge management, internal inquiry response, sales support, and technical document search, significantly contributing to improved operational efficiency and enhanced decision-making. *For more details, you can view the article through the related link. For more information, please download the PDF or feel free to contact us.*

The "Generative AI Chatbot Chaos Map" is a document that summarizes the latest generative AI chatbots covering everything from internal use to customer support. As the utilization of generative AI rapidly expands, the introduction of generative AI chatbots that support companies in improving operational efficiency and enhancing customer experience is progressing quickly. This chaos map includes the latest chatbots that can be widely used, from streamlining internal operations to optimizing customer touchpoints. It is structured to make it easier to find the most suitable solutions based on use cases and objectives. In addition to the chaos map, we also provide a list of AI service providers (Excel) free of charge, so feel free to download it if you are interested. *You can view the detailed content of the article through the related links. For more information, please download the PDF or feel free to contact us.*

We would like to introduce examples of utilizing generative AI aimed at supporting operations in the sales department. Specific applications include the automatic creation of sales materials to be submitted to clients and PowerPoint presentations used in negotiations, as well as automatic replies to customer emails and automatic summarization of email content. AI also gathers and analyzes customer data, helping sales teams approach efficiently, making follow-ups more effective. 【Applications】 ■ Automatically create sales materials to be submitted to clients and PowerPoint presentations for negotiations ■ Create minutes for sales meetings ■ Automatically reply to customer emails and summarize email content ■ Create sales lists and check progress ■ Propose high-priority tasks and support negotiations using AI *For more details, please download the PDF or feel free to contact us.

We would like to introduce a case study on the use of generative AI aimed at strengthening customer follow-up in the sales department. By utilizing AI, it becomes possible to prioritize customer follow-ups, analyze inquiries from customers, and automatically formulate response schedules. AI collects and analyzes customer data, allowing sales teams to efficiently plan their approaches, making after-sales follow-up more efficient as well. 【Utilization Details】 ■ Prioritization of customer follow-ups using AI ■ Analysis of customer inquiries and automatic formulation of response schedules ■ Automatic detection and alerting of customers with missed follow-ups ■ Proposing accurate follow-up strategies based on data *For more details, please download the PDF or feel free to contact us.

We would like to introduce examples of utilizing generative AI in the current state of the marketing department and data analysis. By leveraging AI, the aggregation and analysis of information become easier, and it is possible to support the utilization of collected information and the progression of measures derived from the analysis. Specific applications include the automation of regular report generation, which achieves efficiency in KPI monitoring, as well as the automatic detection of anomalies and outliers, providing alert notifications and analysis of their causes. 【Utilization Details】 ■ Ask questions about large amounts of internal data (sales, inventory, customer information, etc.) in natural language and obtain analysis results instantly. ■ Analyze multiple data sources transversely to automatically detect correlations and hidden patterns. ■ Achieve efficiency in KPI monitoring through the automation of regular report generation. ■ Automatically detect anomalies and outliers, providing alert notifications and analysis of their causes. ■ Collect and analyze publicly available information from competitors and social media data to understand market trends. *For more details, please download the PDF or feel free to contact us.

Here are examples of utilizing generative AI in the marketing department. By leveraging AI, it is possible to learn from past campaign data and predict the success rate of new marketing initiatives. Additionally, there are successful cases where AI talents were used in TV commercials and package designs created with generative AI, which enhanced product appeal and brand value. [Utilization Details] ■ Learning from past campaign data to predict the success rate of new marketing initiatives ■ Automatically generating campaign content optimized for each target customer segment ■ Automating everything from A/B test design to execution and result analysis, speeding up the PDCA cycle ■ Integrated campaign management across multiple channels (Web, email, SNS, etc.) ■ Measuring campaign effectiveness in real-time and automatically optimizing delivery content and budget allocation *For more details, please download the PDF or feel free to contact us.

We would like to introduce examples of utilizing generative AI aimed at promoting operations in the Human Resources and General Affairs departments. AI can assist in document review and support the creation of documents such as job postings and internal regulations. Specific applications include the automatic creation of updates to internal regulations in response to legal amendments, as well as analyzing applicants' responses to automatically generate suitability scores and reports. 【Utilization Details】 ■ AI automatically generates job postings and internal regulations, optimizing the text. ■ Creates appropriate job postings based on job requirements, learning from past successful cases to improve. ■ Automatically creates update proposals for internal regulations in response to legal amendments. ■ Reduces workload by 60% through automatic aggregation of interview evaluations. ■ Analyzes applicants' responses to automatically generate suitability scores and reports. ■ Provides 24/7 support for scheduling interviews according to applicants' availability. *For more details, please download the PDF or feel free to contact us.

We would like to introduce a case where generative AI has been utilized to enable automated responses in the Human Resources and General Affairs department. In addition to automating processes such as expense reimbursement, attendance management, and equipment requests through an internal chatbot, it also streamlines cross-departmental information searches, reduces the investigation time for responsible personnel, and provides automated responses to FAQs and inquiries from within the company using AI. There are various ways to utilize this technology. If you are interested, please feel free to contact us. 【Utilization Details】 ■ Automating processes such as expense reimbursement, attendance management, and equipment requests with an internal chatbot ■ Streamlining cross-departmental information searches and reducing investigation time for responsible personnel ■ AI providing automated responses to FAQs and inquiries from within the company ■ Learning from past inquiry history to provide appropriate answers instantly ■ Automatically generating standard operating procedures in a tutorial format ■ Providing clear explanations and level adjustments according to the user's proficiency *For more details, please download the PDF or feel free to contact us.

We would like to introduce examples of utilizing generative AI aimed at breaking away from person-dependent tasks in the Human Resources and General Affairs department. Specific applications include delegating internal inquiry responses and standardizing inquiry processing, organizing internal regulations and procedures, and centralizing scattered information. Additionally, by building a system that accumulates manuals for the logistics management system and allows a chatbot to respond, we have been able to reduce training time and on-site burdens, as well as decrease person-dependent responses. 【Utilization Details】 ■ AI delegates internal inquiry responses and standardizes inquiry processing ■ Learns the response know-how of veteran employees and deploys it company-wide ■ Supports inquiries from overseas locations through multilingual capabilities ■ AI automatically detects updates to regulations and always reflects the latest status ■ Visualizing and standardizing business processes eliminates dependency on specific employees ■ Optimizing business flows with AI prevents risks of person-dependency and business stagnation *For more details, please download the PDF or feel free to contact us.

We will introduce specific use cases of generative AI in the accounting and finance departments. AI performs accounting tasks on behalf of humans. A significant feature is the elimination of input hassle and errors. It can be utilized for automating routine tasks such as attendance and expense reimbursement, promoting paperless operations through automatic digitization of receipts and invoices, and automating data linkage and reconciliation tasks across multiple systems. [Utilization Details] ■ Reading invoices and receipts with AI-OCR and automatically converting them into journal entry data ■ AI automatically processing routine tasks such as attendance and expense reimbursement ■ Promoting paperless operations through automatic digitization of receipts and invoices ■ Automating data linkage and reconciliation tasks across multiple systems ■ Learning from past journal entry patterns and automatically suggesting appropriate journal entries *For more details, please download the PDF or feel free to contact us.

Here is an example of utilizing generative AI for financial data analysis in the accounting and finance department. It can automatically calculate management indicators from P/L, B/S, and C/F, generate dashboards, discover areas for improvement from financial data, and automatically propose specific measures. AI performs accounting tasks on behalf of humans. Not only does it eliminate the hassle and errors of data entry, but it can also analyze all accumulated data, making it easy to create financial status reports from daily operational data. [Utilization Details] ■ Automatically calculates management indicators from P/L, B/S, and C/F, and generates dashboards ■ Detects anomalies from historical data and automates alert notifications ■ Visualizes the company's position through financial comparison analysis with industry peers ■ Monitors accounts receivable delays and abnormal inventory increases in real-time ■ Discovers areas for improvement from financial data and automatically proposes specific measures ■ Streamlines investment decisions and prioritization of measures through ROI simulation *For more details, please download the PDF or feel free to contact us.

Here are examples of utilizing generative AI in customer support. By leveraging AI, we can reduce the costs of responding to foreign customers through multilingual support. Additionally, automating frequently asked inquiries significantly cuts down on operator workload, enabling a reduction in human resource costs. There are successful cases where initial responses were automated using voice bots, completing about 80% of inquiries through the bot and achieving a response rate of over 90%. 【Utilization Details】 ■ Achieving 24/7 support through AI-driven automated responses, reducing labor costs ■ Lowering the costs of responding to foreign customers through multilingual support ■ Automating frequently asked inquiries, significantly reducing operator workload ■ Streamlining the process by escalating only complex inquiries to humans *For more details, please download the PDF or feel free to contact us.

Here are examples of utilizing generative AI aimed at improving operational efficiency in customer support. Specifically, it can be used for automating and streamlining After Call Work (ACW) in call centers, delegating the input of interaction details, and automating routine tasks. By significantly reducing ACW in call centers, operational efficiency can be improved, and trouble response manuals can be created based on accumulated information. 【Utilization Details】 ■ Automate and streamline After Call Work (ACW) in call centers ■ AI takes over the input of interaction details, reducing the burden on operators ■ Utilize accumulated information in AI to enhance the speed and accuracy of customer interactions ■ Automate routine tasks to concentrate resources on more complex operations *For more details, please download the PDF or feel free to contact us.

Here is a case of utilizing generative AI for creating customer support manuals. By leveraging AI, we can automatically generate troubleshooting guides based on the data accumulated in customer support. It is possible to efficiently update troubleshooting manuals by organizing past customer interaction histories. Additionally, there are successful examples where municipalities have implemented FAQ systems utilizing vast amounts of data, resulting in improved user satisfaction and response efficiency, as well as reduced workload for staff. [Utilization Details] - Automatically generate troubleshooting guides based on data accumulated in customer support. - Efficiently update troubleshooting manuals by organizing past customer interaction histories. - Automatically generate standardized manuals that can be used for training new operators. - Formalize tacit knowledge and make it shareable across the organization. *For more details, please download the PDF or feel free to contact us.

This is an introduction to a case where generative AI is utilized for legal compliance checks in the research and development department. The applications include automatic checks of information related to laws and patents, as well as verifying whether expressions within documents comply with laws and regulations. AI can also be used for summarizing texts and checking content against relevant regulations. 【Applications】 ■ Automatic checks of information related to laws and patents ■ Verification of whether expressions within documents comply with laws and regulations ■ Early detection of risks by referencing the latest relevant regulations and industry rules ■ Support for confirming intellectual property rights and ensuring compliance in research and development *For more details, please download the PDF or feel free to contact us.

Here are some examples of how generative AI is utilized in the research and development department. AI is also used for summarizing texts and checking content against relevant regulations. As a result, it can transform long texts containing specialized terminology into a format that can be understood in a short time, and it can be combined with translation to efficiently grasp the content of foreign language papers. 【Utilization Details】 ■ AI automatically summarizes research papers and foreign specialized literature ■ Transforms long texts containing specialized terminology into an understandable format in a short time ■ Combined with translation to efficiently grasp the content of foreign language papers ■ Automatically generates summaries optimized for reports and presentations *For more details, please download the PDF or feel free to contact us.

We will introduce examples of utilizing generative AI aimed at supporting SE in the research and development department. It is possible to automate routine tasks such as automatic generation of programming code and scripts for test code. We provide an environment where beginners and non-engineers can develop prototypes. Additionally, we have successfully established a system development method incorporating generative AI that reduces development man-hours by approximately 70% compared to traditional methods. 【Utilization Details】 ■ AI automatically generates programming code, reducing development man-hours ■ Automation of routine tasks such as scripts for test code ■ Reduces the workload of engineers, allowing them to focus on upstream processes and advanced design ■ Provides an environment where beginners and non-engineers can develop prototypes *For more details, please download the PDF or feel free to contact us.

To successfully implement AI company-wide without limiting to specific departments or job types, there are some key points to consider. During implementation, it is important to take existing systems and costs into account. It is necessary to think about how to ensure smooth utilization of AI. Additionally, since there are certain risks associated with usage, it is essential to thoroughly check whether AI utilization could lead to information leaks or whether it poses any legal or logical risks. Furthermore, implementing AI is not the end of the process. There needs to be a common understanding among all employees about its use throughout the business, and they must be able to effectively utilize it. Continuous support after implementation is crucial for successful AI utilization. **Three Key Points for Successful AI Utilization** - Consider existing systems and costs during implementation - Aim for operations that address risks - Provide ongoing support until users are proficient *For more details, please download the PDF or feel free to contact us.*

This document introduces hints and ways to utilize generative AI to transform operations across all industries and job roles. Starting with examples of utilization and success stories aimed at supporting the sales department, we have included 15 specific use cases categorized by department, such as marketing, human resources and general affairs, and accounting and finance. Please feel free to use this as a reference for your company's implementation. [Contents] ■ Introduction / Background ■ [By Department] Specific Use Cases / Success Stories ■ Three Key Points for Successful AI Utilization ■ Introduction to AIsmiley / Service Overview *For more details, please download the PDF or feel free to contact us.

A chatbot is a coined term that combines "chat" (conversation) and "robot," referring to a program that automatically engages in dialogue with users. Traditionally, its main applications were automated responses to standard inquiries, such as FAQ handling and customer support. However, in recent years, advancements in generative AI technology have enabled more natural and flexible conversations. With the emergence of new large-scale language models (e.g., the GPT-4 series), chatbots are increasingly capable of understanding user intent and context accurately, generating appropriate responses based on the situation, rather than being limited to fixed answers. This document aims to support companies in smoothly implementing chatbots by comparing the features, implementation costs, and ease of operation of major products, focusing on chatbot services equipped with the latest class of AI technology. *For detailed content of the document, please refer to the PDF. For more information, feel free to contact us.*

In recent years, with the evolution of generative AI and large language models, chatbots have expanded their potential beyond traditional FAQ responses and customer support to various fields such as marketing, sales, operational efficiency, and even internal communication support. In the future, chatbots are expected to become mainstream with multi-platform support and multi-modal communication that includes voice and video, increasingly attracting attention as important tools for promoting digital transformation (DX) in companies. By identifying appropriate solutions to the challenges faced by various companies and utilizing chatbots, significant improvements in customer satisfaction and operational efficiency can be anticipated. We hope that this document will assist you in formulating a suitable chatbot implementation strategy for your company, taking into account advanced market trends and technological developments, as well as addressing future business challenges. *For detailed content of the document, please refer to the PDF. For more information, feel free to contact us.

This document is a comprehensive comparison guide for Dify construction support services. "Dify" is a powerful tool that allows for the development of high-functionality AI applications through intuitive GUI-based operations. However, to fully leverage its potential and build an AI agent optimized for your company's operations, specialized knowledge and expertise are essential. We will provide a thorough explanation of the basic overview of Dify, the advantages and disadvantages of in-house development versus expert construction support services, and the service offerings, strengths, and features of the top 10 companies providing Dify construction support in Japan. We hope this will assist companies considering the use of this tool for operational efficiency in finding the right partner. [Contents (excerpt)] ■ About this document ■ What is Dify? ■ Options for Dify implementation: Comparison of in-house development and construction support services ■ Five points for choosing Dify construction support services (checklist format) ■ Companies providing Dify construction support services ■ Company overview *For more details, please download the PDF or feel free to contact us.

"Dify" is an open-source LLMOps platform that allows for the rapid development and operation of generative AI-native applications with no-code/low-code. It comprehensively provides prompt engineering, RAG, agent functionalities, and more, enabling the implementation of AI features without the need for specialized backend development. In particular, it excels in building AI agents that enable autonomous task execution by integrating external APIs and proprietary business logic as "tools" for the AI. 【Features】 ■ Intuitive GUI ■ Fast AI agent development ■ Support for a wide range of LLMs ■ Standard BaaS functionality ■ Flexibility of OSS *For more details, please download the PDF or feel free to contact us.