Programmes

Build governed AI systems your team owns. In 4 to 12 weeks.

Three fixed-scope programmes for B2B marketing and leadership teams. Governance-first, EU AI Act aligned, no consultant lock-in.

Book a discovery callSee the programmes
100+ countries running AI I've built50+ systems in productionAuthor of Prompt. Refine. Deliver. Repeat.

Where are you today?

The Five Levels of AI Maturity

Most teams starting here land at Level 2 or 3.

1

Level 1

No structure

Individuals experimenting independently, no governance, no shared approach.

2

Level 2

Tools deployed, outputs inconsistent

Copilot or ChatGPT licensed, training done, results variable.

3

Level 3

Some working processes

A few good prompts in use, but no system, no governance, no customer grounding.

4

Level 4

Governed but not optimised

Policy exists, shadow AI mapped, but no methodology producing consistently strong outputs.

5

Level 5

Structured and compounding

Customer-voice extraction, governance live, team independent, outputs measurably better.

The AI Governance Sprint gets you from wherever you are to Level 4 in 4 weeks.

Programmes

Three ways to work together

Fixed scope. Fixed price. No retainer required.

Tier 01

AI Governance Sprint

Best for: VP PMM or CMO who needs governance fast

Available on request

4 weeks · On-site or virtual

  • ✓Shadow AI audit across your organisation
  • ✓Data exposure risk map
  • ✓Board-ready governance framework
  • ✓EU AI Act and GDPR alignment
  • ✓90-day implementation roadmap
Book a discovery call
Most Popular

Tier 02

AI GTM System

Best for: Head of PMM ready to build

Available on request

8-12 weeks · On-site or virtual

  • ✓Everything in AI Governance Sprint
  • ✓Customer-voice extraction system
  • ✓Content playbook grounded in real customer language
  • ✓Team trained to run the system
  • ✓30-day implementation support
Book a discovery call
Premium

Tier 03

AI x PMM Partnership

Best for: Senior PMM with a complex GTM motion

Available on request

3-6 months · Hybrid

  • ✓Everything in AI GTM System
  • ✓Channel and reseller enablement layer
  • ✓Competitive intelligence system
  • ✓8-12 weekly mentoring sessions
  • ✓Monthly strategic reviews
  • ✓Custom AI tool development support
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Case Studies

Systems in production

Full case studies coming soon.

Live in productionSalon OS

Clinical aesthetics platform, Czech Republic

A leading Czech clinic was not struggling, it was growing. The problem was structural: two years of business data locked in a Google Sheet nobody could query. Twelve monthly tabs, 1,530 rows a year, legible only to its creator. Client contraindications (cardiovascular conditions, autoimmune disease, pacemakers) held in the practitioner's memory. No system, no flag, no way to check before a treatment.

We built a purpose-built operating system from the ground up. Nine integrated AI systems now run the clinic: reconciled financial records, structured client profiles across eight medical categories, treatment protocol tracking across every multi-session programme, product transaction analysis, and a repositioned public-facing site.

Then the proof-of-concept scaled. A national cosmetics reseller network adopted the same architecture across their branded salons.

Audit the data that exists but cannot be used. Build a purpose-built system around how the specific business actually works. Let the results do the scaling.

Phase 1 liveCognitive Rehab

Purpose-built for a healthcare organisation

A cognitive rehabilitation practice was running on paper and in practitioners' memories. Session notes on clipboards, treatment progress recalled from memory, outcome sharing across a distributed team functionally impossible. The clients most affected: those recovering from brain injury, where session continuity is the intervention.

We designed a six-phase platform from scratch. Phase one is live: deterministic, offline-capable, zero AI dependency by design. Unreliable connectivity in clinical settings is not a bug to work around, it is the constraint the platform is engineered for. AI-assisted clinical notes ship in phase three. Eye tracking for non-verbal users (MediaPipe Iris, dwell-to-select) ships in phase five.

Built for a domain where the system going down is not an inconvenience. It is a failure of care.

The Cost of Waiting

Every month of unstructured AI has a price tag

Ungoverned teams waste time on ad-hoc use and miss the productivity gains a governed system would deliver.

1100
£20£200

Ad-hoc AI use wastes an average of 4 hours per person per week, plus the productivity gain you would have captured with a governed system.

The cost of waiting
£13,000
per month, right now

Over a year

£156,000

Over five years

£780,000

An AI Governance Sprint fixes this in 4 weeks.

Illustrative calculation based on typical unstructured AI use in B2B marketing teams. Actual figures vary by team and workflow.

Methodology

How we'll work together

The Prompt. Refine. Deliver. Repeat. methodology. When AI projects fail, it's almost never the model. It's a vague problem, fuzzy metrics, and no path to real work.

Phase 1: Prompt - Start from one painful problem

We begin with one well-defined pain your team already feels: launches dragging, research stuck in decks, or content bottlenecks. In 60-90 minutes, we pick a single outcome and a "board-visible" metric, plus one operational metric your PMMs feel every week, and set the baseline. We frame a clear AI x PMM hypothesis: when we fix this, here's what will change and how we'll know.

Why you should care:

When you start with a specific pain and a metric, you're not buying "AI", you're buying a path to relieve something that already hurts.

Frequently Asked

Enterprise questions, straight answers

Prompt injection is the number one OWASP LLM risk, and it is real. But the model side of it is well understood: OpenAI reports 99.5% mitigation on synthetic web injection attempts, and 99.9-100% on critical actions like financial data or personally identifiable information. The residual risk is not the AI, it is how companies configure access: giving AI tools access to everything instead of scoping, leaving documents shared openly in Drive or SharePoint, turning everything on for everyone with no policy. That is exactly what the governance framework prevents. The companies that get burned are the ones who turned AI on without thinking. Building the framework first is how you use AI confidently.

You own everything: the prompts, the custom GPTs, the governance framework, the documentation, the workflows. Every engagement is a co-build, not a delivery. Your team is trained to run and extend the systems themselves. There is no retainer requirement and no consultant lock-in. If you later hire an internal AI lead, they inherit a functioning system rather than starting from scratch.

Yes. The AI Governance Sprint is the smallest engagement: 4 weeks, focused on one team or one workflow, delivering a Shadow AI audit, risk map, governance framework, and 90-day roadmap. It is designed as the entry point for organisations that want to validate the approach before committing to a longer programme. When it pays off, the next piece funds itself.

Most clients see measurable productivity gains within the first two weeks of active engagement, before the formal programme completes. The AI Governance Sprint delivers a governance framework and roadmap in 4 weeks. The AI GTM System has working systems in production within 8-12 weeks. Every engagement is iterative: we build, test, refine, deploy. If a system does not work in practice, we iterate until it does.

Start with a discovery call.

Thirty minutes. No slides. We diagnose where you are, and decide together whether it makes sense to work together.

Book a discovery call→