Public Build Proof
Net Worth & Cashflow Management Engine
A household finance platform focused on transaction aggregation, budgeting visibility, long-term net worth tracking, and performance-conscious query design.
This project is useful recruiter proof because it is not just a personal dashboard. It combines backend design, caching strategy, scheduled upkeep, and opinionated financial views into a system that has to stay fast and trustworthy over time.
System context
What problem this project actually solves.
Most consumer finance tools are either generic, inflexible, or weak at combining budgeting, transaction visibility, and long-horizon net worth context in a way that matches how a real household actually reviews money.
Operating constraints
- Financial data is sensitive, so the public-facing story has to explain system quality without exposing actual records.
- Serverless performance matters because a sluggish dashboard undermines trust even when the calculations are correct.
- The application has to handle both operational views, like recent cashflow, and longitudinal views, like investment progress.
Why it belongs in the portfolio
A personal finance hub demonstrating serverless automation, custom caching, and clean dataviz.
It shows the decision-making, system design, and implementation signal behind the build without exposing private customer or financial records.
Architecture
How I structured the build.
The goal is not to show every file. It is to make the operational design legible to a recruiter or hiring manager in a few minutes.
Backend and APIs
Serverless endpoints handle read and write workflows while keeping the application deployable on lightweight infrastructure.
Data layer
Supabase provides the relational core for transactions, budget categories, cashflow history, and investment tracking.
Performance layer
Caching and indexing decisions are used deliberately so the dashboard stays responsive instead of devolving into slow ad hoc queries.
Decision surface
Recharts-based views expose surplus, trends, and anomalies in a way that supports action rather than decorative reporting.
Product and data decisions
- Optimized for fast recurring reads because a finance dashboard is only useful if people will actually open it often.
- Used scheduled upkeep to reduce serverless cold-start pain instead of pretending the platform defaults were sufficient.
- Designed the interface around cashflow decisions and anomaly review, not only net worth vanity metrics.
What a public reviewer can verify
- The case study makes the performance goals, automation design, and modeling priorities explicit for outside reviewers.
- The build demonstrates that I can move from schema and backend logic into a user-facing decision surface without changing problem domains.
- Sensitive household data remains private, but the technical constraints and implementation choices are concrete enough to assess.
Future iterations
What I would expand next.
Publish a sanitized schema and request-flow walkthrough showing how transactions, budgets, and projections connect.
Capture redacted screenshots or seeded demo states so viewers can inspect the actual dashboard experience.
Add tests or benchmarks that make the performance claims easier for an external reviewer to trust quickly.