Services that make AI work. Safe, human-centred and practical.

Who it’s for

Organisations across commercial, healthcare, public and tech contexts that want AI embedded in real work.

When this helps

You want AI value with control, but lack structure: what first, what later, what’s responsible, and who owns it.

What I do (practical)

• Clarify context and needs (stakeholders, processes, data, risks).
• Inventory and prioritise use cases (value, feasibility, risk).
• Translate choices into a roadmap, governance and implementation agreements.
• Support execution where needed.

Typical deliverables (scope-dependent)

• AI strategy & roadmap (phasing, dependencies, prerequisites).
• Use case backlog + selection criteria.
• Governance proposal (roles, decision-making, documentation).
• Risk & compliance checklist (EU AI Act / GDPR translated to practice).

Pricing: on request. Timeline: depends on size and stakeholders.

Who it’s for

Teams implementing an AI application/technology and wanting it to create real value in day-to-day work.

When this helps

You know you want to implement, but need clarity on prerequisites, who to involve and how to embed it properly.

What I do (practical)

• Define prerequisites (data, integrations, roles, policies).
• Bring stakeholders and workflows along (human-centred design).
• Create implementation + adoption steps (training, guidelines, work instructions).
• Support rollout and aftercare.

Deliverables

• Tailored implementation plan and implementation strategy.
• Roles & responsibilities (ownership, operations, monitoring).
• Practical safe-use guidelines (incl. EU AI Act / GDPR focus areas).
• Adoption materials (training outline, examples, prompts/work instructions).

Pricing: on request. Timeline: depends on scope.

Who it’s for

Organisations using (or about to use) AI and wanting a durable way to assess and adjust.

When this helps

You want to prevent “forgotten AI”: performance drifts, context changes, or responsibilities are unclear.

What I do (practical)

• Set up an evaluation framework (what to measure, why, how often).
• Define monitoring agreements (ownership, signals, escalation).
• Include quality/safety/bias where relevant.
• Build an improvement loop (feedback, updates, documentation).

Typical deliverables

• Evaluation & monitoring plan (frequency + owners).
• KPI set + acceptance criteria (quality, reliability, impact).
• Reporting format / review cadence (monthly/quarterly).
• Improvement backlog and assurance actions.

Pricing: on request. Timeline: depends on scope.

Who it’s for

Teams researching AI (or using AI in research) e.g., healthcare, pharma, public sector and tech.

When this helps

You want a robust way to study or evaluate AI, and need structure in approach, criteria and reporting.

What I do (practical)

• Help scope research questions and desired outcomes.
• Design evaluation/validation approach and data strategy (within legal constraints).
• Support analysis, interpretation and reporting.
• Translate findings into implementation and decision-making implications.

Typical deliverables

• Research plan (goal, method, measurement points, interpretation frame).
• Evaluation criteria set (holistic where relevant).
• Stakeholder-ready summary/reporting.
• Next-step advice (pilot, scale, adjust).

Pricing: on request. Timeline: depends on scope.

Who it’s for

Whole organisations, departments or professional groups that want stronger AI skills and self-reliance (also relevant for AI regulation readiness).

When this helps

Teams want to use AI but lack guardrails and skills—or you want a measurable, repeatable AI literacy programme.

What I do (practical)

• Assess current AI literacy level (optionally by team/role).
• Translate industry context and requirements into learning goals.
• Review workflows and interview stakeholders to understand needs and culture.
• Design and deliver training sessions or a complete AI curriculum.

Deliverables

• Tailored AI literacy self-assessment (for evaluation & ongoing monitoring).
• Slides/materials from training sessions.
• Tailored AI curriculum (programme + rationale + strategies).

Pricing: curriculum on request; packages are possible for individual training sessions (depending on number of sessions and group size).
Timeline: depends on scope.