Every decision, and why it was made that way
Most of what follows is a choice someone else made differently. Where that is the case, the reason is stated — so you can disagree with it on the merits rather than taking it on trust.
What it does
Six things most habit trackers get wrong
Each of these is a decision with a reason behind it, not a feature list.
Habits that forgive a bad week
A day counts at 60% of its expected load, not 100%. A habit due four days a week only asks for four. Six of eight glasses of water is 0.75 of that habit, not a failure. Streaks you can actually keep.
Sleep, in stages
Duration, deep, REM, light and awake, with bedtime consistency tracked separately — because when you go to bed predicts more than how long you stay there. Ready for Apple Health and Health Connect.
A journal that stays yours
Morning intentions, evening reflections, and an AI that reflects on what you wrote. The text never leaves your account — not to an ad platform, not into a training set, not into our own dashboards.
Statistics, not vibes
Pearson and point-biserial correlations with exact t-distribution p-values. A finding appears only if it clears three floors at once: 20 paired days, |r| ≥ 0.25, and a corrected p ≤ 0.00625.
Honest about nothing
The hypotheses are fixed in advance rather than trawled, so "nothing to report" is a real outcome the screen is designed to show. Every card carries its r and its sample size.
Calm by construction
No streak-loss guilt, no red badges, no notification you did not ask for. Every colour in the interface was contrast-solved rather than eyeballed, in both light and dark.
In depth
The four decisions worth a longer answer
Each of these is a place where Crescendo does something other trackers do differently, and where the reason takes more than a card to explain.
Correlations between your habits, your sleep and your mood
This is the part of Crescendo that justifies the rest of it. Tracking is only worth the effort if something reads the data back to you and says something true about it.
Streaks that measure the habit, not your attendance
Most streak counters measure one thing: whether you have failed to break a chain. That is a measure of attendance, and it stops describing your habits the moment life is anything other than uniform.
An AI journal that does not read your journal
"Private" is the easiest word in this category to write and the hardest to mean. Here is the specific version, which is checkable rather than reassuring.
Your data, exportable in one click
The test of whether an app considers your data yours is not what its privacy policy says. It is how hard it is to leave.
Use cases
What people actually come here to solve
The same product, argued for the problem you turned up with.
Habit tracking
Most habit trackers count. This one also checks whether the counting meant anything, and says so plainly when it did not.
Goal tracking
A goal you cannot act on this afternoon is a wish with a deadline. The point of this page is the decomposition.
Accountability
Motivation is a weather system. Anything you build on it stops working on the day you most needed it to.
Progression
Gamification usually fails in one direction: the points become the goal. This one is built to make that unprofitable.
Digital wellbeing
Everyone knows the number is too high. Knowing that has never once been the thing that changed it.
Focus
The decision to not be interrupted has to be made before the interruption, because afterwards you are no longer the one deciding.
Not enforcing yet
App blocking
Most app blockers are defeated in about four seconds. The interesting design questions are all about what happens after that.
Not enforcing yet
For students
Almost everyone revising has a plan. Far fewer have a plan that survives the first week it goes wrong.
For professionals
The habits that support demanding work are the first to be cut when the work gets demanding. That is not a coincidence, and it is measurable.
What you actually see
Your day, then the pattern behind it
Two screens carry the product. Today is what you open in the morning. Insights is what you read at the end of a month.
Today
Whole habits finished, so the ring always agrees with the checkmarks.
Insights
Every claim about your life arrives with the evidence for it.
Better sleep, more training
r = 0.41 · n = 118 · p < 0.001On nights over 7h 20m you trained on 71% of the following days, against 34% otherwise.
Morning meditation lifts tomorrow
r = 0.29 · n = 104 · p = 0.003Mood averaged 0.5 higher the day after you sat, controlling for sleep.
Caffeine after 2pm and deep sleep
n = 14 · 6 more daysNot enough paired days yet. We will not guess before the numbers can carry it.
Illustrative figures from the demo dataset — the same ones the seeded history produces, and the same filters your own data passes through.
How it differs
Compared with a typical habit tracker
Behaviours rather than brands, so you can check each one yourself.
| Capability | Crescendo | Typical |
|---|---|---|
| Streaks that survive one missed day | Yes | No |
| Partial credit on numeric targets | Yes | No |
| Correlations with p-values and sample sizes | Yes | No |
| Pre-registered hypotheses, not data trawling | Yes | No |
| Sleep stages alongside habits | Yes | Varies |
| Journal text excluded from all analytics | Yes | No |
| Full data export and deletion, self-service | Yes | Varies |
| Contrast-audited in light and dark | Yes | No |
Give it a month and see what it finds
Twenty paired days is the minimum before the statistics will say anything at all. That is roughly three weeks of ordinary use.
Want it on your phone?
On iPhone: Safari, then Share, then Add to Home Screen.
On Android: Chrome, then the menu, then Install app.
Prefer to wait for native apps? Leave an email and we'll tell you the day they land. Nothing else.