App builder

Run every deal through your own deal analyzer
before you send the offer.

Tell Netiva how you underwrite and the agent builds a private web app where saved deals, your assumptions, the comps behind them and every run’s numbers stay in one place.

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Starter prompt

Build a private deal analyzer web app for an investor buying small multifamily in two markets. Behind sign-in I save deals with address, market, units, asking price, stage and offer deadline. Each deal holds several underwriting runs — base, conservative and lender cases — each with the price tested, rehab and closing costs, stabilized rent, the operating expenses I expect after purchase and my quoted rate, plus the percentages and loan sizing from its buy box profile. Show net operating income, cap rate, cash-on-cash, coverage and the highest price that clears my minimums. Attach sale and rent comps, and print a one-page summary per run.

Build it in Netiva Paste the prompt into a new workspace and adjust it to your business.
Overview

Who this deal analyzer is for

Most investors underwrite in a spreadsheet that started on somebody else’s laptop. A year in, the vacancy rate on one tab no longer matches the next, the rent comps that justified the number sit in an email and nobody can say why the March offer was $40,000 higher than this one. A deal analyzer built with Netiva keeps saved deals, the assumptions behind each run, the comps you leaned on and a one-page summary together, so every offer traces back to figures you can defend to a partner or a lender.

Key features

What your deal analyzer can do

  • One deal, several cases

    Underwrite the same building at your number, at today’s in-place rent and at the rate and loan sizing your lender will use. Every run is saved with the assumptions behind it, so you can see why a deal that worked in March doesn’t now.

    • Net operating income, cap rate, cash-on-cash and coverage on every run
    • Runs for one property listed side by side, with the case your offer came from
    • Price tested, rehab and closing costs, rent and the operating expenses you expect, per run
    • The formula behind each result readable in the code view

  • Buy box screening

    Your minimums — vacancy and management percentages, a per-door reserve, loan-to-cost and amortization, a cash-on-cash floor, a coverage ratio — live in a buy box profile. Each run is checked against it, and a miss names the failing test.

    • A pass or miss flag on every run, with the failing test named
    • One profile per market or strategy, with the loan-to-cost that market really offers
    • Profile percentages and loan sizing screen every run; price, rent, expenses and rate are per case
    • Saved views for deals under review and deals you passed on

  • Comps behind the rent you used

    Sale and rent comps sit on the deal they support or in a market library, each with living area, a date and where it came from. The deal page works out price and rent per square foot, so an assumption isn’t just a feeling.

    • Sale comps and rent comps in one list, filtered by market and reused across deals
    • Price and rent per square foot across the comps you kept
    • A date and a source on every comp, so stale evidence stands out
    • Unit rents you describe to the collection assistant, drafted into rows you review

  • A one-page summary you can print

    Each run gets a print-ready sheet: the property, the case, the assumptions used, the results and the comps behind them, with the estimate notice you want on it. Deadline emails keep the pipeline moving.

    • Assumptions printed next to the results they produced
    • An estimate notice on every sheet the app prints
    • Emails before an offer deadline and when a deal sits too long
    • Everything behind sign-in, so your pipeline stays private
Data model

The collections behind it

Netiva keeps your records in built-in collections. Here’s a starting structure — the agent adapts it to your prompt, and you can change it any time.

Deals

Every property you have looked at, from a broker’s email through to a closing.

  • Address (required) Text
  • Market (required) The submarket or county you buy in; the pipeline and comp views filter by it Text
  • Property type (required) Single-family, duplex, small multifamily, mixed use Text
  • Units (required) Doors in the building; 1 for a single-family rental Number
  • Asking price (required) Number
  • Stage (required) Screening, Underwriting, Offer out, Under contract, Passed, Closed Text
  • Offer due A call-for-offers date or the deadline the broker gave you Date
  • Seller package Rent roll, operating statement or offering memorandum you were sent File

Buy box profiles

The standards a deal has to clear and the assumptions each run starts from.

  • Name (required) One per market or strategy, such as Core rentals or Value-add multifamily Text
  • Vacancy rate (required) Percent of gross rent held back for vacancy and credit loss Number
  • Management fee (required) Percent of collected rent; many underwrite one even when self-managing, as some lenders do Number
  • Maintenance and reserves (required) Yearly amount per door for repairs and a capital reserve Number
  • Loan-to-cost (required) Percent of price plus rehab your lender funds on this kind of deal Number
  • Amortization years (required) Years the payment is spread over, such as 25 or 30 Number
  • Minimum cash-on-cash (required) The return on cash invested you will accept, as a percent Number
  • Minimum coverage ratio (required) Debt service coverage ratio (DSCR): net operating income over yearly debt service Number

Underwriting runs

One saved pass at a deal: what you tested and under which assumptions.

  • Deal (required) Relation to Deals
  • Buy box profile (required) Supplies the percentages, loan sizing and minimums this run is checked against Relation to Buy box profiles
  • Case (required) Base case, Conservative, Lender case, Seller ask Text
  • Price tested (required) Number
  • Rehab and closing costs Repairs and capital work before stabilization, plus loan fees, title and due diligence Number
  • Stabilized monthly rent (required) Every unit at the rent you expect after rehab, before vacancy Number
  • Yearly operating expenses (required) Taxes, insurance, owner-paid utilities and anything the profile percentages miss Number
  • Interest rate (required) Percent per year; debt service comes from the profile’s loan-to-cost and amortization Number

Comps

The sales and rents behind the value and the income you assumed.

  • Deal Leave blank for a comp you keep in the library for the whole submarket Relation to Deals
  • Market (required) Matches the market on the deals this comp supports Text
  • Comp type (required) Sale comp or rent comp Text
  • Address (required) Text
  • Price or rent (required) Closed price for a sale comp, monthly asking rent for a rent comp Number
  • Living area Square feet; add beds and baths if your rent comps turn on them Number
  • Comp date (required) Close date, or the day you captured the asking rent Date
  • Source (required) Public record, a data provider you license, a broker’s note or your own licensed MLS feed Text

Required field. Types are Netiva collection field types.

Screens

Pages and screens to start with

A typical first version. Ask the agent for more, or annotate the preview to change any of them.

  • Pipeline

    Every deal by stage, with the base-case return, the buy box flag and days left on the offer deadline, filtered by market.

    Signed-in users

  • Deal file

    One property with its runs side by side, the comps behind them, the seller’s package and the case your offer came from.

    Signed-in users

  • Underwriting run

    Enter price, rehab, rent, expenses and the rate; income, cap rate, cash-on-cash, coverage and the maximum offer update as you type.

    Signed-in users

  • Run summary

    A print-ready sheet for a partner or a lender: property, case, assumptions, results and comps, all marked as estimates.

    Signed-in users

  • Buy box

    Your profiles with their minimums, default percentages and loan sizing, next to the runs each one has screened.

    Signed-in users

  • Comp library

    Every comp saved on a deal or kept for a market, filtered by type and date, with price and rent per square foot worked out.

    Signed-in users
How it works

From prompt to a live deal analyzer

  1. Describe how you underwrite

    Tell the agent which numbers decide a deal for you, which assumptions you reuse and how many markets you buy in. It drafts collections for deals, runs, buy box profiles and comps, and wires the deal page to them.

  2. Set your buy box

    Enter your minimums, percentages and loan sizing in the collection grid, one profile per market or strategy, then check them against what you are actually paying and what a lender is actually quoting you.

  3. Re-underwrite a deal you closed

    Load a building you already own into the live preview and compare the run with the spreadsheet you bought it on. If a figure is off, annotate the preview or read the formula in the code view and ask for a fix.

  4. Publish and work the pipeline

    Publish in one click, sign in from your phone at a walkthrough and switch on the deadline emails. Every change is checkpointed, so an assumption you change and regret is easy to roll back.

Why Netiva

Netiva vs a traditional build

Building a deal analyzer with Netiva compared with a traditional build
Criterion With Netiva Traditional build
Underwriting a new deal A new run that reuses your saved assumptions and stores every input against the deal A copy of last quarter’s spreadsheet, renamed, with formulas that may not have survived the copy
Showing your work to a partner A summary sheet rebuilt from the saved run each time somebody opens it A PDF of one tab, out of date the moment a rent or rate assumption moves
Getting started Describe what you need in chat and watch it take shape in a live preview Hire developers, or stitch together templates, plugins and a hosting plan
Content and data Built-in collections with nine field types, bound straight to your pages Set up and connect a separate database or CMS
Making changes Ask the agent; every change is checkpointed and reversible File a ticket, wait for a sprint, redeploy
Hosting and domain Global hosting and automatic SSL; connect a custom domain from the Starter plan Buy hosting, then install and renew SSL certificates yourself
Code ownership Clean production code you own and can export Locked into a template, plugin or agency setup
Examples

Ways teams use it

  • An investor buying two buildings a year

    Most broker emails don’t survive the first pass. The buy box flags them in minutes, the deal is marked Passed with the run that missed still on the file, and the few that clear get a full run and a walkthrough.

  • Two partners running a small fund

    Both partners underwrite from the same profiles, so an argument is about an assumption rather than a formula. The lender case, at a lower rent and a higher rate, is the one that goes to the bank with the summary sheet.

  • A buyer moving into short-term rentals

    A nightly rate and an occupancy percentage replace monthly rent, management runs higher and cleaning sits in operating expenses, so one deal page holds a short-term run beside a long-term one. Check local registration, permit and zoning rules before you underwrite nightly income.

Good to know

Before you build

  • The math is yours, not a valuation

    The app calculates what you enter. It isn’t an appraisal, an automated valuation or a lending decision, and Netiva doesn’t supply property values. A lender re-underwrites with its own appraisal, rent schedule and rules, and can land somewhere else.

  • Comps and property data come from you

    Netiva doesn’t supply MLS data. Comps taken from an MLS need your own licensed IDX or RESO feed and have to follow that MLS’s display, attribution and refresh rules. Otherwise work from public records, a data provider’s API with your own key or comps you type in.

  • Assumptions age faster than you expect

    Operating expenses on a seller’s statement may not be yours: in California, a change in ownership triggers a reassessment to current fair market value. A term shorter than the amortization leaves a refinance date to plan around. Re-check each profile against what you pay now.

  • Sourcing and closing live elsewhere

    This app starts when a deal arrives and stops when the offer goes out. Finding off-market houses, tracking a rehab and running contracts and closing checklists belong in separate apps, and so do the month-by-month numbers once you own a building.

Compliance note

Net operating income, returns, coverage ratios and a maximum offer are arithmetic on assumptions you chose — not an appraisal, an automated valuation or financial, lending or investment advice. Keep that notice on any summary you hand a partner or a lender, and keep a date and a source on every comp a run leans on.

FAQ

Questions about building a deal analyzer

How does a deal analyzer work out a maximum offer?

However you describe it to the agent. Rental buyers usually solve backwards: hold the buy box minimums fixed, such as a cash-on-cash floor and a coverage ratio, then ask what purchase price still clears them at the rent and expenses in that run. Flippers more often work down from an after-repair value, subtracting repairs, holding costs, selling costs and the profit they want. Either way the figure is an estimate built from your own inputs.

Why keep more than one run on the same deal?

Because the argument is always about assumptions. A base case at the rent you believe, a conservative case at today’s in-place rent and a lender case screened against a profile that carries your bank’s loan-to-cost and coverage minimum give you three answers from one property. Each run stores the price, rent, expenses and rate it used, so when a seller counters you can compare what actually changed instead of rebuilding a sheet from scratch.

Can the app pull comparable sales and rents for me?

Not by itself. Netiva doesn’t supply MLS data, property records or valuations. You can type comps in, or ask the agent to call a property or rental data provider’s API with your key stored securely. If the comps come from an MLS, you need your own licensed feed and have to follow that MLS’s display and refresh rules. Every comp keeps its source and date either way.

How is this different from a public rental property calculator?

A public calculator is a marketing page: a visitor runs a quick number and you get a lead. A deal analyzer is private. It sits behind sign-in, holds a pipeline of real addresses, keeps the assumptions and comps behind each offer and prints a summary for a partner or a lender. The arithmetic overlaps; the job is not the same.

Can I underwrite from my phone at a walkthrough?

Yes. Netiva builds web apps that run in the browser, including on phones, so you can open a deal at the property, drop a rehab budget into a run and watch the coverage ratio move before you leave. There is nothing to install and no store listing — you sign in through the same link you use on a laptop.

Who can see my deals, and do I own the analyzer?

The pages sit behind sign-in rather than on the open web, and users sign in with their own accounts, so each partner opens the deals on their own account and their pipeline stays separate from yours. The code is clean and framework-standard, yours to read, edit or export whenever you want, and every change is checkpointed, so an assumption you rewrite badly can be rolled back.

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Drafted with AI assistance from Netiva’s product pages and reviewed by the Netiva team. Example data models, screens and prompts are illustrative starting points, not customer projects.

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