Behavidence provides a mobile application that uses digital phenotyping and machine learning to generate a daily mental health similarity score based on passive digital behavior. This scientifically validated feedback offers providers, clinical trials, and insurance companies objective insights into mood, focus, worry, and stress levels. The platform enables early intervention and remote monitoring of mental health conditions while ensuring user data remains private and secure.
Funding
$10.1M 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.
WVFounders
Product
Problem
Individuals often struggle to consistently monitor and manage their mental well-being due to the challenges of self-reporting and the stigma associated with traditional mental health assessments. Existing methods rely heavily on subjective questionnaires and infrequent clinical visits, failing to capture the subtle, day-to-day fluctuations in mental state. This lack of continuous, objective data hinders early intervention and personalized support.
Solution
Behavidence offers a mobile app that passively monitors a user's digital behavior to provide daily insights into their mental health. By analyzing how individuals interact with their mobile devices—assessing usage patterns and engagement metrics—the platform generates an anonymized "Mental Health Similarity Score." This score reflects the similarity between a user's digital behavior and that of individuals with specific mental health conditions like ADHD, depression, or anxiety. The app aims to provide users, clinicians, and insurers with an unbiased, data-driven tool for early detection and ongoing monitoring of mental well-being, without tracking personal content or compromising privacy.
Target Audience
The primary target audience includes individuals seeking to manage their mental well-being, clinicians looking for objective monitoring tools, clinical trial researchers needing real-time behavioral markers, and insurance companies aiming to reduce costs through early intervention.
Features
- Passive data collection of mobile usage patterns and engagement metrics
- AI-driven analysis to generate a daily Mental Health Similarity Score
- Anonymized data to ensure user privacy and security (AES 256 encryption)
- Scientifically validated digital biomarkers for mood, focus, worry, and stress
- In-app journal for users to record insights and track progress
- Integration capabilities via SDK for existing platforms
- Support for administering standard questionnaires (e.g., PHQ-9, GAD-7, ASRS)
- Availability on both iOS and Android devices