A production personal finance app built on a simple bet: the reason people overspend is emotional, so the ledger should record the feeling alongside the amount.
Every budgeting app I tried could tell me I spent $16.99 at a restaurant. None could tell me I did it because I was hungry and my friends were going anyway. That second fact is the one that predicts whether it happens again next week.
Budgeting apps stop at categorisation. They produce a tidy record of what already happened and no insight into why, which is exactly the part a person needs in order to change anything. I wanted a system that captured the trigger, not just the transaction.
The product in order: the daily surface, the emotional check-in that makes the ledger different, then the coaching and automation built on top of it. Click any screen to enlarge
An emotion prompt is worthless an hour later — you have already rationalised the purchase. The check-in fires at capture time, in the same flow as logging the expense, which is the only point where the honest answer is still available.
Emotional and financial data is about as sensitive as a dataset gets. A sanitization layer tokenizes identifying fields before anything leaves for the model, so Aura reasons over shapes and amounts rather than identities.
A circuit breaker wraps every model call. When the provider degrades, the app falls back to deterministic summaries instead of hanging on a spinner — a smaller answer beats no answer.
Recurring cashflows evaluate in the user's local timezone, not the server's. Celery schedules per user rather than as one nightly global sweep, which is what makes a 'rent posts tomorrow' notification arrive at the right hour.
I am glad to go deeper on the architecture, the tradeoffs, or the parts that did not work the first time. That conversation is usually more useful than the README.