Abstract:
Amid the shift toward automation in customer service through artificial intelligence (AI), this research study explores the practical integration of OpenAI Realtime API using the GPT-4o-mini-realtime-preview-2024-12-17 model into an AI-powered call center tailored for the local automotive webshop. Based on OpenAI's documentation, this study investigates the cost structure, technical implementation, and integration techniques of a ChatGPT language model through ChatGPT Realtime API, a streaming API suitable for real-time interactions with token-by-token response and low latency within a PHP-based environment. The study aimed to develop a scalable, multi-lingual AI-powered call center prototype leveraging WebRTC and PHP to deliver online, i.e., text-based, and phone, i.e., speech-based, customer assistance. The system employs WebRTC for real-time speech and text communication, while PHP facilitates seamless interaction with existing databases and backend systems. The prototype focuses on system integration, real-time data processing, and efficient API connectivity to improve automation in the context of online auto parts retail. The resulting prototype represents a cost-effective alternative to traditional call centers, offering faster response times, reduced operational expenses in terms of staffing expenses, and improved customer experience.
CITATION:
IEEE format
P. Dakić, T. Heričko, . Kljajić, V. Todorović, “The Economics of AI-Powered Call Center Development Using Chatgpt for the Needs of an Automotive Retail Business,” in Sinteza 2025 - International Scientific Conference on Information Technology, Computer Science, and Data Science, Belgrade, Singidunum University, Serbia, 2025, pp. 382-388. doi:10.15308/Sinteza-2025-382-388
APA format
Dakić, P., Heričko, T., Kljajić, ., Todorović, V. (2025). The Economics of AI-Powered Call Center Development Using Chatgpt for the Needs of an Automotive Retail Business. Paper presented at Sinteza 2025 - International Scientific Conference on Information Technology, Computer Science, and Data Science. doi:10.15308/Sinteza-2025-382-388