Split It automatically tracks your purchases, flags transactions you’ll likely share, and lets you settle up with friends in seconds.

24/7 transaction monitoring via secure Plaid connections

AI detection of likely shared purchases—dinners, rides, rentals & more

One‑tap splits and instant payouts through Venmo contact sync

Real‑time push alerts plus weekly & monthly summary digests

Privacy‑first design—bank credentials never touch Split It’s servers

Say goodbye to the “Did we ever split that?” dilemma. Split It keeps an always‑on eye on your bank activity: the moment your card clears at that group dinner or rideshare, the app sends a gentle nudge—“Want to split with Alex and Jamie?” Approve, adjust amounts, and Venmo handles the rest.

Powered by machine‑learning cues such as merchant type, location, and time of day, Split It surfaces only the purchases you’re most likely to share, saving you from statement‑scroll fatigue. A clean dashboard organizes every transaction, while weekly and monthly recaps make budget check‑ins effortless. Whether you’re splitting rent with roommates or costs on a weekend getaway, Split It ensures everyone settles up—fast, fair, and friction‑free.

Behind Split It’s simple interface lies a robust finance toolkit built for everyday life:

The onboarding flow connects to banks through Plaid’s OAuth process, giving Split It read‑only access that keeps credentials private. Once linked, an AI categorization engine tags every purchase, feeds a smart‑alert system, and populates spending insights—highlighting repeat merchants, location trends, and category totals.

Mobile notifications arrive in real time; deeper dives live in the dashboard, where users can filter by friend, merchant, or date, or add cash payments for a complete ledger. And because memories matter more than math, Split It syncs contacts so repayment happens with a single tap.

AI Tagging & Auto‑Categorization

Instant Push / SMS Reminders

Venmo Payout Integration

Contact Sync & Smart Suggestions

Insight Cards for Spending Patterns