Clinicians are trained to read tone, hesitation, and affect — but they're doing it from memory, mid-conversation, while taking notes. The signal that matters most often leaves no record at all.
Two clinicians can hear the same session and read the affect two different ways.
The moment passes. The note captures the words — rarely the tremor behind them.
Slow shifts between visits — the ones that matter most — are the hardest to see.
In session or via upload, Emotn AI processes the voice signal — not the words alone.
Vocal biomarkers are mapped to emotional and cognitive dimensions, each with a confidence indicator.
You get a clear, timestamped view to weigh alongside your own clinical observation.
Emotn AI surfaces signals. You make the call. Always.
Emotn AI never leans on a single signal. Three independent machine-learning models analyze the same voice in parallel — then fan in to one confidence-weighted set of findings and a clinician-ready report.
Reads the acoustics — prosody, rhythm, pitch, energy, and micro-tremor. The vocal biomarkers beneath the words.
Reads the emotional charge — the valence and affect carried in how something is said, moment to moment.
Reads the meaning — what is actually being said, in context, and how content shifts across a session.
One timestamped view — showing where the models agree, how confident each is, and the moments that drove every result. Built to sit alongside your clinical judgement, never to replace it.
Catch affective shifts you can revisit between sessions.
Add an objective signal to medication and treatment-response decisions.
Screen and monitor with a consistent, structured input.
Quantify affect at scale, reliably and reproducibly.
Built on peer-reviewed research in vocal biomarkers and affective computing, and benchmarked against clinician-rated standards. We publish our methods, our limitations, and our confidence bounds.
We protect it accordingly — consent-first, encrypted, and configurable to your practice's retention policy.
“It flagged a flattening in affect I'd have caught a session later.”
[Dr. Name], [Credentials] — [Practice] · replace with a real, permissioned quote
We work closely with each early practice to fit Emotn AI to real clinical settings. Tell us about your work and we'll be in touch about a pilot.