CyberWatch AI exists to catch that moment: the few seconds before someone clicks, pays or replies to a message that only looks real. For organizations, it is a security console that tests how your people respond to real attacks, trains the gaps it finds, and shows you exactly where you stand. For anyone, it is a free scanner that gives a straight answer about a suspicious link or message, in any language.
Scams stopped looking like scams. The grammar is clean, the logos are right, the sender looks familiar, and the request is urgent enough that checking feels rude. Fake payment confirmations, job offers with an upfront fee, a message that appears to come from your bank — all engineered to bypass careful judgement rather than defeat a firewall.
We kept watching people we know lose money to attacks that were obvious in hindsight. Not because they were careless, but because nobody had a fast, honest way to ask is this real? without feeling foolish. That question is what CyberWatch AI answers.
Inside companies we saw the same thing at scale. Budgets went on firewalls and software while the attack walked in through an inbox, and nobody could say how their own staff would respond until the day it mattered. So we built the console to answer that too: test it safely, fix what the test finds, and measure whether it is getting better.
CyberWatch AI is built by two brothers who work in security operations. The detection logic comes from attacks they respond to in their day jobs.
Divine spends his working days monitoring threats, analysing attack patterns and responding to incidents before they become breaches. That is where the detection engine came from — not from a threat-intelligence feed, but from seeing which tricks actually land on real people, week after week. He built the first version because the advice he kept giving colleagues deserved to be available to everyone.
LinkedIn profile
Gideon is the reason CyberWatch AI makes sense to people who are not security professionals. As an analyst he had used plenty of tools that were powerful and unusable — too technical, too cold, too full of jargon to act on. He owns how the product thinks and speaks. If a scan result is clear enough for your grandmother to act on immediately, that is his work.
LinkedIn profileRealistic phishing simulations show who opens, clicks and reports, without anyone being put at risk.
Short lessons go to the people and topics the tests point to, not a yearly slideshow for everyone.
One security score and plain reports show management what changed and what to do next.
Every member can also check anything suspicious before acting on it, and report it to their security team in one step. The checker reads the content itself rather than matching a list of known scams, so it works in any country and any language, including attacks that are days old. The same checker is free for anyone to use.
A short demo walks you through the console. Or check something suspicious right now, no account needed.