While wellness-focused software is often designed to address resting or sleep, Mindwell’s machine learning “predictive mood engine” is rooted in its most prominent feature: MoodShift. This tool enables users to choose a “desired mood outcome” by logging their current one on a grid, Monclarity’s chief product officer Paul Ingram told Observer.
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“We create psychographic profiles based on where you are and what time of day it is,” Ignram explained. “We can then correlate that with the weather, as well as life-impacting events happening in your locations, that might be affecting your mood.”
Using this data, the Mindwell team then suggests which meditations—from over 350 tracks across 36 categories—are “the most effective when combined with those specific dynamics.”
MoodShift suggests two to three meditations combined as a personalized sequence put together by Monclarity’s team of neuroscience consultants, including a specialized musician who composes and voices many of Mindwell’s tracks. But while the AI-generated sequences will help cultivate a long-term practice, they won’t necessarily take you directly to the mood you’d like to achieve.
“A great example of how we imagine this being used is helping take you from a bad meeting you’ve had to getting ready for the next one,” Ingram said.
The advantage of using machine learning is that it gives Mindwell’s team the ability to aggregate and understand patterns across millions of users. Eventually, the system will be fine-tuned to what’s going on around each user.
“As we gather more data about what’s effective for a user, we can match them with tracks that have the highest likelihood of getting them to the mental state they need to be in,” Ingram said. “It’s not a quick trick; it’s a practice based on training muscle memory over time.”