Review your recorded patterns
Explore patterns across check-ins, tags, and daily context. Insight processing runs on your device; optional sync and account features are described separately in our privacy policy.
Pattern detection
Vibbrancy reviews your mood entries to surface recurring tags and time-based context. You might notice that entries tagged “exercise” tend to score higher, or that Sunday evening check-ins tend to be lower. These patterns are observations, not proof of a cause.
Recurring themes
The app shows activities, people, and situations that recur in the entries you record. Their presence alongside a mood does not establish that they caused it.
Day-of-week patterns
Compare your recorded check-ins by day of the week. Treat differences as questions to explore rather than conclusions about why a day felt a certain way.
Automatic insights
You don't have to go looking. Insights proactively surface as they're detected — they show up in your feed ready to read.
Context patterns
Review people, places, activities, tags, and times that recur around your mood entries. Vibbrancy presents this context for reflection; it does not determine a trigger, diagnose a condition, or explain why your mood changed.
Context-aware analysis
The app can group notes, tags, time of day, and day of week around the entries you record. You decide whether a recurring context is useful to explore further.
Sequence, not cause
The app can show context recorded before or after a mood change. Sequence and correlation do not prove that one event caused another.
Reviewable context
Review recurring context such as sleep tags, social interactions, or routines. You choose whether to keep observing, change something, or take no action.
Visual analytics
Review weekly and monthly mood trends, distribution breakdowns, and tag correlations. The charts describe what you recorded and do not assign a cause or medical meaning.
Mood trends
Line charts show how your recorded mood scores change across daily, weekly, and monthly views. A change is not a warning or diagnosis.
Distribution breakdown
See how your recorded check-ins are distributed across a chosen period, including the share of higher and lower scores. The chart does not explain those scores.
Tag correlations
Compare tags that appear alongside higher or lower recorded mood scores. A difference can have many explanations and is not proof of an effect.
Export your data
Use the app's export controls to make a portable copy of your mood history. Available formats and plan access are shown in your current app version.
On-device processing
Analysis runs locally on your phone using the app's on-device engine. Mood entries do not need to be sent to a server for insight processing.
Local insight processing
The analysis engine runs on your phone. Optional account, sync, subscription, diagnostics, and support features are separate from insight processing.
Powered by Transformers.js
Vibbrancy uses Hugging Face Transformers.js to run supported analysis models on your device. Mood entries do not need to be sent to a server for insight processing.
Works offline too
Locally available insight views can be reviewed without an internet connection. Optional sync and other connected features require connectivity.
Build a record you can review
As your own history grows, Vibbrancy can surface recurring context worth reviewing. What appears depends on the entries you choose to record.