AdSwipe — get paid for honest attention

Instead of being targeted for free, you’re the judge. Brands pitch. You swipe. You get paid when you leave real feedback. Consent turns noise into signal.

PrototypeAnti-bot friction: mandatory reasons + textPayout: €0.05+
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Tutor Trail

Tutor Trail

Education

Micro-lessons that match your week and your brain.

ClinicCalm
HealthZurich

ClinicCalm

Therapy scheduling + secure notes for small practices.

Admin down. Care up.

ClinicCalm helps therapists manage appointments, reminders, secure patient notes, and invoices. Designed for small clinics.

Secure notesRemindersSmall practice

Advertiser offer

Free migration from Calendly-like tools(From €19/mo)

Swipe left = “No”. Swipe right = “Yes”.
You must submit feedback after each swipe. No feedback = no next card.

Your wallet

Prototype payouts — real money requires server-side validation.

Guest

Balance

€0.00

Today earned (cap)

€0.00 / €2.00

Remaining: €2.00

You’re browsing as a guest. Your swipes can still be logged, but payouts require login.
Loading wallet…

How payout works

Designed to avoid paying bots for mindless swipes.

Why friction?

Paying for raw swipes creates farms. Paying for structured feedback creates signal.

  • Swipe is free (no payout).
  • Submit required feedback (chips + note) → €0.02
  • If you swiped YES → bonus €0.03
  • If you clicked Open → bonus €0.10
  • Daily cap → €2.00
Pro move: advertisers would pay more for verified intent (e.g., “booked demo”) and less for passive attention.

Session stats

Local session metrics (not authoritative).

Reviewed

0 / 10

Current

Health

Keyboard: / . Swipe: drag card left/right.

Roadmap (real market readiness)

The parts you’ll need to make this non-cheatable.

Server-side payouts

Move payouts to Cloud Functions / API. Validate rate limits, uniqueness, device attestation, advertiser budgets, and fraud scoring.

Advertiser billing + budget

Prepaid budgets, per-signal pricing (feedback vs click vs conversion), and dispute tooling.

Privacy + consent model

Clear user controls: categories, frequency, data usage. This is your moat: trust.