Health, home and travel decision

Homefast.cy

A motivated developer can reproduce the core monitoring+alerts+feed using existing OSS components (see the ai-real-estate-assistant repo), but building and hardening the always-on scraping, reliable SMS delivery, and polished UX to match the paid product is a multi-week effort and maintenance burden — so keep paying if you need turnkey reliability and speed.

Visit website

Built by Mehdi Ben Haddou, who ships 3 products in this index

You pay

$19/mo

$228/yr

Read off the official pricing page.

You’d pay instead

$100one-off72 h to build

$140/mo6 h/mo upkeep

On cash alone, building overtakes the subscription at 8 seats.

No open-source build does this yet

Nothing published replaces this one, so a replacement starts from an empty file. Here is what it would have to cover.

What a replacement has to do

  • Continuously scrape three listing sites, dedupe and store listings, score each listing vs. market data, compute commute times, surface matches in a shared feed/CRM, and send prioritized SMS alerts.

What it still won’t have

  • Polished 24/7 monitoring and reliability for scrapers at scale
  • Built-in SMS delivery workflow and negotiated SMS throughput
  • Refined AI scoring tuned to local Cyprus market
  • Polished UX (map, shared feed, voting, CRM) and support
  • Monitoring, retries, and anti-blocking for scraping fragile third‑party sites

What remains hard

  • Product polish and ongoing maintenance
Read the build prompt

First-year cost

Keep paying

Paying is—cheaper in year one.

On cash alone, building overtakes the subscription at 8 seats.

Paid seatsseats

Money you would actually spend

Keep paying
—

Subscription price × seats × 12

Build it
—

AI build —APIs + hosting —

Time you would spend

—

—

What you would spend

What we assumed

The verdict above measures whether you could build it. This one is only about money.

Runnable build prompt

Not run yet
Build a minimal Homefast replacement as a hosted app using: Next.js for frontend, Postgres on managed provider (Supabase or Neon) for storage, FastAPI (or Express) backend, Playwright-based scrapers per source, Redis for job queue, OpenAI-compatible LLM calls for price/feature analysis, Google Maps (or OpenRouteService) for commute times, and Twilio for SMS. Core features in scope: (1) register and save up to 5 active searches, (2) scrapers for Bazaraki/Home.cy/Zyprus that run on a scheduler and dedupe results into Postgres, (3) match & scoring pipeline that runs an LLM analysis and stores the score, (4) feed UI with map pins, listing cards and basic CRM columns, (5) scheduler that sends SMS alerts to a single phone with summary and link. Out of scope: multi-tenant billing, advanced rate-limiting/anti-bot scraping at scale, enterprise team/permissions, and polished mobile app. Include tests for scrapers, API endpoints, and job workers; add error handling, retries, logging, and a basic Docker Compose for local dev and a Kubernetes-ready Dockerfile for production.
How we checked2 sources · 2/3 runs agreed · evidence score 56

How the score was reached

  • Partly verdict base52
  • 2 cited sources+1
  • Price verified on pricing page+3
  • Evidence score56

The base comes from the verdict. Everything under it is a check that either happened or did not, and each one is a fact frozen in this record rather than a judgement made at render time - so the same evidence always produces the same number.

How scoring works →

Cited sources · 2

Every page the run actually retrieved.

Integrity checks

What held up, and what did not.

✓ Price read off the page! 2 of 3 runs agreed; the verdict is the majority✓ Citations limited to fetched pages! 1 moat recorded