Automate customer support available 24/7 using natural language processing!
We would like to introduce a case study of the development of a "Customer Support Automation System" at our company. During the development, we faced challenges such as improving the flexibility in responding to ambiguous inquiries. In response to these challenges, we implemented a BERT-based natural language understanding model, incorporating self-learning capabilities from dialogue history and emotion classification logic. 【Technical Challenges】 ■ Improving flexibility in responding to ambiguous inquiries ■ Organizing FAQ data and continuous learning ■ Ensuring quality in emotion analysis and complaint handling *For more details, please download the PDF or feel free to contact us.
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basic information
**Main Achievements** - Operator workload: Reduced by 40% - First response completion rate: Achieved over 65% - Response time: Immediate answers within an average of 3 seconds - Number of cases handled: Expanded to five times compared to human support *For more details, please download the PDF or feel free to contact us.*
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For more details, please download the PDF or feel free to contact us.
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Company information
Our company acts based on a sense of "mission" as "IT professionals," focusing on the "thoughts" of each individual customer to lead them to success. We contribute to stable energy supply through energy solutions utilizing AI and IoT. Additionally, we provide services globally across our entire company group, including overseas locations. Please feel free to contact us if you have any requests.
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