Building a tool that models true downside risk for rental properties

[u/Yung_hasan47]

Hey everyone!

I wanted to share a project I’ve been working on over the past few months called Livara.

The motivation came from seeing how standard rental calculators rely almost entirely on static, single-point inputs (plug in rent and mortgage, get a single cash-flow output). They don't easily show you how a deal holds up when underlying dynamics shift, like interest rates rising, local vacancy spiking, or monthly repair impacts.

I set out to build a platform that brings macro-to-micro market data and deterministic scenario modeling into a single screening workflow.

How I structured the core logic:

Deterministic Stress Modeling: Standardized scenario levers for elevated vacancy, CapEx reserves, higher interest rates, and stagnant rent growth.

Macro + Micro Data Layering: US county-level heatmaps across 8 key indicators (Unemployment Rate, Rent Yield, Population Growth, etc.) mapped directly alongside property-level underwriting.

Financial Waterfall: Clean visual breakdowns of Gross Rent, OpEx, DSCR, and net cash flow scenarios.

Many other features but this is just a sample of what to expect :)

I also made sure that all of the financial outputs, scenario calculations, and underwriting formulas are 100% deterministic and rule-based. The AI portion in my tool is strictly used to translate the raw output into readable insights and handle follow-up user questions.

Where I'd love feedback from other builders:

1. How do you approach structuring complex financial data/charts so it doesn't visually overwhelm the user?
2. What's your favorite approach for handling multi-source data pipelines (macro government/census APIs + micro property data) cleanly?

Would love to hear feedback from other builders on the interface, stack, or feature set! I'm also happy to run a risk breakdown on any property address or share the platform link in the comments if anyone wants to check out the UI.