How Dual-Layer AI Interview Assistance Works (Technical Deep Dive)

Technical Deep Dive: Dual-Layer AI Interview Assistance

AissenceAI's dual-layer architecture is what enables 116ms response time and truly undetectable operation. This technical article explains exactly how each layer works.

Layer 1: Audio Processing Pipeline

The first layer handles everything from raw audio to structured text:

• System Audio Capture — OS-level audio loopback captures the interviewer's voice from Zoom/Meet/Teams without any integration. Works like recording what your speakers play.
• Audio Chunking — Audio is segmented into 100ms chunks for streaming processing
• Voice Activity Detection (VAD) — Silence is filtered out to reduce processing load
• Speech-to-Text — Optimized STT engine transcribes speech with sub-50ms latency
• Speaker Diarization — Identifies who is speaking (interviewer vs candidate)

Layer 2: AI Response Generation

The second layer processes transcribed text and generates contextual answers:

• Question Detection — NLP identifies when a question is being asked vs general conversation
• Model Routing — Based on question type (coding, behavioral, system design), the optimal AI model is selected
• Context Injection — Your resume, job description, and previous answers are included in the prompt
• Streaming Inference — Answers stream token-by-token as they're generated, not waiting for full completion
• Stealth Rendering — Tokens render in the desktop overlay in real-time

Performance Breakdown

Stage	Latency
Audio capture + chunking	~10ms
Speech-to-Text	~40ms
Question detection + routing	~5ms
AI inference (first token)	~55ms
Overlay rendering	~6ms
Total (first answer token)	~116ms

Read the full performance benchmark article for methodology details.