Traditional phishing platforms make administrators think in campaigns. They select templates, choose target groups, set difficulty, build schedules, review results, and then decide what should happen next, over and over. Graybait replaces that cycle with a policy. Using agentic AI and each employee's evolving Human Risk Profile, it decides what every person should face next, and why.
Employees who keep spotting simple attacks move on to more sophisticated scenarios, at their own pace.
Each simulation uses the lure most relevant to that person's role, context, and history with Graybait. Over the year it works through every attack vector for each employee, retiring a methodology once they have beaten it, so every person is tested across a wide variety of attacks.
Graybait learns which pressures work on each person, such as authority or urgency, and keeps testing until that weakness closes.
Each employee is tested when and as often as their risk calls for, always within the limits you set.
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Setting up Graybait takes four steps. After that, the program runs on its own for twelve months, and your team steps in only when it chooses to.
01
Bring in your employees and groups so Graybait knows who it is building resilience for.
02
Define the boundaries Graybait must respect: who is included, how often anyone can be tested, and which scenarios are off-limits.
03
Tell Graybait what success looks like, so every decision it makes moves your workforce toward it.
04
Switch it on. Your 12-month adaptive phishing program is now running.

At the center of Graybait is a loop that keeps running. Every simulation teaches it something about the person who received it, that lesson changes their risk profile, and the updated profile decides what comes next. Over months, observed weaknesses become strengths, one employee at a time.
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Graybait follows how each employee responds to every simulation: whether they report it, ignore it, click it, or enter credentials.

Each response updates the employee's Human Risk Profile, building a detailed picture of their individual vulnerabilities, including the psychological triggers that work on them.

Agentic AI selects or generates the next simulation for that person and sets its difficulty, theme, trigger, and timing without an administrator choosing any of them.

Graybait tracks each person's susceptibility over time, so improvement appears as a trend you can report.

When someone masters simple attacks, the difficulty rises. When someone keeps falling for authority-based or credential lures, Graybait concentrates on those until they improve.

The cycle continues all year, with no campaign, no schedule, and no administrator decision required.
Graybait exists to reduce each individual's measurable susceptibility, and its reporting follows that objective employee by employee.
How each employee's likelihood of falling for an attack is changing month by month, measured continuously across the year.
Which psychological triggers and attack types each person has been tested against, which they now resist, and which still need work.
How far each employee has moved from foundational scenarios toward sophisticated ones, and how quickly they got there.