[Contract Development] Customer Support System Construction Service Realized with Chatbots
Reduce the burden of inquiry operations! We will customize the features to build a high-precision chatbot exclusively for your company!
At Fujisoft, we build high-precision LLM (Large Language Model) and chatbot-based automated response systems to achieve highly accurate responses to all inquiries. In addition to automated responses, we also offer a wide range of services tailored to customer needs, including ID integration, extraction of information that can be used to improve services from collected data, and searching and providing services based on inquiry keywords. [This service will be built using the LINE API] Fujisoft has developed an automated response operator web application that combines OpenAI (Function Calling), AWS, and the LINE Messaging API. LINE is a widely used tool that many users are familiar with, making it easy to implement, and by using LINE, we expect users to feel comfortable reaching out with inquiries. *What is LLM (Large Language Model)?* It is a natural language processing model built using a vast amount of text data and deep learning technology, utilized in AI chat services such as ChatGPT.
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basic information
~Reasons Why LLMs Are Chosen for Chatbots~ ■Advanced Natural Language Understanding and Real-Time Responses The high language understanding capability of LLMs allows for deep analysis of user inquiries. Upon receiving a message on LINE, it quickly generates responses that take into account context and intent, enabling smooth interactions with virtually no waiting time. ■Continuous Learning and Improvement Through Data Utilization By analyzing interactions and response content with users, LLMs (Large Language Models) can continuously deepen their knowledge and enhance response accuracy. Utilizing chat history on LINE, it is possible to understand which questions are frequently asked and which responses are highly rated, allowing for constant optimization of the system. ■Detailed Customization Tailored to Business Needs Leveraging the strengths of LLMs, it is possible to build conversational systems that can handle highly specialized questions in line with the requirements of businesses and organizations. By combining this with LINE's dialogue flow, it can provide immediate responses and guidance tailored to specific fields, contributing to improved user satisfaction.
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Applications/Examples of results
【Examples of System Features】 1. Automation of Frequently Asked Questions and Customer Support Responses The system automatically responds to inquiries entered by users via LINE, providing information instantly 24/7. It can also automate responses regarding software usage and troubleshooting, achieving automation of customer support answers. By automating this process, human errors in customer support can be prevented, reducing the burden on operators and labor costs. 2. Service Search and Provision Based on Inquiry Words The LLM analyzes words input by users and displays a list of related information on LINE, allowing users to make reservations directly through LINE. Service providers can directly capture user interests, obtaining data that enables efficient promotion. 3. Analysis and Linking of Customer Information By linking LINE_ID with system ID, user information and purchase history can be associated, allowing for one-click orders or inquiries from buttons on LINE.
Company information
Fujisoft has a history of 40 years in embedded development since its founding, accumulating various experiences in both software and hardware. Based on the experience cultivated over many years, a team of over 2,000 embedded technology experts provides embedded services across a wide range of fields, including automotive, medical, industrial, and home appliances. Our seamless development system, covering everything from hardware to software, allows our consultants to propose solutions starting from the "soft phase," such as requirements specification, and we offer a consistent solution that encompasses development, research, testing, and production.
