Underwrite flips in minutes. Keep the math inspectable.
FlipFinder Analyze is built for operators who need one canonical deal model, one deterministic engine, and one decision system that survives real diligence.
2841 Oak Knoll Avenue
Oakland, CA 94605
3 beds · 2 baths · 1,680 sqft
| Purchase price | $540,000 |
| Rehab budget | $80,000 |
| Total project cost | $704,382 |
| Net profit | $212,413 |
| Downside profit | $74,521 |
Operators need to know when a deal breaks and which inputs actually swing the call.
Know when a deal breaks, not just whether it pencils. See which inputs swing your outcome, and what happens if any of them drift against you.
Invisible defaults
Critical assumptions often hide in workbook cells and survive from the last deal without an audit trail.
No canonical intake
Listing copy, broker notes, and structured values drift apart, so teams debate inputs before they can debate the deal.
Weak downside view
When ARV softens and rehab slips, most calculators do not explain why the chip should change.
The tool is designed around the questions that surface before capital moves.
Each screen exists to collapse operator uncertainty, not to generate more of it.
Six modules, one underwriting spine.
The product feels premium because every part is disciplined: intake, normalization, deterministic math, stored scenarios, memo output, and public proof.
Canonical intake
Manual entry, listing paste, and FlipFinder import all normalize into one typed deal object.
Deterministic engine
Transparent acquisition, rehab, financing, holding, exit, and profit math in pure TypeScript.
Decision rules
Green, yellow, and red are rule-based with stable reason codes instead of vague model language.
Scenario storage
Every scenario persists its canonical input, computed outputs, memo, and audit trail.
Sensitivity view
ARV, rehab, and hold-duration stress cases surface whether the deal breaks on first contact.
Memo output
Each computed scenario renders a deterministic memo that a partner or lender can actually read.
Built for operators who want discipline, not decoration.
The software is best when the team already knows how to think through a flip and wants the system to hold that standard every time.
- Single-market or multi-market operators.
- Teams that need a memo and a decision chip from the same source of truth.
- Buyers who duplicate scenarios before changing an offer.
- People looking for AI-generated narratives instead of deterministic math.
- Operators who only need a top-line profit guess.
- Teams that are not willing to keep assumptions explicit.
This is opinionated software for real underwriting work.
The product is deliberately restrained. No gradient theater, no fake urgency, and no black-box scoring. The point is to let an operator move faster without giving up trust.
FlipFinder Analyze exists to make capital conversations cleaner. If the answer is yellow, the reasons are explicit. If a team member disagrees with the output, the debate moves to inputs or rules instead of hand-waving.
Don't buy a deal whose math you can't defend. Every number, every scenario, every assumption — traceable before you wire earnest money.
What matters is not prettier output. It is having scenarios, assumptions, memo output, and decision reasons tied back to one canonical deal.
Scenarios that stay in sync
Vary finance and exit. Comparisons stay aligned because the math engine is one place.
Assumptions you can audit
Every input is stamped with its source: what you set, what the pack gave you, when it changed.
Memos that show the work
A decision summary, the base case, and the downside side-by-side. Ready to hand to a partner.
A trail for every number
Open any scenario later and see which inputs changed, who changed them, and what the decision was at the time.
The questions are mostly about trust, not features.
That is the right shape of demand for underwriting software.
No. The engine is deterministic. The only future AI seam is optional assistive parsing, and that does not own the math.
Yes. The system ships with baseline and conservative packs, and you can clone or edit assumptions so inherited values stay visible.
Yes. Duplicate a scenario, change the assumptions, and compare deltas side by side.
The Oak Knoll walkthrough is driven by the seeded scenario result used throughout local development.
Export buttons exist as stubs in v1. The seam is there for future document services.
Supported county feeds and RentCast sale listings drop into the same comps panel, and you can still enter comps manually when no feed is available.
Start from the sample, then open the app and pressure-test your own deal.
The public story and the authenticated product are one system. The same Oak Knoll scenario that powers the marketing surface powers the underwriting surface.