AI Categorisation for EdTech using FinTrack
FinTrack's AI categorises every transaction instantly — and learns from every correction, so accuracy improves the longer you use it. Specifically designed for EdTech teams.
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.
AI Categorisation for EdTech
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. We build this specifically for EdTech teams.
Initial Categorise
AI applies category on transaction import using merchant data and description.
Confidence Score
Low-confidence categorisations flagged for user review.
Learn
User corrections update the model for that user's transaction patterns.
Improve
Accuracy rate tracked and surfaced to user — a satisfying feedback loop.
What you get
Why EdTech teams use FinTrack
Built for EdTech workflows
EdTech teams have unique requirements around compliance, data sensitivity, and growth patterns. FinTrack is configured to handle them.
AI Categorisation done right
Intelligent transaction categorisation that learns from corrections and improves over time. Tailored to the context of EdTech operations.
Shipped in 3 days
Greta builds fast. FinTrack went from idea to live in 3 days. We can do the same for your EdTech product.
Build this for your EdTech product.
We build fast, production-ready EdTech products. Scope to launch in days, not months.