Consulting for expert-led organisations

Make AI useful where judgement matters most.

We help leadership teams turn AI ambition into a practical plan - one that strengthens expert judgement, improves adoption, and avoids expensive distractions.

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Strategy clarity

Prioritise the few AI opportunities worth backing.

Readiness insight

Identify what is genuinely ready and what is still risk.

Knowledge resilience

Design AI that works with hard-won expertise, not around it.

Where we help

Too many AI ideas, no clear sequence

We turn scattered initiatives into a decision-ready roadmap leadership can actually act on.

Pilots that sound promising but feel fragile

We pressure-test readiness, assumptions, and adoption risks before more money gets committed.

Critical knowledge trapped in a few people

We help you protect expert judgement while using AI to extend its reach.

What you get

Clearer priorities, practical next steps, and a stronger basis for AI investment decisions.

Services

Choose the right starting point for your organisation.

Whether you need a clearer strategy or an honest readiness view, each engagement is scoped to support a decision, not just create another document.

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Advisory Engagement

AI Strategy Consulting

Typically 4-8 weeks

AI strategy consulting built around your organisation's expertise. Practical roadmaps that make your best people more effective, not obsolete.

  • A prioritised AI opportunity map grounded in real operational expertise.
  • A phased roadmap with decision gates, dependencies, and practical next steps.
  • A clearer view of where AI should help and where human judgement should stay central.

Leadership workshops and focused advisory sprints

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Diagnostic Engagement

AI Readiness Assessment

Typically 3-4 weeks

A five-dimension AI readiness assessment that tells you honestly where you stand, including the knowledge and expertise mapping most reviews miss.

  • A scored readiness view across data, process, culture, strategy, and expertise.
  • A shortlist of realistic AI opportunities with sequencing guidance.
  • Clear risks, gaps, and mitigation priorities before larger commitments are made.

Interviews, technical review, and executive report

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How engagements work

A measured path from uncertainty to useful progress.

Good consulting removes noise before it creates more. We structure engagements to sharpen the decision, test the assumptions, and only then expand the scope.

What stays constant

Every phase has explicit success criteria, decision gates, and space to stop if the evidence does not support doing more.

01

Diagnose

Understand the operational context, the decisions that matter, and the expertise your AI work must support.

02

Align

Prioritise the opportunities that fit your strategy, data reality, and adoption constraints.

03

Pilot

Start with a constrained proof of value that tests the real workflow, not just the model in isolation.

04

Scale

Expand what earns trust and outcomes, while keeping human oversight and organisational fit in view.

Insights

Writing for leaders navigating AI decisions.

Short, practical thinking on strategy, readiness, human expertise, and the reasons AI programmes often stall.

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The LLM Wiki: A Pattern for Smarter Organisational Knowledge Bases

Andrej Karpathy's 'LLM Wiki' pattern offers a compelling alternative to retrieval-augmented generation. Instead of re-deriving insights from scratch on every query, AI incrementally builds and maintains a persistent, structured knowledge base. The implications for organisational knowledge management are significant.

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AI for Knowledge Transfer: The Opportunity Most Organisations Miss

AI is widely used to process existing information. Its potential to capture expertise that was never documented in the first place is largely overlooked.

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AI Doesn't Just Miss Tacit Knowledge. It Can Destroy It.

Most AI is designed to optimise tasks. But when it's built without reference to the expertise behind those tasks, it doesn't just fail to capture that knowledge — it can actively erode it.

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