Scam AI is a deepfake detection and AI scam prevention tool that helps users verify videos, voices, and messages in seconds. It provides automated analysis to identify potential scams.
Business Specialistscam.aiTracked since 2026-08-211 discovery source
1.8KBacklinks
180Referring domains
23Domain authority
+5.9%Referring domains · 90 days
Authority & distribution
How strong is Scam AI’s web footprint?
Backlinks measure accumulated distribution; referring domains show how broadly that authority is spread. Both are observable on the open web, so both are published for every product here.
Backlinks
1.8KCurrent snapshot
Referring domains
180Current snapshot
Authority
23Domain authority · category median 22
90-day move
+5.9%Referring domains, last 90 days
At 23, Scam AI sits above the 22 median for its category.
Trajectory · Pro
The counts above are the latest of 370 daily observations. The curve through them is on the full profile.
Traffic makes more sense when you can connect it to the actual product promise.
“Scam AI”
Scam AI is a deepfake detection and AI scam prevention tool that helps users verify videos, voices, and messages in seconds. It provides automated analysis to identify potential scams.
Business SpecialistSeen 2026-08-21 → 2026-08-21Coverage tier C
What we have measured
4 of 8 signal groups are available for this product: identity, authority and backlinks, AI referrals, search demand.
Not measured for this domain: traffic and engagement, audience demographics, country distribution, acquisition mix. Those sections are left out of the page rather than filled with estimates.
Canonical website: https://www.scam.ai
Observed across 1 discovery source.
Research questions
What the evidence answers about Scam AI.
Every answer is tied to a source we collected, and the questions with no evidence behind them are left unanswered rather than guessed.
What problem does Scam AI solve, and how does it work?
Scam AI is a deepfake detection and AI scam prevention tool. It helps users verify videos, voices, and messages by providing automated analysis to identify potential scams and AI-generated content.
In what situations is Scam AI used?
Scam AI is used for verification in situations like KYC (Know Your Customer), claims processing, and content moderation. Its use cases include detecting AI images, deepfakes, forged documents, and synthetic participants in live meetings.
What features and services does Scam AI offer?
Scam AI offers detection models for images, videos, documents, and live calls (via Halo). Its features include pixel-level artifact detection, face-swap boundary detection, region-level forgery localization on documents, and liveness checks. It provides shareable stamped verdict cards with evidence attached to every verdict.
How is Scam AI priced or packaged?
Scam AI operates on a prepaid credit system with no per-call billing. The evidence shows specific credit costs for different scans, such as 1 credit per frame for image checks and 2 flags for deepfake scans.
Who is Scam AI for?
Scam AI is for businesses and developers needing to combat AI-powered scams. It provides an API platform for security and verification tasks, as indicated by its categorization as a specialist security platform.
5 of 6 research questions are answered for this product. The rest need source evidence we have not collected yet, so they are left unanswered rather than guessed.
Behind the lock
Unlock full Scam AI intelligence.
Backlink trajectoryThe figures above are the latest observation. The daily curve behind them holds 370.
AI referral detailHow much traffic assistants send.
Search structure and ranking depthOrganic against paid, brand against non-brand, and how many keywords rank in the top three against the long tail — which is what decides whether the demand is portable or tied to the name.
The rest of the marketPage through every leaderboard 100 rows at a time, put any five products side by side, and query the whole dataset over API / MCP.
Worldwide estimates · Data period 2026-05-01 → 2026-07-31. Figures are measured estimates intended for market research. Signals we have not measured for this domain are omitted, never estimated; a measured zero is still reported as zero. How this was measured