E-learning
- Real conversation practiceNo
- Individual practiceNo
- Repeat as many times as neededNo
- Immediate feedbackQuiz / test
- Scalable across the organizationYes
Digital Twin
Digital Twin for human skills development
Map how people communicate, lead and respond in realistic conversations — and turn every simulation into measurable development data.
What is the Digital Twin?
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Conversations with avatar
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AI structured feedback
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Competency profile
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Personalised development path
Digital Twin in Metaskills is a dynamic competency profile of a user, built from simulation data, behavioural indicators, self-assessment and AI feedback.
What we map
Metaskills does not map personality, emotions or private inner states.
It maps observable behavioural evidence from realistic conversation simulations — and uses it to build a structured picture of competence, progress and development needs.
Competency level
How strongly a competency is demonstrated across valid behavioural samples and conversation contexts.
Strengths
Which behaviours are effective, repeatable and visible in different scenarios.
Competency gaps
Where performance is inconsistent, context-dependent or not yet sufficiently demonstrated.
Progress over time
How the user’s behaviour changes across multiple simulations and difficulty levels.
Contextual patterns
How competencies show up in different relationships, scenarios and moments of pressure.
Leadership profile coverage
How the user’s behaviours fill different areas of the competency model: relationship, task, change and system orientation.
Development direction
Which simulations, skills or behaviours should be practised next.
Digital Twin It is not a personality test
This is an evidence-based developmental profile-built on observable behaviors.
See it live
This is what a conversation looks like
A realistic AI avatar that reacts to your words, shows emotion, and gives you an instant coaching read. Here's a sample feedback conversation.
TELL MARGO WHAT'S GOING ON
Auto-playing sample · this is exactly how the real avatar responds
FROM LEARNING TO DOING
Training gives people knowledge. Metaskills turns it into practice.
E-learning is great for delivering knowledge. Workshops let people practice it. But real skills are built through repeated attempts, feedback and the opportunity to try again. Metaskills gives every employee a safe space to practice real conversations whenever they need it.
- Learn
- Practice
- Feedback
- Repeat
- Improve
- Learn
- Practice
- Feedback
- Repeat
- Improve
E-learning mainly ends at Learn.
Workshop reaches Practice and Feedback, with a limited number of attempts.
Metaskills covers the full loop: Practice, Feedback, Repeat, Improve.
E-learning
Learn
Efficient way to deliver knowledge at scale.
Workshop / Trainer
Learn + practice
Live practice and human feedback, limited by trainer time and group format.
Metaskills
Practice. Improve. Repeat.
Individual practice of real conversations with immediate feedback and the ability to repeat.
Workshop / Trainer
- Real conversation practiceYes
- Individual practiceLimited
- Repeat as many times as neededLimited
- Immediate feedbackTrainer
- Scalable across the organizationLimited
Metaskills
- Real conversation practiceYes
- Individual practiceYes
- Repeat as many times as neededYes
- Immediate feedbackAI Coach
- Scalable across the organizationYes
A trainer can only run so many conversations at once. Metaskills makes practice available across the whole organization. No pressure. No audience. Immediate feedback and the freedom to try again.
COMPLEMENTARY, NOT REPLACEMENT
Metaskills extends training beyond the classroom. Before a workshop. Between sessions. After training. Or as a standalone practice program.
Metaskills is more than a conversation with AI. Each simulation defines the role, context, objectives, character behavior and assessment criteria. After the conversation, the user receives structured feedback, while the organization can track practice and development over time.
See how a simulation worksReady to move from learning to doing?
Where organisations use it
Leadership development
Managers rehearse difficult conversations with their team — delegation, conflict, performance — and see which behaviours hold up under pressure and which need work.
Healthcare communication
Clinical teams practise breaking bad news, gaining consent and calming distressed patients, with feedback on empathy, clarity and the structure of the conversation.
Feedback culture
People practise giving and receiving feedback before it matters — so praise, correction and peer-to-peer conversations become routine rather than an annual event.
Customer service
Agents handle complaints, escalations and demanding callers in simulation, and see how tone, questioning and de-escalation change the outcome of the conversation.
DEIB
Teams rehearse reacting to exclusion, bias and awkward remarks — turning an inclusion policy into concrete sentences people can actually say in the moment.
Onboarding
New joiners practise the conversations of their role from day one and start with a baseline profile that shows where support is needed, before habits set in.
Talent development
You see which behaviours a person shows across scenarios, not just who speaks up — a starting point for development conversations — formal decisions rest on AI Assessment.
Competency assessment
Formal evaluation is a separate use case: AI Assessment, with defined criteria and human oversight. Digital Twin itself stays a development layer.
Digital Twin and AI Assessment are connected, but they are not the same.
Digital Twin is the development layer. It supports practice, feedback, progress tracking and personalised recommendations.
AI Assessment is a separate formal use case. It can support Assessment Center or Development Center processes, but only under defined conditions.
✓ The participant knows they are taking part in an assessment.
✓ Consent and data use are clear.
✓ Scenarios are selected according to assessment criteria.
✓ Competencies are defined in advance.
✓ Results are based on behavioural evidence.
✓ Interpretation includes human oversight.
✓ Access to results is role-based and agreed in advance.
Digital Twin helps users develop.
AI Assessment supports structured competency evaluation.
How this is actually built
Methodology
The competency model
18 competencies in four domains and 108 behavioural scenarios - why a functional taxonomy rather than a personality model, and what a competency description contains.
The competency modelMethodology
How behaviour becomes evidence
What counts as proof of a competency and what does not, why confidence is stated openly, and why we never average session scores.
How behaviour becomes evidenceValidation in progress
Testing assessment against human assessors
The study design, published before the results: the same scenario with an AI avatar and with a human actor, scored by independent assessors.
Testing assessment against human assessors