Zana develops an AI platform that analyzes digital voice biomarkers extracted from voice recordings to assess physical and mental well-being. This technology provides quantifiable health indicators for proactive care, remote monitoring in clinical research, and treatment adjustment. The platform currently offers applications focused on detecting severity and predicting decompensation in cardiology and respiratory diseases.
Funding
$40K raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Early detection and continuous monitoring of cardiorespiratory diseases often require frequent clinic visits and specialized equipment, creating barriers to proactive care and timely intervention. Subjective symptom reporting can be unreliable, and subtle physiological changes may go unnoticed until a critical event occurs.
Solution
Zana leverages AI-powered voice analysis to extract vocal biomarkers, providing objective and early indicators of health status, particularly for cardiology and respiratory conditions. Voice recordings, collected via mobile app or call center, are processed through Zana's SaaS platform. The AI technology identifies voice patterns associated with specific health outcomes and generates health scores. These analyzed results can be integrated into existing systems or accessed via API, enabling proactive care, efficient remote monitoring, and timely treatment adjustments.
Target Audience
The primary target audience includes pharmaceutical companies seeking to evaluate medication efficacy, monitoring providers aiming to improve the quality and reduce the costs of remote monitoring, and MedTech companies looking to enhance their devices with voice analysis capabilities.
Features
- AI-driven voice analysis for extraction of vocal biomarkers
- Mobile app and call center integration for voice data collection
- SaaS platform for processing and analyzing voice recordings
- Identification of voice patterns associated with specific health outcomes
- Generation of health scores for cardiorespiratory conditions
- API integration for seamless data transfer to existing systems
- Patient companion app for heart failure severity detection and decompensation prediction
- Customized app for predicting shortness of breath and declining lung function in asthma and COPD patients