This study focuses on developing and implementing a chatbot system using the Python Flask framework to enhance customer service efficiency at PT. NG Tech Supplies. The chatbot is designed to provide fast and accurate responses to customer inquiries, leveraging artificial intelligence and natural language processing technologies. The development follows a systematic approach using the Waterfall methodology, encompassing requirements analysis, design, implementation, verification, and maintenance. Key features include seamless integration with order management and CRM systems, enabling real-time updates on product and order status. Black-box testing was conducted to evaluate system performance, demonstrating an average response time of less than 2 seconds and high accuracy in handling queries. The chatbot also supports a well-organized folder structure in cPanel, ensuring efficient management and scalability. This research highlights the chatbot's potential to automate repetitive tasks, reduce workload, and improve customer satisfaction through enhanced service delivery.
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