How StaffAgent Handles Interview Calls in Real-Time

Real-time interview processing requires sophisticated architecture to deliver natural, responsive conversations. Here's how StaffAgent makes it happen.

The Architecture

Our system combines multiple AI models and services to create seamless conversational experiences.

Speech Recognition

Advanced ASR models convert speech to text with minimal latency, handling accents and background noise effectively.

Natural Language Understanding

Context-aware NLU processes candidate responses, extracting key information and determining appropriate follow-up questions.

Dynamic Response Generation

Responses are generated based on interview context, ensuring natural conversation flow rather than rigid scripts.

Text-to-Speech

Neural TTS creates natural-sounding speech with appropriate intonation and pacing.

Latency Optimization

Through careful optimization, we achieve sub-second response times, maintaining natural conversation rhythm.

Scalability

Our cloud-native architecture scales automatically to handle thousands of concurrent interviews without degradation.

This technical foundation enables StaffAgent to deliver interview experiences that feel natural while gathering comprehensive candidate insights.