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Need your team ready for the conversation that goes wrong?

A rehearsal written once stops teaching after a few runs. An AI training simulation changes the situation every time, plays the other person and scores how your team handled it.

The idea Our message has to reach people when we are not in the room

Start a conversation Try a run
One fixed script, run four times

  1. Run 01

    Reads the situation

  2. Run 02

    Recognises it

  3. Run 03

    Remembers the answers

  4. Run 04

    Recites them

Try a run

No two runs the same

Here is the fix in miniature. Each run draws who your learner meets, their mood and the complication, then follows one route through the conversation and scores it.

Worked example

Run 01

Difficulty 2 of 5

Who they meet
A customer whose delivery is a week late
Their mood
Calm, but short of time
The complication
The system you need has gone down

Their route

  1. Reply Acknowledged how they feel
  2. Then Asked what they need next
  3. Ended Calmer, with a next step agreed

Scored automatically

81/100

Empathy
90
Clarity
70
Outcome
82

Set against what good handling looks like, agreed with you.

Three short lists written for this page, combined at random. A real scenario is built with you from the situations your team finds hardest, and the route is whatever the learner says and does.

Run 01: A customer whose delivery is a week late. Calm, but short of time. The system you need has gone down. Overall score 81.

Why scripts wear out

A script teaches until it is learned.

Conventional VR training is written once. After a few runs a learner knows what is coming and starts recalling answers instead of reading the situation. Generative AI takes that limit away.

A fixed VR script compared with an AI-driven simulation
A fixed script An AI-driven simulation
The situation Written once and the same every run. Changes as it unfolds, so no two runs are alike.
The other person Says the same lines whatever the learner does. Played by a conversational AI character who answers what the learner says and does.
The difficulty Set on the day it was written. Rises or falls to match how the learner is coping.
The score Given by a facilitator who sat in on the session. Worked out from the decisions, words and actions the system saw, with feedback straight away.
After a few runs Learners recall the answers. Learners still have to read what is in front of them.

Where it fits

Where varied practice matters most

  1. Virtual reality

    Safety drills

    In an industrial setting the hazard can move every run, so teams practise judging the situation in front of them instead of learning one route to the exit.

    Explore Industrial

  2. Virtual reality

    Difficult conversations

    Appraisals, complaints, sales calls and care conversations, rehearsed with an AI character who reacts to tone as well as words. People can try the hard version again straight away.

    Explore Conversational AI Characters

  3. Augmented reality

    Maintenance on real machines

    Guided practice in inspecting and servicing machinery, with the steps laid over the equipment itself. It extends our augmented reality work for machinery maintenance.

    Explore Augmented Reality

How we work

From the hardest moment to a scored session

  1. Find the hard moments together

    We start with you on the situations your team finds hardest, and agree what good handling looks like so the score measures what matters to you.

  2. Build the world and the cast

    We build the setting, the characters and the ways each run can change, and you try it in a headset at every stage.

  3. Let people practise

    Learners practise alone, as often as they like, with feedback straight away. Your facilitators spend their time on coaching.

The case for it

More practice from every build

The case for immersive training rarely rests on one figure. It is a handful of things that add up, and a scenario that varies adds one more.

  1. More practice

    People come back to it more often, because it is different each time and they can do it on their own.

  2. Practice you could not stage

    They rehearse what would be dangerous or disruptive to set up for real, as many times as it takes.

  3. Less marking by hand

    The system scores every run, so facilitators coach instead of watching and marking.

  4. A build that stays useful

    A fixed scenario is spent once it is memorised. One that varies keeps producing new practice.

Training several people at once, in one space? The same thinking applies to venues. Explore Location-Based VR

Our projects

Made with our clients

See all projects

Questions

Good to know

  • How is this different from standard VR training?

    Standard VR training plays one scenario written in advance. An AI-driven simulation varies it each run, adjusts the difficulty to the learner and scores them automatically, so practice never becomes a memorised sequence.

  • Can people practise conversations as well as technical tasks?

    Yes. Learners can rehearse appraisals, complaints, sales calls or care conversations with a conversational AI character that responds to what they say and do.

  • Do we still need a facilitator in every session?

    Not in every one. Scoring and feedback are automatic, so learners can practise alone and as often as they like. Facilitators keep the coaching and the cases that need a person to look at them.

  • Does it work in augmented reality as well as virtual reality?

    Yes. Virtual reality suits places and situations that are fully simulated. Augmented reality suits guidance on the job, such as maintenance on real machinery.

Your idea

Talk it through with us

Tell us what you are trying to explain, launch or change. We will work out with you whether this is the right medium for it.

Book a meeting Start a conversation

Also in Immersive AI

Other ways to tell it

Your turn

What’s your idea?

Tell us the idea you are trying to explain, launch or change, and together we will find the right way to tell it.

Start a conversation See our projects