Project Fuji

Scope

A service-driven business approached us to explore how AI could improve their customer support operations. They were receiving a high volume of inbound calls, and their existing call center setup relied on outdated IVR systems (“press 1 for… press 2 for…”), which frustrated customers and slowed down response times. Our brief was to design and implement an AI-powered voice agent that could understand natural language, handle routine queries, and escalate complex cases to human agents.

Problem

Traditional call systems made it difficult for customers to quickly reach the help they needed. Agents were overloaded with repetitive enquiries, leaving less capacity for high-value conversations. Response delays risked damaging customer experience, while operational costs continued to rise. The client needed a scalable, intelligent solution that could streamline interactions and improve customer satisfaction.

Solution

We developed a proof of concept AI voice agent capable of handling natural speech queries in real time. The system was designed to:

• Answer common questions and guide customers without human intervention.

• Log support requests directly into the business’s ticketing system.

• Route complex queries to human agents with full context.

• Integrate with existing knowledge bases and CRM systems for accurate, consistent answers.

By building this on top of modern AI models and telephony infrastructure, the client gained a flexible, future-ready platform that could be expanded to new use cases beyond customer support.

Conclusion

Although still in proof of concept, the AI voice agent demonstrates the potential to reduce call handling times by ~40-60%, free human agents from repetitive tasks, and improve customer satisfaction through faster, more natural interactions. The client is now positioned to roll out AI-driven automation across their support function - modernizing the customer experience and driving operational efficiency.