A live AI interviewer that reads the answer behind your answer.
Experience interviews with an intelligent AI interviewer that speaks naturally, understands your voice, and evaluates every response through the MLIM pipeline—measuring emotion, intent, communication quality, and behavioral consistency to deliver deep, actionable insights.
An animated avatar runs the session end to end — reading each question aloud, waiting on your spoken or typed answer, and reacting in real time. Your camera and microphone stay active the whole way through.
A lip-synced animated avatar reads each question through your browser's speech synthesis, mouth and gaze moving in real time.
Answer out loud. Groq Whisper Large v3 transcribes your recording live and feeds it straight into the evaluation pipeline.
Your webcam feed is read continuously across 7 emotion classes, fused alongside what you actually say.
If your answer's intent is ambiguous, the interviewer asks a targeted clarification instead of moving on blind.
“Tell me about a time you had to push back on a technical decision.”
Every spoken or typed answer in your interview passes through all four layers. ASL and PEL run first, then GSTL updates the HMM belief state, and IFL fuses everything into a final intent prediction with entropy-based uncertainty scoring.
Valence-arousal extraction, sentiment polarity classification, emotional uncertainty estimation, and affective masking detection across voice transcripts and typed responses.
From facial expression to pragmatic speech acts — the full analysis stack activates live during your session.
Select your target role and paste the job description. The Groq-powered question engine generates fresh technical, behavioral, and scenario questions for that exact role.
An animated avatar reads each question aloud through your browser's speech synthesis, with mouth movement synced to speech. Camera and microphone activate for the session.
Speak naturally into your mic or type your answer. Groq Whisper Large v3 transcribes voice in real time. Both inputs feed the identical MLIM pipeline.
ASL and PEL run first. GSTL updates the HMM goal belief state. IFL fuses every signal with your session history into a final intent label.
In Practice mode, a structured feedback card scores your answer. In Simulation mode, the interviewer stays neutral and evaluation runs after you finish.
Your session closes with a full breakdown: overall score, weak areas, recommended topics, per-question detail, and an MLIM summary — exportable as PDF.
Every session closes with an overall score, an integrity score, per-question detail, flagged weak areas, recommended topics to revisit, and a full MLIM summary — exportable as a PDF.