Vaultwise
An AI budgeting coach that links every account and turns raw transactions into daily savings decisions.
Project Snapshot
- Client
- Vaultwise
- Industry
- FinTech (AI Personal Finance & Budgeting)
- Platform
- iOS & Android
- Timeline
- 5 months
- Our Role
- Full-stack mobile development, AI integration, and UI/UX design
The Challenge
Vaultwise came to iMobdev with a clear thesis: most people don't need another spreadsheet or a static budget chart, they need someone to actually tell them what to do with their money. Before development started, that thesis lived in a pitch deck and a spreadsheet of manual "coaching" notes the founders had been writing by hand for a small group of beta testers. There was no app, no bank connections, and no automated way to turn a bank statement into advice.
The pain points were specific. Users had no single view of net worth across checking, savings, credit, and investment accounts held at different institutions. Budgets that did exist were static snapshots that went stale within days of being set, with no mechanism to flag overspending before the month was over. And the founders' manual coaching notes — the actual product insight — had no path to scale past the handful of beta users they could review by hand every week.
Every month spent hand-writing insights was a month Vaultwise couldn't onboard new users, since the "coaching" was a person, not a product. Investors evaluating the seed round wanted to see the advice generated automatically, at scale, before committing capital to growth.
Technically, the team also had to solve for bank-grade security and reliability from day one — aggregating live transaction data across unpredictable third-party institutions while keeping the ledger accurate enough for users to trust every number on screen.
Our Solution
iMobdev framed Vaultwise as a single source of financial truth first, and a coach second: get the numbers right and current, then layer AI advice on top of data users could already verify against their own bank apps.
On the architecture side, we built native iOS and Android apps backed by a Node.js and NestJS API, with Plaid API handling secure bank-account linking and transaction sync across checking, savings, credit, and brokerage accounts. Transactions flow into a PostgreSQL ledger that categorizes and normalizes merchant data, while an OpenAI API-powered insight engine, orchestrated with LangChain, reads each user's rolling transaction and budget history to generate the plain-language observations that appear in the Insights feed — subscription creep, idle cash sitting below-market APY, category overspending, and goal-pacing projections.
On the UX side, we built the home dashboard around a single hero net-worth number with a live trend line, so the "am I doing okay" question is answered in the first second of opening the app. Budgets, transactions, and goals each got their own focused tab rather than being crammed into one dashboard, and every dollar amount that matters — over-budget categories, credit balances, goal progress — is color-coded consistently across the whole app so users build pattern recognition over time.
For the data layer, the categorization engine is trained against a continuously growing merchant-mapping table, and goal and budget projections recompute nightly against the latest transaction data rather than waiting for a manual refresh. Delivery was phased in three stages: account linking and the core ledger shipped first, budgets and the transaction feed followed, and the AI insight engine and goals module closed out the release ahead of the investor demo.
The Impact
Vaultwise launched with an automated coaching product where a manual, unscalable process used to be — every linked user now gets the same quality of insight the founders used to write by hand, generated fresh every day. The single net-worth dashboard and color-coded budgets gave users a reason to open the app daily instead of only at month-end, and the AI insight engine became the centerpiece of Vaultwise's investor demo.
The auditable ledger and nightly-recomputed goal projections gave Vaultwise a foundation it can extend with new account types and advice categories without re-architecting the core system. iMobdev continues to work with Vaultwise on new insight types as the user base grows.
Key Features
What We Built
Unified Net Worth Dashboard
One hero number and live trend line across every linked checking, savings, credit, and brokerage account.
Daily AI Insights Feed
Plain-language observations on subscriptions, idle cash, and spending trends, refreshed every day.
Category Budgets
Auto-categorized spending with progress bars per category and instant over-budget flags.
Real-Time Transaction Feed
Every linked-account transaction categorized and searchable within seconds of posting.
Savings Goals with Pacing
Goal cards that project your completion date from current savings velocity, not just a static target.
Secure Bank Linking
Connect checking, savings, credit, and investment accounts in under a minute via Plaid.
Tech Stack
- React Native
- NestJS
- PostgreSQL
- PLPlaid API
- OPOpenAI API
- LangChain
- AWSAWS
Screenshots
App in Action
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“iMobdev turned five months of whiteboard sketches into an app that gives every user the kind of financial advice we used to write by hand for a handful of beta testers. The AI insights feel like they actually know our users.”
Vaultwise
Founder
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ISO 27001-compliant, NDA-ready, GDPR-aware — secure by design at every layer.
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