Consumer · Idea
AI fake-review detector
Paste any Amazon, restaurant, or SaaS review and find out what's actually real.
Build time
4–5 days
Monetization
Subscription
$5/month once the wedge converts; bulk-paste tier at $15/month.
Difficulty
One-week build
The problem
Online reviews are increasingly manipulated and untrustworthy.
The solution
Paste Amazon, restaurant, or SaaS reviews and AI estimates authenticity at a glance.
Who it's for
Online shoppers, restaurant-goers, and SaaS buyers who don't trust the star rating anymore.
Recommended stack
SuggestedSimple web wedge: paste box → score. Lovable ships the whole thing in days with auth, DB, and the AI Gateway built in — no separate vendor keys.
Platform
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LovableBackend
SupabaseIntegrations
Lovable AI GatewayPlumbing
Comes with Lovable — no setup.- Auth
- Email + Google (built in)
- Hosting
- Lovable
- Repo
- GitHub (auto-connected)
Feature ideas
- 1Suspicion scoringDetects repetitive patterns and unnatural language.
- 2Real-user highlightsSurfaces the most believable reviews first.
- 3Seller history analysisTracks sudden rating spikes over time.
First-week milestone
A web page where someone pastes 20 reviews and gets a per-review trust score plus a one-line explanation.
Distribution playbook
- Reddit threads in r/AmazonReviews, r/BuyItForLife, r/Frugal — show before/after on viral fake-review posts.
- TikTok carousel: 'Top 5 fake reviews this tool caught on Amazon last week.'
- Free paste-and-score wedge; paid tier for bulk pasted reviews and saved sellers.
Guardrails & risks
- Frame scores as 'signal', never a verdict — a wrong call on a real seller is a legal headache.
- Don't scrape Amazon directly; let users paste reviews or use their official API where it exists.
- Show the reasoning behind every score so users can override and trust the tool.
Validation signal
Watch repeat-paste rate in week one — if users come back to check a second product, the wedge works.
Trust Factor
People desperately want reliable opinions online.
webconsumertrust