Call Center System
Context & Pain points
Alongside online ticket sales, the client wanted a telephone booking service. Keeping staff continuously available to answer calls and assist customers, however, required significant staffing and operating costs.
Client Objective
Build an AI-powered call center that understands and responds to callers, reduces staffing costs and can scale as demand grows.
Solution
• We used speech-processing technologies to analyze spoken input and convert it into text for natural language processing.
• AI then analyzed the results and consulted system data to generate responses for callers.
• We automated the recording and processing of the analyzed data.
Challenge
The team needed to thoroughly assess the latency, accuracy and stability of new voice and AI technologies before putting them into production.
How We Solved It
• We created a dedicated test environment and ran repeated tests using realistic call scenarios.
• After integration, we continued monitoring and optimizing the system.
Scope
- Solution proposal
- Offshore development
- Design
- High-level design
- Implementation
- Unit testing
- Integration testing
- Bug fixes
- Release deployment
System Features
- Solution proposal
- Offshore development
- Design
- High-level design
- Implementation
- Unit testing
- Integration testing
- Bug fixes
- Release deployment
Outcome
• The system was deployed safely and on schedule, with operational incidents kept to a minimum.
• The new technologies improved efficiency and scalability and provided a foundation for future features.
Testimonials
Hear from the clients who have worked with Fenix throughout their projects.
Our Work
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