TrustedClicks

What TrustedClicks is

Third-party directories describe TrustedClicks as an AI platform for ad safety and click-fraud defence: visitor addresses get scored in real time, and fraudulent or automated clicks are blocked before they eat the budget.

A direct caveat: the official site answered with a Cloudflare DNS error when this was written, leaving it unreachable, so everything below rests on directory entries — confirm it all on the live site once the error clears.

What you can do with it

According to those summaries, each visitor's address passes through an AI risk model that assigns a precise, moving score; malicious clicks and bot traffic are then flagged or blocked ahead of spending. The positioning is address scoring for fraud and bot defence, built for teams on both the ad-serving and marketing sides.

Because the vendor's page was down over a DNS conflict, no feature list, prices, or terms of service could be verified here — treat the capability notes as indicative, and confirm product, cost, and data handling with the vendor directly.

Who it is for

Advertising and growth teams with paid campaigns running, wanting invalid traffic filtered and their budgets shielded from bots and fraud.

Anyone needing contractual guarantees should hold off until the site is live and terms exist.

Networks reselling traffic gain most, since quality disputes are their daily reality.

Networks reselling traffic gain the most, since quality disputes are their daily reality.

Agencies billing on conversions gain most, since fraudulent clicks distort their numbers too.

What to watch out for

The vendor's site was unreachable, so nothing should be relied upon until the product loads and is confirmed running.

Scoring and blocking on addresses touches visitor data and can mistakenly block real users — look into accuracy, the appeal route, and the legal basis for processing addresses. With no reachable terms or prices, secure both in writing before linking ad accounts or sending traffic through the system.

IP ranges shared by offices or universities produce false positives — expect appeals.

Shared IP ranges in offices or universities produce false positives — expect appeals.