Description
Unlike most wellness apps that only provide generic tips or meditations, W3LL Companion uses proven psychology and cutting-edge science [1][2] to understand your stress, mood, and energy, then delivers personalised tips right when you need them.
W3LL Companion uses your phone's built-in sensors to understand patterns in your daily life. It passively and anonymously analyzes data from your phone’s motion sensors and location to help detect subtle changes in your behavior that are linked to stress and mood. Get daily feedback and receive tips to boost performance and improve well-being every day.
Discover your wellbeing hassle-free. Track stress, anxiety, and depression without constant surveys, get daily feedback, and receive tips to boost performance and improve wellbeing every day.
Your emotions and wellbeing matter. They shape how you feel, think, and perform every day. W3LL Companion is your personal wellbeing guide, built with clinical expertise to help you better understand your mental state and take small, positive steps towards balance and resilience.
Key Features:
■ Smart Wellbeing Tracking
Get a clear picture of your stress, mood, and energy with clinical-grade data — just by allowing the app to run in the background.
■ Personalised Insights
Understand what’s driving your wellbeing with easy-to-read explanations and practical takeaways.
■ Daily Tips That Work
Short, science-based strategies designed to improve mood and sharpen focus.
■ WhatsApp Integration
Get nudges and science-backed tips directly through WhatsApp, making it easy to stay consistent without overwhelming app notifications.
■ Progress You Can See
Track your wellbeing over time and celebrate the small wins that lead to lasting change.
Privacy First:
Your emotional data is yours alone. We never sell your information. Reports are securely stored and accessible only by you.
[1] Wang, R., et al. (2014). Tracking Mental Health with Mobile Phone Sensing: A Survey. IEEE Transactions on Affective Computing. This survey paper reviews the use of mobile phone sensors, including motion and location, to infer mental health states. It provides a strong basis for the claim that these methods are a subject of significant research and have potential for real-world application.
(https://dl.acm.org/doi/10.1145/3191775)
[2] Schoenfelder, D. et al. (2019). The use of smartphone sensors to predict mood states in patients with bipolar disorder. Journal of Affective Disorders. This study shows how passive sensor data from smartphones can be used to predict mood states in clinical populations. It directly links the use of motion and location data to the detection of changes in mood and behavior.
(https://ieeexplore.ieee.org/document/6866115)