How an AI Interview Copilot Works

The Audio Pipeline

The process begins with capturing real-time audio locally in the browser. Using the Web Audio API, the AI interview copilot taps into the system audio stream to listen to the interviewer/meeting audio. This stream is then processed via a WebSocket connection to a transcription service (like Deepgram or OpenAI Whisper) which converts speech to text with sub-second latency.

Contextual Processing

Once the text is available, it is fed into an inference engine. This is where the "copilot" logic resides. The system analyzes the transcribed text to identify:

• Intent: Is this a technical question, or a job tracking event?
• Keywords: Specific technologies (e.g., "React useEffect", "Database Sharding") are highlighted.
• Relevance: The system checks your pre-loaded resume context to see if you have relevant experience matching the query.

LLM Response Generation

The final step involves querying a Large Language Model. The system constructs a prompt containing the interviewer's question, your resume context, and specific constraints (e.g., "Answer using the STAR method"). The LLM then streams a structured response back to the UI.

Related Technology

For a practical application of this technology, explore our AI Interview Copilot page.