AI Operator
An AI-driven call handling system that understands intent and escalates only when it has to.
Industry
Telecommunications & Automation
Scope of work
Applied AI & Backend
Duration
a year
Challange
Most call automation doesn't understand callers. It just filters them.
High call volumes overwhelm human operators fast — and existing automation either blocks callers entirely or routes them blindly without understanding what they actually need.
Goal
Build something that handles calls intelligently, not just efficiently.
Design a modular AI system that understands natural speech, responds in real time, resolves what it can autonomously, and hands off to a human operator with full context — not a raw audio feed.
Solution
Augmentation, not replacement. The system makes human operators faster, not redundant.
Integrated STT, NLU, and TTS into a centralized backend that tracks call state, priority, and context across every interaction. Built a live monitoring dashboard so operators can observe, intervene, and make decisions using AI-generated context rather than listening blind. Won 2nd place at ROSEF and 1st place at Simpozionul Național CONVERGENȚA RECUNOAȘTERII for both engineering depth and real-world relevance.
