Co-Founder & Technical Lead, Appraiva | Co-Founder & CEO, Royal Abraj Group | AI & data systems

Ahmadreza Samadi • Peerlist

A browser-local tool by Ahmadreza Samadi for comparing two to five property value estimates: lowest, highest, median, percentage spread and review flags.It flags estimates more than 10% from the median and prompts evidence checks; agreement does not establish accuracy. Educational, not financial advice.

Valuation range checker

A reproducible descriptive analysis by Ahmadreza Samadi, using U.S. Census Bureau ACS 2024 table B25070 across 386 whole metropolitan areas in the 50 states/DC scope.The 30% and 50% gross-rent-to-income thresholds use units with a computable ratio. Not-computed units are excluded from that denominator and reported separately. The 50% group is nested in the 30% group; do not add the shares.The release includes raw aggregate source files, a CSV, chart with alt text, source hashes, rebuild scripts and CITATION.cff. All 11 source estimate/margin-of-error pairs are retained; derived percentage margins of error are not calculated. Displayed differences are not established as statistically significant.The gallery chart shows ten metros selected by the largest computable renter-unit denominators and displayed alphabetically. It is not a selection of the ten highest rent-burden shares.Six formula tests and a raw-data rebuild pass in four Linux/Windows and Python 3.12/3.13 CI jobs. Original code is MIT licensed; the Census data retain their source-specific reuse qualifications. Developed with AI assistance. These are survey estimates, not current asking rents, investment rankings, property yields or forecasts.Versioned method, data and code: <a target="_blank" rel="noopener noreferrer nofollow ugc" class="break-all link-break text-gray-500 hover:underline" href="https://github.com/ahmadreza-smdi/metro-rent-burden/releases/tag/v1.0.0">https://github.com/ahmadreza-smdi/metro-rent-burden/releases/tag/v1.0.0</a>Author and official profiles: <a target="_blank" rel="noopener noreferrer nofollow ugc" class="break-all link-break text-gray-500 hover:underline" href="https://a-samadi.com/about.html">https://a-samadi.com/about.html</a>

Metro rent burden: ACS 2024

Evidence Note is an offline claim/source note editor by Ahmadreza Samadi, for AI for property decisions.Record one claim, its source and dates, missing evidence and the next check. Export a readable HTML note, Markdown or JSON you can reopen locally. Blank fields remain Not recorded.Download the ZIP, extract it and open index.html in your browser. No account, server, installation or API key is needed. Save JSON before closing or reloading; unsaved fields are not retained.You record whether a source supports, contradicts or leaves a claim unresolved. The editor does not fetch or verify sources, property identity, evidence adequacy or decision readiness. The included property, source and dates are fictional. This is an AI-assisted educational note organizer, not a company deployment, appraisal or certified report.Source and usage notices: <a target="_blank" rel="noopener noreferrer nofollow ugc" class="break-all link-break text-gray-500 hover:underline" href="https://github.com/ahmadreza-smdi/evidence-note">https://github.com/ahmadreza-smdi/evidence-note</a>Download v0.1.0: <a target="_blank" rel="noopener noreferrer nofollow ugc" class="break-all link-break text-gray-500 hover:underline" href="https://github.com/ahmadreza-smdi/evidence-note/releases/download/v0.1.0/evidence-note-builder.zip">https://github.com/ahmadreza-smdi/evidence-note/releases/download/v0.1.0/evidence-note-builder.zip</a>About Ahmadreza Samadi: <a target="_blank" rel="noopener noreferrer nofollow ugc" class="break-all link-break text-gray-500 hover:underline" href="https://a-samadi.com/about.html">https://a-samadi.com/about.html</a>

Evidence Note

An offline Python CLI and editable experiment workbook by Ahmadreza Samadi for measuring full workflow cost per accepted result. The CLI has no dependencies; the workbook can be used without Python.The three workbook sheets — Compare, Results and Attempts — pair manual and AI outcomes for the same batch. Record every retry and failed attempt, labor effort, elapsed time and non-labor cost. Capacity: 10 paired results and 30 attempts. Replace all fictional rows before using it for your own experiment.The worked example is fictional: manual review costs 24 for three accepted results (8 each); the AI workflow costs 18.40 for two accepted results (9.20 each). Lower total spend alone does not establish a better workflow. The gallery shows these fictional workbook inputs and outputs.Acceptance is caller-defined, not independent verification of correctness. Unknown costs must not become zero; zero accepted results leave unit cost undefined. This project does not measure ROI, establish a company outcome or recommend a model.MIT licensed and developed with AI assistance and synthetic tests. Excel desktop and Google Sheets native recalculation have not been tested.Download the v0.1.1 workbook: <a target="_blank" rel="noopener noreferrer nofollow ugc" class="break-all link-break text-gray-500 hover:underline" href="https://github.com/ahmadreza-smdi/ai-workflow-cost/releases/download/v0.1.1/AI-Workflow-Experiment.xlsx">https://github.com/ahmadreza-smdi/ai-workflow-cost/releases/download/v0.1.1/AI-Workflow-Experiment.xlsx</a>Source, CLI instructions and release: <a target="_blank" rel="noopener noreferrer nofollow ugc" class="break-all link-break text-gray-500 hover:underline" href="https://github.com/ahmadreza-smdi/ai-workflow-cost">https://github.com/ahmadreza-smdi/ai-workflow-cost</a>Method: <a target="_blank" rel="noopener noreferrer nofollow ugc" class="break-all link-break text-gray-500 hover:underline" href="https://a-samadi.com/writing/ai-cost-per-verified-result.html">https://a-samadi.com/writing/ai-cost-per-verified-result.html</a>Maintainer: <a target="_blank" rel="noopener noreferrer nofollow ugc" class="break-all link-break text-gray-500 hover:underline" href="https://a-samadi.com/about.html">https://a-samadi.com/about.html</a>

AI workflow cost ledger

A standard-library Python CLI by Ahmadreza Samadi for checking video publication dates in local HTML JSON-LD and optional video sitemaps. It reports impossible dates, missing timezone information, future aware instants and inconsistent instants for repeated exact video URLs.It reads inputs without changing them, makes no network requests and supports text or JSON diagnostics. Strict datetime, required sitemap dates and required video presence are separate policy options.MIT licensed, developed with AI assistance, with synthetic behavioral tests. Syntax and consistency checks do not prove actual first publication, complete schema compliance, indexing eligibility or ranking improvements.Documentation and source: <a target="_blank" rel="noopener noreferrer nofollow ugc" class="break-all link-break text-gray-500 hover:underline" href="https://github.com/ahmadreza-smdi/video-date-lint">https://github.com/ahmadreza-smdi/video-date-lint</a>Maintainer: <a target="_blank" rel="noopener noreferrer nofollow ugc" class="break-all link-break text-gray-500 hover:underline" href="https://a-samadi.com/about.html">https://a-samadi.com/about.html</a>

Offline video publication-date linter

Two browser-local calculators by Ahmadreza Samadi. Compare rental income with annual operating costs, debt payments and upfront cash, or estimate buyer-paid costs for a completed Dubai residential purchase. Unknown inputs stay blank rather than becoming zero. Examples are fictional, and fees have a dated basis and quote-dependent conditions.Create an explicit result link, print the inputs and results, or embed a compact calculator with personal attribution. Anyone with a result link can read its inputs; recipients must review quote confirmations again. Compact embeds have no site analytics.Rental cash flow: <a target="_blank" rel="noopener noreferrer nofollow ugc" class="break-all link-break text-gray-500 hover:underline" href="https://a-samadi.com/tools/rental-cash-flow.html">https://a-samadi.com/tools/rental-cash-flow.html</a>Dubai purchase costs: <a target="_blank" rel="noopener noreferrer nofollow ugc" class="break-all link-break text-gray-500 hover:underline" href="https://a-samadi.com/tools/dubai-purchase-cost.html">https://a-samadi.com/tools/dubai-purchase-cost.html</a>These are decision-support tools, not property valuations, observed investment returns or lending assessments.

Property Calculators

An interactive study by Ahmadreza Samadi across 393 US metropolitan areas. It compares illustrative ownership cash budgets with HUD FY2027 two-bedroom gross rent estimates and Census ACS2024 median owner-occupied home values. These describe different housing populations, not matched properties or observed investment returns.Edit assumptions, inspect separate HUD rent areas and owner-value sensitivity, and download the scenarios as CSV. The site includes methodology, source notes and attributed chart embeds.Code and reproducible data notes: <a target="_blank" rel="noopener noreferrer nofollow ugc" class="break-all link-break text-gray-500 hover:underline" href="https://github.com/ahmadreza-smdi/rent-own-metro-study">https://github.com/ahmadreza-smdi/rent-own-metro-study</a>The original code is MIT licensed; federal-source and font reuse qualifications are documented separately. CITATION.cff and quarterly refresh instructions are included.

Rent and ownership scenarios — 2026 metros

Before You Build the AI is a free interactive field guide for turning an AI idea into a decision, an evidence plan and a small first experiment.The worksheet helps you define the next action, identify the evidence it needs and decide what to test before committing to a full product. It includes illustrative property-research and support-triage scenarios, plus a blank starting point.Readers can export a decision brief as text or print it to PDF. The worksheet runs in the browser without sending the entered answers to a server.Built with HTML, CSS and JavaScript, with English, Persian and Arabic editions. It is a structured thinking aid; it does not validate evidence or calculate an AI-readiness score.