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Greta.Agency
Consumer App · Solo Founder

Transactions That Categorise Themselves

FinTrack's AI categorises every transaction instantly — and learns from every correction, so accuracy improves the longer you use it.

3 days
idea to live product
10,000+
banks supported via Plaid
95%+
categorisation accuracy at 30 days
3x
higher goal achievement vs manual tracking
The Problem

Mis-categorised Spending

Mis-categorised Spending

Generic rules-based categorisation puts coffee in 'Restaurants' and software in 'Shopping'. Insights built on bad categories are useless.

Static Rules

Rule-based systems don't learn. The same mistake repeats every month.

The Solution

How it works

FinTrack combines Plaid's merchant data with AI to categorise transactions accurately from day one. Every user correction feeds back into the model — so categories get more accurate over time, personalised to each user's spending patterns.

01

Initial Categorise

AI applies category on transaction import using merchant data and description.

02

Confidence Score

Low-confidence categorisations flagged for user review.

03

Learn

User corrections update the model for that user's transaction patterns.

04

Improve

Accuracy rate tracked and surfaced to user — a satisfying feedback loop.

Outcomes

What you get

95%+ categorisation accuracy after 30 days
Personalised categories that match each user's actual life
Zero repetitive corrections for the same merchant
Category accuracy improves continuously without user effort
Get Started

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