CRM with a Voice AI Assistant for a Call Center
Project Goals
- Automate call distribution and operator work time tracking.
- Implement a voice AI assistant for handling initial inquiries.
- Provide KPI analytics for call center operators.
Our Solution
Our team started with a detailed analysis of existing call center operations to identify the most common customer inquiries. Based on this, we designed the CRM architecture, integrating IP telephony for automated call routing. The core feature was the AI voice assistant, powered by speech recognition and a pre-trained NLP model. It efficiently handled routine inquiries such as order status, account balance, or service availability. If the question was too complex for AI classification, the system would escalate the call to a live operator. Additionally, we developed a real-time work tracking module that allowed supervisors to monitor operator availability and efficiency. We also created visual dashboards displaying call center KPIs, enabling the company to analyze workloads, service quality, and overall team performance.
Technologies Used
- Python, TensorFlow (AI-powered speech recognition models)
- Node.js, Express (backend logic and integrations)
- React (CRM user interface)
Results
- 30% reduction in operator workload through AI self-service
- 2x faster response times for common customer inquiries
- Advanced analytics helped optimize shift schedules and improve service quality
Project Team
- 1. AI Engineer (voice assistant development)
- 2. Backend Developer (logic and integrations)
- 3. Frontend Developer (CRM interface)
- 4. QA Engineer (functional and AI module testing)
- 5. Project Manager (client coordination)
Implementation Timeline
3 months
Project Uniqueness
We integrated a multi-language voice assistant into a call center CRM, significantly reducing customer service costs while maintaining high-quality support.
Estimated Cost
From $10,000
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