VoiceKind delivers familiar family voices to patients who can no longer communicate — after a stroke, with dementia, or in a disorder of consciousness. Families record from their phone. Care staff play at the bedside. The response is measured.
63 million family caregivers are trying to reach them. When families are not at the bedside, patients hear monitors, alarms, and strangers — not the one voice they would recognize.
The thought is intact. The words will not come. Family visits less, because visiting is painful.
Asked dozens of times a day. Answered, forgotten, asked again. The distress is new every time.
Brain imaging shows a familiar voice still activates language and memory centers. No way to respond.
VoiceKind is built on published, peer-reviewed research. Every claim below is sourced.
Family-delivered voice stimulation produced approximately five times greater improvement in consciousness scores than staff-delivered stimulation.
Familiar voice activated language, memory, and prefrontal regions on functional MRI in patients with disorders of consciousness.
Patients oriented to hearing their own name 40 percent of the time, compared with 23 percent for a neutral sound.
Misdiagnosis among patients with disorders of consciousness consistently approximates 40 percent. Standardized behavioral assessment is more sensitive than clinical consensus.
VoiceKind adds roughly ten seconds per patient to rounds that already happen.
Thirty seconds on a phone, from anywhere. A greeting, a story, ordinary news. Guidance is built in, tailored to the condition.
Encrypted transfer. It appears in the care team’s queue within seconds, flagged if the family saved it for a particular day.
One tap while checking vitals. A pillow speaker keeps it private from a roommate. The nurse is not the audience — the patient is.
A standardized response score, structured observations, and an optional note. Five seconds. This is the clinical data.
Over time, patterns emerge — which voice, which content, which time of day. Recommendations follow the data, and staff always decide.
Features are routed by diagnosis. A patient in a disorder of consciousness and a patient recovering from a stroke need almost nothing in common.
Voice cloning in healthcare raises real questions. We built the answers into the architecture rather than the terms of service.
Staff always see whether a voice is a real recording or AI-generated. There is no ambiguity at the point of care.
A documented multi-step process before any voice is cloned. One tap deletes the model and every recording made from it, permanently.
An audible cue, a spoken statement, or staff-mediated notice. The clinical oversight body selects the mode per patient.
An append-only audit trail covering consent, generation, playback, and revocation. Exportable for IRB or regulatory review.
Two advisory appointments are in progress and will be announced once confirmed.
Designed the platform architecture across nine conditions, the twelve patent-pending methods, and the AI governance framework.
Vascular neurologist with more than 130 peer-reviewed publications in stroke outcomes and machine learning in neurology. Co-designing the clinical trial.
Advising on trial methodology, outcome measures, and analysis plan for the clinical pilot and NIH SBIR application.
Advising on synthetic speech detection, on-premises inference, and the machine learning architecture behind voice recommendation.
Not yet. We are preparing a clinical pilot and building toward a production release. If you are a facility interested in participating, or a family who would like to be notified when we launch, please get in touch.
Roughly ten seconds per patient, during rounds that already happen. The nurse taps play while checking vitals and rates the response afterwards on a single scale. The design constraint was that it had to fit inside existing workflow, not alongside it.
All data is encrypted and access-controlled, and every action is recorded in an append-only audit trail. Messages play through a pillow speaker so a roommate does not hear them. We are designing toward on-premises inference so that voice data need not leave the facility at all.
No. VoiceKind is a general wellness product. It does not diagnose, treat, cure, or prevent disease. Clinical research involving human subjects is conducted under institutional review board oversight.
Two things. It can generate new messages in a family member’s voice from typed text, so a daughter does not have to record every message individually. And it learns which voices and content produce the strongest response for an individual patient, then recommends accordingly. Staff always make the final decision.
Not initially. Our first deployments are through skilled nursing facilities and rehabilitation units, where staff play messages at the bedside and record the clinical response. Home use is on the roadmap.
If any of the following describes you, we would like to hear from you.
Nursing homes and rehabilitation centers in the New York area, for a thirty-day clinical pilot. VoiceKind provides the platform, devices, and staff training at no cost.
Discuss a pilotWe are building an advisory board across neurology, speech-language pathology, and biostatistics, and preparing an NIH SBIR application.
Get in touchWe are hiring a CTO or technical lead. React, Node.js, and healthcare experience. Fractional or full-time.
See the roleWe are raising a pre-seed round to fund the production build and the clinical pilot.
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