AI coaching for compliance teams
Compliance you don’t just read.
You say it.
Your teams practise the conversations where the rules really count: reporting a data breach, asking where money comes from, questioning a new tool. With AI characters who react like real people, and feedback after every conversation.
No obligation. We show you Kaite with your teams’ own conversations.
The conversations that matter
Rules only work in conversation.
Most people know the policy. It gets hard the moment they have to say it out loud: to a colleague, a client or their own team. With Kaite, your people practise exactly these moments.
Reporting incidents
Naming a slip clearly instead of playing it down, and taking the right route, even when a colleague would rather stay quiet.
Asking awkward questions
Asking clients where money comes from and what it’s for, without damaging the relationship.
Saying no without blocking
Questioning a new tool or a quick shortcut, and still offering a way forward.
From the Kaite Library
Scenarios your teams can practise today.
Real scenarios from the Library, from data protection to anti-money laundering. Open one and try it yourself, no account needed.
Isabelle
Team member
An 8% pay gap, and an upset team member
Isabelle has read her pay report: she earns 8% less than her peer group and believes it’s discrimination. The gap is justified by a specialisation she doesn’t have yet. Take her concern seriously, explain the reason and show her the way to the next level.
Your goals
- Acknowledge her concern without getting defensive
- Explain the objective criteria
- Name the specific difference
- Show the path to the next level
Daniel
Colleague
Wrong recipient
A colleague admits he sent a file with client data to the wrong client, and wants to let it go because the recipient “seems nice”. Name it as a data breach and get it reported straight away.
Your goals
- Find out what data was sent
- Name it as a data breach
- Explain why every hour counts
- Get it reported now
Ashley
Long-standing business client
Unusual cash deposits
A long-standing business client has made several unusual cash deposits that require an anti-money-laundering review. Ask about their origin and purpose clearly and respectfully, without sounding accusatory.
Your goals
- Build trust before raising the deposits
- Explain why the bank has to ask
- Clarify where the money comes from and what it’s for
- Keep the relationship intact
Priya
Customer
“Delete everything I gave you”
A furious customer keeps getting marketing emails after unsubscribing. Now she demands that all her data be deleted and a full copy of it, by tomorrow. Stay calm and route the request properly, without promising what you can’t decide.
Your goals
- Work out what kind of request this is
- Protect the data before acting
- Route it through the right process
- Calm things down without overpromising
Chloe
Team member
“Everyone’s already using it”
A keen team member wants to roll out a US collaboration tool quickly and sees no need for a compliance check, because other departments use it too. Guide her through the decision without blocking the idea.
Your goals
- Explain why “everyone uses it” isn’t enough
- Clarify where the data actually goes
- Point out that the UK freelancers may need their own check
- Route it through the internal review
Isabelle
New team member
Anti-money-laundering, explained to a sceptic
A new customer service employee thinks the anti-money-laundering rules are excessive red tape. Explain why they matter in her daily work, without compliance jargon and without getting defensive.
Your goals
- Acknowledge the scepticism
- Explain what the rules are for
- Clarify her responsibilities
- Make it feel like protection, not paperwork
Your policies and cases are specific? We build scenarios from your own code of conduct. See Kaite Studio
Your own scenario
Your typical case. Ready to practise in 48 hours.
A case from your code of conduct that keeps going wrong in practice? We turn it into a draft scenario and walk you through it in the demo.
Free and without obligation.
Describe the case
In a first call or a few lines: who talks to whom, and which rule is at stake.
A draft within 48 hours
Our editors build the scenario with its character, goals and feedback criteria, based on your policy.
Try it together
You test the scenario yourself, then decide how to go on.
How a practice conversation works
Three steps, and as many second tries as your teams need.
- 1
Choose a scenario
From the Library or built from your policies, in the browser or embedded in your learning platform.
- 2
Have the conversation
Type or dictate. The character’s mood reacts to every sentence, and your goals tick off as you reach them.
- 3
Get your feedback
Strengths, what to try next time and how the mood developed, as a report. Then try again.
Scenario completed
Feedback report: Daniel
Summary
You named the incident clearly and still backed Daniel up. Next time, say sooner who is responsible.
Analysis
Named clearly
You didn’t play the slip down. You called it a data breach.
“That’s personal data. So it’s a data breach.”
Who’s responsible
For a long time Daniel didn’t know whom to turn to. That drags out the hesitation.
Try: “Our data protection team handles this. Let’s go over together now.”
Your skill profile
Key skill dimensions based on your responses.
Conversation history
The AI character's mood over the conversation.
In everyday work
Practise, don’t just sign.
No training date
No mandatory seminar, no click-through module. People practise when it suits them, as often as they need.
13 languages
International teams practise in their own language. The AI character answers in the language they choose.
In the browser or your LMS
Nothing to install and no personal account. Scenarios can be embedded in your learning platform or intranet.
Frequently asked questions
Which industry are you in?
This helps us suggest scenarios your team will recognize.