The diagnostic co-pilot that shows its proof.
Auscult.ai turns the consultation into verifiable reasoning: the LLM proposes, an exact engine disposes — and the trace of that decision is the explanation.
Demo · 2 min 55
The clinical thread: chest tightness where the stakes are not missing a heart attack.
Say what is missing, then recompose the diagnostic tree.
01
The LLM proposes
It listens to the consultation — voice, text, documents — and translates it into clinical facts and rules. It never decides alone.
02
The engine disposes
An exact reasoner verifies, constrains and decides: a live ranked differential, can’t-miss alerts, the questions with the highest information gain.
03
The trace is the explanation
Every conclusion is linked to the evidence that grounds it — structured, verifiable and contestable, down to the proof tree.
“The explanation is not produced after the fact: it is the reasoning itself.”
The ReasoningLayer thesis, applied to the clinic.
- Continuously ranked differential
- Can’t-miss red-flag alerts
- Questions suggested by information gain
- Result extraction — labs, ECG
- Navigable diagnostic lattice
- Generated SOAP note