Telehealth Respiratory Monitoring

Telling.ai analyzes voice and breath sounds to assess lung health

Voice and breath sounds are powerful biometrics

Breathing icon

Speech is a complex process involving the lungs, upper airways, nerves, and muscles.

Sound wave icon

Signatures found in breath and speech, are indicators of many medical conditions, including respiratory diseases and infections.

Pneumonia icon

Mucus, obstruction, congestion, inflammation, scarring, and more have unique auditory signatures.

Under Attack

The lungs are the only internal organ constantly exposed to the elements

20% of US adults smoke regularly
25% of high school seniors vape regularly
Climate change has contributed to increases of wildfires and allergenic air pollutants
Even before considering the added impact of coronavirus, lower respiratory tract infections cause nearly 4 million deaths per year globally
Massive Need
47 million
Americans live with a chronic lung disease
$150 billion
The annual spend on chronic lung disease and respiratory infections
800,000+
Hospitalizations per year from COPD alone

Voice Advantages

Ease of Use
As easy as speaking into your phone and entirely non-invasive
Low Cost
Use the phone you already have without any professional assistance
Ubiquitous Availability
At home or wherever you happen to be
Instantaneous
Results available within seconds of sample submission
Personalized
Your vocal and respiratory tracts are unique to you
Predict and prevent acute exacerbations

By monitoring the 47 million at-risk Americans, we aim to enable timely interventions that prevent costly hospitalizations.

COPD alone accounts for 1.5 million Emergency Department visits per year and 800,000 hospitalizations. Nearly 20% of AECOPD patients are readmitted within 30 days.

We hear you in ways
no one else can

A unique framework to capture respiratory sounds in real world settings, providing real-time feedback and denoising to optimize data quality.

We extract dozens of features - many undetectable by the human ear - to power our best-in-class algorithms.

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