Revolutionized Live and Voicemail Classification
**Introduction:** The telecommunications industry requires prompt and efficient customer service. Traditionally, distinguishing between live calls and voicemails necessitated human intervention, which was time-consuming and prone to errors. A telecom company reached out to Apptware to automate this differentiation, leading to cost reductions and less manual work.
**Challenge:** The client faced difficulties in manually distinguishing live calls from voicemails, resulting in prolonged wait times and reduced efficiency. With millions of recordings, the current methods fell short. They needed a real-time, precise solution that did not rely on human input. Apptware's cloud-based platform was implemented to address this issue, enabling the AI model to concurrently process millions of recordings with minimal delay.
**Solution:** Apptware utilized advanced deep learning techniques, specifically CNN and VGG-16, to classify live calls and voicemails. The AI model was trained using the client's recordings, allowing for rapid sorting and routing of calls to the appropriate department in real-time. The solution integrates seamlessly with the client's existing phone system and features an intuitive dashboard for real-time insights and performance metrics.
**Results:** Apptware's AI solution successfully automated the sorting of live calls and voicemails, reducing manual labor for agents and decreasing customer wait times. This improved the efficiency of the customer service team and resulted in a savings of $50,000 monthly in labor costs, greatly enhancing profitability. The AI model achieved an accuracy rate of over 95%, surpassing expectations. Real-time tracking of call volumes, classification accuracy, and wait times demonstrated the solution's capability to manage millions of recordings simultaneously, impressing the client.