
Behavidence
Mental Health Application | Behavidence.
Date | Investors | Amount | Round |
---|---|---|---|
- | investor investor investor | €0.0 | round |
N/A | €0.0 | round | |
investor | €0.0 | round | |
* | $4.3m | Seed | |
Total Funding | 000k |
USD | 2021 | 2022 | 2023 |
---|---|---|---|
Revenues | 0000 | 0000 | 0000 |
% growth | - | 31 % | 17 % |
EBITDA | 0000 | 0000 | 0000 |
Profit | 0000 | 0000 | 0000 |
EV | 0000 | 0000 | 0000 |
EV / revenue | 00.0x | 00.0x | 00.0x |
EV / EBITDA | 00.0x | 00.0x | 00.0x |
R&D budget | 0000 | 0000 | 0000 |
Source: Dealroom estimates
Related Content
Behavidence is a digital health startup that offers a mobile application designed to measure and track users' mental health. The app uses digital phenotyping and machine learning to analyze users' behavior and provide daily feedback. This feedback is based on scientifically validated data and gives insights into the user's mood, focus, stress, and worry levels.
The company's primary clients are psychiatrists, physicians, and insurance companies, but the app is also designed for individual users who want to monitor their mental well-being. The app is available on both Android and iOS platforms, making it accessible to a wide range of users.
Behavidence operates in the digital health market, specifically in the mental health tech sector. Its business model revolves around providing a tool for mental health professionals to monitor their patients' mental health and for individuals to self-manage their mental well-being. The company generates revenue through the use of its app, either by embedding its software development kit (SDK) into existing platforms or by providing unique codes for users attributed to the data collected via the app.
The company assures total privacy and security for its users. It does not collect any identifiable or personal data, and all user data is encrypted and protected using top systems. The app does not track any content, and users are fully anonymized.
Keywords: Digital Health, Mental Health, Mobile Application, Digital Phenotyping, Machine Learning, Privacy, Security, Self-Management, Mental Well-Being, Data Encryption.