Voice is a clinical sign.
We build the infrastructure to treat it like one.

Audexia turns clinical voice into a governed, FHIR‑native artifact — protocol‑based capture, on‑device feature extraction, and a durable record of derived acoustic features.

14standardized voice tasks
FHIR R4Media · Observation · Provenance
HIPAABAA‑ready · privacy‑first
Built on the standards clinical IT trusts
FHIR R4 HL7 USCDI+ HIPAA Epic‑ready
How it works

From voice task to clinical observation, in one pipeline.

Clinicians order a task bundle. Patients complete it on a phone. Audexia extracts acoustic features on the device, destroys the raw audio, and writes a structured, longitudinal artifact back to the EHR — features only, no recordings retained.

01 / Order

Clinician selects a task bundle

Choose by condition — ALS, Parkinson's, frailty, cognitive screening, mood — or compose your own. Audexia auto‑selects evidence‑based tasks (sustained /a/, DDK pa‑ta‑ka, read‑aloud, picture description).

Order
02 / Capture

Patient completes on a phone

A QR code or text link opens a guided session. Acquisition‑time QC gates — silence, clipping, SNR, prompt adherence — accept or re‑prompt before the session ever leaves the device.

QR · SMS QC pass
03 / Observation

Features in, audio out, FHIR write‑back

Acoustic features are extracted on the patient device. The raw waveform is destroyed at the edge — only the derived feature vector reaches downstream models. Audexia does not own or host inference models. A FHIR Observation is written back to the chart. No recordings retained, by design.

Features no audio Models n vendors EHR FHIR
What we measure

Six families of acoustic features. One canonical artifact.

Audexia computes the same evidence‑based features researchers cite — grouped by speech subsystem so clinicians can interpret the score, not just the number.

F1 · Phonation Jitter · Shimmer · HNR Cycle‑to‑cycle variation in pitch and amplitude, plus harmonic‑to‑noise ratio. Sensitive to vocal fold pathology and laryngeal weakness.
F2 · Prosody F0 range · Intensity Pitch variability and loudness contour. Reduced range is a hallmark of hypokinetic dysarthria and depressed affect.
F3 · Articulation Vowel space · VOT Formant centralization and voice onset time. Quantifies articulatory undershoot — sensitive to early PD and ALS phenotypes.
F4 · Timing Rate · Pause · DDK Articulation rate, pause distribution, and diadochokinetic regularity. Robust early markers of bulbar decline.
F5 · Spectral MFCC · CPP Mel‑frequency cepstral coefficients and cepstral peak prominence. Powerful discriminators — computed on device, the only signal that leaves.
F6 · Phonetic PPG · Self‑sup. embeddings Phonetic posteriorgrams and learned representations. Content‑aligned, robust to channel and speaker variability.
F7 · Context Device · Environment Microphone metadata, ambient noise floor, distance, and clinical setting — captured alongside the feature vector for reproducibility.
F8 · Quality SNR · Clipping · Adherence Acquisition‑time QC computed before the session uploads. Re‑prompts the patient if the take won't support reliable inference. 74%
FHIR · interoperability

A canonical voice artifact your stack already understands.

Audexia represents every captured session as a FHIR Media + Observation + Provenance bundle. The canonical artifact is the feature vector — never the recording — so the science can evolve without re‑capturing patients.

  • MediaThe canonical feature vector for the session — task, codec, sample rate, and quality metadata. Raw audio is never persisted.
  • ObservationPer‑feature scores, condition‑specific composites, and confidence — all coded.
  • ProvenanceCapture device, model version, consent, and chain of custody — fully auditable.
  • DocumentReferenceOptional indexing layer for EHRs that prefer document‑oriented retrieval.
Reference architecture v1.0
Capture FHIR Feature Store FHIR Models FHIR EHR write‑back Analytics Research
Security & compliance

Security and HIPAA aren't features. They're the foundation.

Voice is biometric data. Raw audio will never be an issue — it never leaves the patient's device. Audexia is built HIPAA‑first, with privacy and compliance as core design constraints, not afterthoughts.

HIPAA · BAA

HIPAA‑first, BAA‑ready.

Audexia is designed for regulated clinical environments. We execute BAAs with covered entities and operate with HIPAA compliance as a baseline, not an option.

Audio handling

Raw audio is never an issue.

Features are extracted on the patient device. The raw waveform is destroyed before anything leaves it — Audexia never receives, transmits, or stores voice recordings.

Encryption

Encrypted in transit and at rest.

All data is encrypted in transit (TLS 1.3) and at rest (AES‑256). Feature vectors and FHIR artifacts are the only things that ever cross the wire.

Consent & provenance

Every artifact is auditable.

Per‑task consent is captured at the device. FHIR Provenance records bind capture metadata, software version, and clinician identity — every score is traceable back to its source.

Pricing · access

Designed partnerships, not seat licenses.

Audexia is in early access with a small group of design partners across neurology, geriatrics, behavioral health, and research. Pricing is per‑program — scoped to your task bundles, capture volume, and integration footprint.

Who we want to talk to

  • Researchers studying voice as a clinical biomarker
  • Neurologists, ENT specialists, geriatricians, and psychiatrists
  • Lifestyle medicine and precision health practitioners
  • Innovative health systems building voice‑enabled clinical workflows
  • Vocal biomarker startups looking for a FHIR‑native data layer