Skip to main content

AI Interview Studio

The XeCubes AI Interview Studio conducts autonomous, real-time voice and video technical interviews. The AI avatar or voice agent adapts questions dynamically based on candidate responses, probes depth of understanding, and evaluates competencies against custom grading rubrics.

Technical Workflow​

sequenceDiagram
    autonumber
    actor Candidate as Candidate Browser
    participant Gateway as WebRTC Media Gateway
    participant AI as Realtime AI Interview Engine
    participant CodeBox as XEtest Sandbox
    participant Recruiter as Recruiter Dashboard

    Candidate->>Gateway: Connect WebRTC (Audio / Video / Screen)
    Gateway->>AI: Stream PCM Audio & Video Frames
    AI->>Candidate: Synthesized Voice Question (TTS, sub-350ms latency)
    Candidate->>Gateway: Candidate Answers Audio & Code
    Candidate->>CodeBox: Execute Code Snippet
    CodeBox-->>AI: Unit Test Results & Execution Output
    AI->>AI: Analyze Logic, Fluency & Problem-Solving
    AI->>Candidate: Dynamic Follow-up Question
    Candidate->>Gateway: Session Completed
    AI->>Recruiter: Dispatches Scored Transcript & Video Highlights

Key Capabilities​

1. Ultra-Low Latency Conversational Engine​

  • Powered by WebSocket-based real-time audio streaming.
  • Total turnaround latency (Speech-to-Text → Reasoning LLM → Text-to-Speech) is maintained under 350ms, ensuring a natural human-like dialogue without awkward pauses.
  • Intelligent interruption handling: candidates can interrupt the AI naturally to ask clarifying questions about constraints or requirements.

2. Adaptive Technical Questioning​

  • Rather than reciting static questionnaires, the AI agent follows a competency graph:
    • If a candidate effortlessly answers a distributed caching question with Redis, the AI naturally raises the difficulty: "How would you handle cache stampedes across a multi-cluster deployment?"
    • If a candidate struggles, the AI offers subtle scaffolding hints to gauge coachability and problem-solving resilience.

3. Integrated Live Coding Sandbox​

  • Built-in Monaco editor supporting 20+ programming languages (Python, TypeScript, Go, Java, C++, Rust, SQL).
  • Candidates run code in real-time within isolated WebAssembly / Docker micro-sandboxes.
  • The AI evaluates algorithmic complexity, code readability, test coverage, and edge-case handling.

4. Integrity & Proctoring Telemetry​

  • Multiple Face Detection: Flags if an unverified secondary person enters the frame.
  • Tab & Window Blur Logging: Logs every instance the candidate switches focus away from the assessment window.
  • Audio Anomaly Detection: Distinguishes between ambient noise and unauthorized background whisper prompting.
  • Copy-Paste Monitoring: Tracks large clipboard paste operations into code editors.

Candidate Scorecard Output​

At the conclusion of each interview, an AI assessment dossier is generated:

  • Holistic Score: Weighted average (0–100%) calibrated to role seniority.
  • Competency Heatmap: Breakdown across System Design, Algorithmic Problem Solving, Communication, and Debugging.
  • Full Verbatim Transcript: Searchable text linked directly to time-stamped video replay clips.
  • Actionable Recommendation: Clear hire/no-hire justification with highlighted strengths and identified flags.