AI coaching for feedback conversations

“Have you got a minute?” Practise what comes next.

Your people practise giving feedback clearly and respectfully, and taking it themselves. With AI characters who react like real people, without an audience and with feedback after every conversation.

No obligation. We show you Kaite with your team’s own conversations.

The conversations that matter

Feedback rarely fails on content. It fails on the first sentence.

Most people know what they want to say. It gets hard in the moment itself. With Kaite, your people practise exactly that moment.

Criticism that lands

Name a behaviour specifically, without the other person shutting down or having to justify themselves.

Feedback between peers

Raise what isn’t working as an equal, without authority and without straining the working relationship.

Your own impact

Listen, ask and acknowledge how your own words came across, when the feedback is about you.

From the Kaite Library

Feedback conversations your team can practise today.

Real scenarios from the Library: with team members, in the team and between colleagues. Open one and try it yourself, no account needed.

  • Chloe

    Float nurse

    Feedback on a short-staffed shift

    On a short-staffed shift, a stressed float nurse skipped hand hygiene and left charts unfinished. When you raise it, she snaps back. Acknowledge the pressure without letting the safety standard slide.

    Your goals

    • Name the moment and the behaviour
    • Explain the impact
    • Ask for her view
    • Agree on what happens next
  • Mehmet

    Talented team member

    The feedback conversation you’ve been avoiding

    Mehmet works hard, but his last two project updates came in late and both needed rework. Give him clear feedback without getting pulled into blame or defensiveness.

    Your goals

    • Describe the behaviour you saw
    • Explain the impact on the team
    • Ask for his view and listen
    • Agree on next steps
  • Isabelle

    Team member

    Quick feedback after the team meeting

    You asked Isabelle to stay back after the meeting. Tell her what worked, what didn’t and what you’d like to see more of, and agree on a clear way forward.

    Your goals

    • Start positive and stay constructive
    • Give clear, concrete feedback
    • Encourage her to reflect
    • Agree on next steps
  • Isabelle

    Team member

    Your best performer has gone quiet

    Over six months Isabelle has withdrawn and does only the bare minimum. In her annual review, use active listening to find out what happened and rebuild trust.

    Your goals

    • Paraphrase to build a bridge
    • Name the emotion in the room
    • Ask open questions about the cause
    • Commit to a credible first step
  • Isabelle

    Team member

    “We’ve done that already”

    In a meeting you dismissed a team member’s idea with “we’ve done that already”. Now she feels her ideas are no longer welcome. Acknowledge the impact of your words and invite her ideas back in.

    Your goals

    • Acknowledge the impact
    • Show that ideas are welcome
    • Ask one curious question
    • Agree on a small next step
  • Alexander

    Colleague

    Feedback after an inappropriate joke

    At a team lunch, a colleague used the wrong pronouns for an intern and joked about it. Speak to him privately: describe what happened, explain the impact and ask for a specific change.

    Your goals

    • Create a safe setting
    • Describe the behaviour and its impact
    • Ask for a specific change
    • Agree on a follow-up

Your organisation has its own feedback model? We build scenarios around it. See Kaite Studio

Your own scenario

The feedback that keeps going wrong for you. Ready to practise in 48 hours.

Describe a typical situation. We turn it into a draft scenario and walk you through it in the demo.

Free and without obligation.

  1. Describe the situation

    In a first call or a few lines: who talks to whom, and what it’s about.

  2. A draft within 48 hours

    Our editors build the scenario with its character, goals and feedback criteria, based on your feedback model if you like.

  3. 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 you need.

  1. 1

    Choose a scenario

    From the Library or built for your organisation, in the browser or embedded in your learning platform.

  2. 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. 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: Isabelle

Summary

You named the behaviour specifically and invited Isabelle to reflect. Next time, agree on a fixed time to follow up.

Analysis

Specific, not general

You described an observable situation, not a trait. That made it possible for Isabelle to accept the feedback.

From the transcript

“Today you cut Mira off twice before she could finish.”

Agreement

At the end it was still open when you’d look at it again.

Try this

Try: “Shall we sit down briefly next week and see how it went?”

Your skill profile

Key skill dimensions based on your responses.

Relationship focusHigh
Collaborative toneHigh
Concrete examplesNeeds work
Next stepsNeeds work

Conversation history

The AI character's mood over the conversation.

Very satisfiedNeutralVery upset

In everyday work

Practise before the real conversation.

Right before the meeting

Run through the conversation once more, shortly before it happens. As often as needed, without an audience.

13 languages

Your people 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

In principle, yes, just without the seminar room and the audience. Your people have the conversation with an AI character who reacts like a real person, and repeat it as often as they like.

Which industry are you in?

This helps us suggest scenarios your team will recognize.