Health, home and travel decision

Going

A capable developer can build a useful flight-alert prototype (price monitoring + alerts) in ~1 week, but reproducing Going’s scale, curated mistake-fare sourcing, and mobile/user-base advantages is not realistic for a solo builder.

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You pay

$4.08/mo

$49/yr

Not verified against a pricing page.

You’d pay instead

$50one-off30 h to build

$70/mo10 h/mo upkeep

On cash alone, building overtakes the subscription at 19 seats.

Open-source builds that already do this

Every project below is open source and already does this job today. Fork one, self-host it, or take the parts you need - the build prompt further down assumes an empty file, and this is the shortcut past that. Licences differ; check the one on each card before you ship. All Going alternatives, with the arithmetic →

What a replacement has to do

  • Users create/watch routes or airports → background job monitors fares → detection rules flag deals/mistakes → send email/push alerts with booking links → users book externally.

What it still won’t have

  • Going’s historical deal database and tuned detection heuristics
  • Mobile app distribution and existing user base
  • Curated mistake-fare alerts and editorial curation
  • Scale and reliability of millions of trackers

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 19 seats.

Paid seatsseats

Money you would actually spend

Keep paying
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Subscription price × seats × 12

Build it
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AI build —APIs + hosting —

Time you would spend

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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 flight-deal alert service using Node.js + Postgres + a background worker (Bull or Sidekiq-like). In scope: (1) REST signup and watchlist API, (2) worker that polls a flight search API (e.g., Amadeus/Skyscanner) or scrapes Google Flights for configured routes, (3) price history storage in Postgres, (4) simple rule engine to detect >=20% drops or absolute thresholds and mark potential mistake fares, (5) send transactional emails via SendGrid and push notifications via Expo/Firebase, (6) single-page web UI to manage watchlist and view active deals, (7) error handling, retries, and unit tests for core components. Out of scope: mobile native apps, large-scale distributed scraping infrastructure, editorial curation, paid tier billing. Include logging, alerting for broken data sources, and automated tests for detection logic.
How we checked3 sources · 3/3 runs agreed · evidence score 64

How the score was reached

  • Partly verdict base52
  • An open-source build was found+5
  • 3 cited sources+3
  • 3/3 assessment runs agreed+4
  • Evidence score64

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 · 3

Every page the run actually retrieved.

Integrity checks

What held up, and what did not.

! Price not confirmed on the page - this pricing page renders its price in the browser✓ 3 independent runs, one answer✓ Citations limited to fetched pages! 1 moat recorded