Call center automation with AI

Client

Atlas is a technology-driven passenger transportation platform that connects independent carriers under one unified system. The company offers travelers an affordable and comfortable journey experience through streamlined booking, flexible pricing, and a user-friendly mobile app

Project Implementation

The project began with a thorough analysis of the recorded call database to pinpoint the root causes of high call center load and operational inefficiencies. The data revealed that despite having a mobile app, customers still frequently called to book tickets. This presented an opportunity to automate simple interactions, reducing call center traffic and costs.

To solve business challenges, we've developed a Proof of Concept (PoC) solution, which includes the following functions: call listening, voice to text and text to voice translation, as well as data exchange with the core back-end system. In addition, the solution offers the ability to request additional information from the client to clarify the request or transfer to the operator if necessary. All operations are performed in real-time, creating the illusion of interaction with a real person.

We replaced ChatGPT with Dialogflow for process modeling, and as a tool for extracting data from user requests, such as departure and arrival points, departure date and time, etc.. After a series of tests for speech-to-text (STT) transcription, we chose AssemblyAI because of its streaming transcription and WebSocket API. Elevenlabs was chosen as the tool for text-to-speech (TTS) conversion due to the finer voice settings compared to OpenAI.

An outbound call bot for trip confirmations is being developed to reduce overhead for drivers and operators, while a Telegram bot is being created as an alternative solution to voice-based booking.

As a result, we developed a solution with a custom flow that enables customers to book, confirm, and cancel tickets without the need for operator involvement.

Key activities