About FakeFind
Built to protect shoppers after the tools they trusted disappeared.
Why Andrew Kane Built FakeFind
My name is Andrew Kane, and I built FakeFind because I got burned.
In mid-2025, I was shopping for a pair of wireless earbuds on Amazon. The product had 4.7 stars and over 2,000 reviews. I bought them based on those reviews. They arrived, lasted three weeks, and stopped working. When I went back to look more carefully, the review history told a different story — hundreds of reviews had appeared within a two-week window, many using nearly identical phrasing.
Around the same time, Mozilla announced it was shutting down Fakespot — the tool that most shoppers had relied on to catch exactly this kind of manipulation. The shutdown left more than 10 million users without a way to verify what they were reading.
I had a background in software development, a frustration I couldn't shake, and a gap in the market that was obvious. FakeFind was the result.
The goal was simple: give shoppers the same kind of protection Fakespot offered, but better — more transparent about what it detects, faster to use, available without an account, and built to keep pace with the AI-generated fakes that older tools weren't designed for.
What the Fake Review Problem Actually Looks Like
The scale of review manipulation on Amazon is difficult to grasp until you see the data:
- • Amazon proactively blocked hundreds of millions of suspected fake reviews in 2025 alone, per Amazon's own Trustworthy Shopping Experience Report
- • Fake reviews cost online consumers an estimated $770.7 billion worldwide in 2025 — roughly $125 per shopper per year wasted on misleading purchases (Capital One Shopping Research, 2026)
- • 82% of consumers say they encountered at least one fake review in the past 12 months (BrightLocal, 2025)
- • Up to 43% of Amazon reviews on bestselling products have been identified as suspicious in category analyses (Fakespot, prior to shutdown)
The tactics have also evolved. It's no longer just people paid to write 5-star reviews. Sellers today use large language models to generate natural-sounding review text at scale, run coordinated campaigns through private Discord and Telegram groups, and exploit a technique called "review hijacking" — where a high-rated listing's reviews get carried over to a completely different product.
FakeFind was built specifically to catch these modern patterns, not just the obvious ones.
How FakeFind Works
FakeFind's AI analyzes Amazon reviews across multiple dimensions simultaneously — something no human reader can do efficiently at scale.
Language analysis
Detects templated phrasing, suspiciously uniform sentiment, and the linguistic fingerprints AI-generated text tends to leave behind.
Timing analysis
Genuine reviews arrive organically. Fake campaigns create detectable spikes — large clusters of reviews appearing within hours or days of each other.
Pattern detection
Review hijacking, repetitive reviewer behavior, off-topic content, and inflated rating bursts all leave statistical signatures our model identifies.
Aggregated output
Signals combine into three outputs — a Trust Score (1–10), an Adjusted Rating discounting suspicious reviews, and a plain-English summary.
What Happened to Fakespot and ReviewMeta
Fakespot, operated by Mozilla after its 2023 acquisition, shut down permanently on July 1, 2025. No migration path was offered. No replacement was announced. Over 10 million users lost access overnight.
ReviewMeta, which had offered Amazon-specific review analysis and adjusted ratings, went offline in early 2026 without explanation.
The shutdown of both tools left a real gap in consumer protection. FakeFind launched in that gap. We're not affiliated with either service, but we built FakeFind to carry forward what made them valuable — and to address their limitations.
Our Commitment
FakeFind is free. Not "free with limits" or "free until you need the good features." Free, with no account required, no usage caps, and no data collection beyond what's necessary to store scan results for shareable URLs.
We keep it running through Amazon affiliate links shown alongside analysis results. You don't pay anything. We don't share or sell your data.
If you want to reach us, visit the Contact page.
Try FakeFind Now
Paste any Amazon product URL and get your Trust Score, Adjusted Rating, and full review authenticity report — free, no account required.
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