Autonomy for Organisations

Your company,
rebuilt as a
learning environment.

AI is reshaping every knowledge-work function. The organisations that pull ahead aren't running more courses — they're creating real capability. There's a difference.

Talk to us See the simulation →
Deployed across teams in Financial services Retail & e-commerce Professional services Technology Higher education

Companies spend billions on training.
Behaviour barely moves.

Your people complete the modules, pass the certifications, attend the workshops. And then return to their desks and work exactly as before — not because they weren't paying attention, but because nothing they did felt like their actual job.

Generic training fails because it's generic. Experience is the only thing that builds judgment. And until now, experience was the one thing L&D couldn't give people.

The difference

Not a training programme.
A capability programme.

The distinction matters — especially when the bar for human judgment is rising, not falling.

Traditional approaches

Generic contentCase studies built for a different industry, role, or context. People struggle to connect it to their actual job.
Passive consumptionWatch. Read. Complete. Pass. Research consistently shows 80%+ is forgotten within a week without active application.
Completion as the metric"73% course completion." A measure of attendance, not capability. Hard to translate into ROI for a leadership team.
Limited space to fail safelyIn real organisations, failure is visible. So people avoid risk. Without a safe environment to make mistakes, judgment develops slowly.

✓   Autonomy for Organisations

Built around your companyYour data, your culture, your challenges. People recognise their working environment — because it is.
Active — they're doing the jobReal decisions. AI stakeholders who push back. Work that doesn't advance until it meets professional standards.
Capability evidenceCompetency scores across real dimensions. A portfolio of work. Performance data tied to outcomes you defined on day one.
Safe space for expensive mistakesPeople develop judgment by making real decisions — without real consequences. That's the environment that changes behaviour.

What your employees experience

They don't study your company. They work inside it.

Every employee steps into a simulation built around your organisation — your data, your AI stakeholders, your challenges. Daily briefs arrive. Decisions need to be made. Stakeholders push back when the work isn't good enough.

Work doesn't advance until it meets professional standards. It's not a course. It feels like the job — because it's designed to.

Inbox — Meridian Bank · Week 2
Simulation · Configured to your environment
HM
Head of Commercial
Senior Stakeholder
09:14

Need the dashboard by Friday — active customers, revenue by segment, trend. Don't over-engineer it. I need something I can take to the board.

CRO
Chief Risk Officer
Senior Stakeholder
11:47

Before anything goes to the board, I need to understand the methodology. Stated assumptions, confidence intervals, sample size. Don't send something you haven't stress-tested.

AI
AI Coach
Always on · In character
15:30

You've been on the same brief for 48 hours. The CRO's concern is specific — look at your confidence intervals. What happens to your conclusion if the sample is 20% smaller?

How it works

We configure the simulation around you. Your people do the rest.

You define what capability looks like. We build the environment. Employees navigate it at their own pace — working through real challenges, with AI stakeholders who respond in character and work that doesn't advance until it meets the bar.

Typically deployed in 4–6 weeks from first conversation. Scales across teams, divisions, and geographies.

What we need from you: A 2-hour configuration session, a brief on your team's context and goals, and access to anonymised data samples if using your environment. We handle the rest — no internal dev resource required.

01
Define outcomes & gapsWhat do you need your people to be able to do? What are the capability gaps you're closing?
02
Configure your environmentData landscape, company culture, stakeholder dynamics, org structure, strategic context.
03
Define the journeyNarrative arcs, challenges, escalation moments, decisions you want people to face.
04
DeployEmployees step inside. Real AI stakeholders, real data, real consequences. 4–6 weeks from kickoff.
05
MeasureCompetency scores, portfolio evidence, performance data — tied to outcomes you set on day one.

Track library

Choose a track. We build the simulation around you.

Every track shares the same rigorous knowledge curriculum. What changes is the simulation — your data, your stakeholders, your company's challenges.

Live now

Data & Analytics

SQL, Python, data analysis, commercial judgment. Employees work inside your simulated business with real data and real stakeholder pressure.

SQLPythonData Viz
In development

AI Builder

Build real products with AI. Scope, design, and ship software using the tools closing the gap between idea and product.

Claude CodeAI Workflows
In development

AI Product Manager

Bridge technical teams and business strategy. Lead AI initiatives inside your organisation's real product context.

Product StrategyAI Literacy
In development

AI Business Analyst

Identify where AI creates value, make the business case, lead implementation. Inside your company's transformation context.

ROI ModellingChange Mgmt
In development

Data Engineer

Build the infrastructure that makes data useful. Essential to every AI-first organisation, deployed in your data environment.

dbtAirflowBigQuery
In development

Machine Learning Engineer

From notebook to production. Build the models that power your organisation's AI — with the judgment to know when it helps and when it doesn't.

PythonMLOps

Employees can be assigned to a track or self-select, depending on your programme design. Multiple tracks can run in parallel across a single cohort. Working in a domain not listed? Talk to us — we build custom tracks for larger enterprise engagements.

Early results

What we're seeing from pilot cohorts.

We're early. Here's what participants and their managers are telling us.

The difference is that it doesn't feel like training. It feels like doing the job. We saw sharper problem structuring and stronger commercial judgment within weeks — analysts who can communicate results, not just report them. That's what we'd been trying to get from two years of conventional programmes.
Director of Analytics UK retail & e-commerce, pilot cohort 2025
I went from zero to querying production-scale data with confidence in weeks. But the bigger shift was everything they don't put in a job spec — how to structure an argument for a CFO, how to know when the data is the story and when it isn't. I didn't just learn analytics. I learned how to think like an analyst.
Graduate Data Analyst Financial services, pilot cohort 2025

What your organisation walks away with

Measurable capability development tied to outcomes you defined before the programme started.

From pilot cohorts: participants reached job-ready output standards an average of 60% faster than equivalent classroom-based programmes. Assessed against competency frameworks agreed at kickoff.

Faster to capable

Mastery-based progression means no wasted time. People advance when they've genuinely learned — and you can prove it.

🧠

Judgment, not just knowledge

Experience making real decisions in your company's context. The capability that shows up in performance, not certifications.

📊

ROI you can show a board

Competency scores, portfolio evidence, performance data — all tied to the outcomes you defined on day one. Not completion rates.

🔄

AI-ready workforce

Every simulation is built for an AI-first context. Your people develop the capability to work alongside AI — not be replaced by it.

🏢

Your culture, embedded

The simulation reflects your values, stakeholder dynamics, and decision-making culture. Development that reinforces who you are.

🎯

A retention signal that works

Top performers stay where they're genuinely stretched. A simulation built around real challenges tells them you're serious about their development.

Built for teams, not individuals.

Autonomy for Organisations is designed for cohort deployment — typically across a team, function, or division. Pricing is per employee, with configuration included. We'll give you a straight number in the first conversation — no three-week RFP process.

Comparable to mid-market enterprise L&D programmes. Typically a fraction of the cost of equivalent apprenticeships or bootcamp providers, with faster time-to-capability and measurable outcomes.

Team

25–100 employees
  • One track, one simulation
  • Custom data environment
  • Cohort dashboard
  • 4–6 week setup

Division

100–500 employees
  • Multiple tracks
  • Full simulation configuration
  • Dedicated account support
  • Custom onboarding

Enterprise

500+ employees
  • Custom track development
  • Multi-division deployment
  • White-label options
  • Strategic partnership

Ready to talk?

Whether you're at the early-thinking stage or ready to move, we'll meet you there.

Book a 20-minute demo

See the simulation in action. We'll walk you through a live deployment and answer your specific questions. No deck. No pitch. Just the product.

Book a demo →

Tell us about your team

Not ready for a demo? Tell us what you're trying to build and we'll come back with a view on how we'd approach it. Usually within 24 hours.

Get in touch →

No sales calls without permission. We respond to every enquiry ourselves.

Common questions

How do we get employees to actually engage?

The simulation is designed to feel like real work, not a course — which is the main driver of engagement. We also share an employee launch pack and onboarding guide as part of every deployment.

How does measurement work?

You get a manager dashboard showing competency scores, progress, and portfolio evidence per employee. Export available for HRIS integration. We also provide a programme summary at the end of each cohort.

What does it cost?

Pricing is per employee and depends on cohort size, track selection, and configuration complexity. We'll give you a number in the first conversation.

Do you need access to our real data?

No. The simulation uses your data environment's structure and logic — not your production data. Anonymised or synthetic data works. Data security is straightforward to manage.