Health, home and travel decision

Flighty Pro

A competent developer can build a basic flight tracker and alerts system in ~one week, but replicating Flighty’s polished native apps, large-scale coverage, and production ML quality would require much more effort and data.

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You pay

$4.99/mo

$60/yr

Read off the official pricing page.

You’d pay instead

$50one-off30 h to build

$50/mo10 h/mo upkeep

On cash alone, building overtakes the subscription at 11 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 Flighty Pro alternatives, with the arithmetic →

What a replacement has to do

  • Collect live flight status and positions, match inbound aircraft to scheduled flights, run a simple delay-prediction model, send push/email alerts to subscribers, display flight status on a lightweight web/mobile UI.

What it still won’t have

  • Polished native iOS/watchOS UI and Apple-grade UX
  • Proprietary delay-prediction model quality and tuned heuristics
  • Coverage/scale and curated airport 'Airports' product
  • Brand recognition and platform integrations Flighty ships

What remains hard

  • Brand trustApple Design Award Winner 2023
  • Execution qualityThe world’s most powerful flight tracker.
Read the build prompt

First-year cost

Keep paying

Paying is—cheaper in year one.

On cash alone, building overtakes the subscription at 11 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

—

—

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-tracking backend and web client using Node.js (Express), Postgres, and React. Scope: ingest live aircraft positions and flight status from an aviation data API, normalize and store flights and inbound-aircraft matches, implement a simple delay-prediction service (logistic regression or rules combining inbound-lateness and ATC advisories), REST endpoints to subscribe/unsubscribe and fetch flight timelines, push/email notification integration (Firebase Cloud Messaging and SendGrid), and a responsive React UI to view a flight timeline and manage notifications. Out of scope: native iOS/watchOS apps, large-scale multi‑region deployment, and a commercial-grade ML training pipeline. Include error handling, input validation, unit tests for core matching/prediction logic, and deployment scripts for a single-host setup (Docker + a managed Postgres).
How we checked3 sources · 3/3 runs agreed · evidence score 67

How the score was reached

  • Partly verdict base52
  • An open-source build was found+5
  • 3 cited sources+3
  • Price verified on pricing page+3
  • 3/3 assessment runs agreed+4
  • Evidence score67

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 read off the page✓ 3 independent runs, one answer✓ Citations limited to fetched pages! 2 moats quoted from the page