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AI Tappers Ltd

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Practical AI. Governed. Built around real workflow

AI Tappers is a UK-based AI and automation consultancy helping organisations move from AI experimentation to practical, governed implementation.

We work with leadership teams to identify high-value workflows, assess business value and operational risk, and design AI-enabled systems that integrate into existing ways of working.

Our approach is discovery-led, technology-agnostic and built around human oversight where judgement, accountability or risk requires it.

  • Min project size
    $10,000+
  • Hourly rate
    $150 - $199 / hr
  • Employees
    2 - 9
  • Year founded
    Founded 2023

Service Lines
AI Consulting
40%
AI Agents
30%
AI Development
20%
Generative AI
10%

No Focus Areas have been added yet…

Industries
Manufacturing
30%
Food & Beverage
25%
Supply Chain, Logistics, and Transport
20%
Business services
15%
Real estate
10%
Clients
Enterprise (>$1B)
40%
Midmarket ($10M - $1B)
30%
Small Business (<$10M)
30%

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Our Story

Marcus Cronan and Mattias Hjemgaard met through the AI Advantage community and have worked together for nearly four years. As early members of the community, they helped build one of the world’s largest AI-focused YouTube channels. AI Tappers grew from that shared experience, combining commercial strategy with hands-on AI engineering to help organisations adopt AI in practical, governed and human-centred ways.

What Sets Us Apart

Governance Before Technology

We start with the workflow, business value, risk and ownership before choosing tools. That keeps AI practical, proportionate and easier to govern, with humans in the loop where judgement or accountability matters.

Strategy and Engineering Together

AI Tappers combines senior commercial and operational thinking with hands-on AI engineering. We can identify the right use case, design the operating model and then build what is actually worth deploying.

Quick Facts

3 years in business

Tools and Technology

Canva
Power BI
Microsoft Teams
Notion
Google Drive
SharePoint
Microsoft Azure
GitHub
Google Workspace
Microsoft Outlook
Miro

Commonly Asked Questions

We work closely with leadership and operational teams to understand real workflows before recommending technology. Engagements are structured, collaborative and evidence-led, with clear ownership, regular checkpoints and human oversight built into the process. We aim to work as a long-term partner rather than a one-off supplier. That means being clear about what is worth pursuing, what is not, and where AI can genuinely improve productivity, reduce cost, strengthen decision-making or reduce operational risk.

It depends on the engagement. A focused AI Discovery typically runs over 2–4 weeks and ends with a prioritised view of where AI can create value, the associated risks and a recommended roadmap. Implementation timelines depend on workflow complexity, integrations, data access and governance requirements. Simpler AI-enabled workflows can often be scoped and delivered within a few weeks, while more complex systems may be phased over a longer period. We prefer clear milestones, controlled rollout and measurable outcomes rather than rushing into build before the workflow and governance requirements are understood.

We start by agreeing the business problem, stakeholders, access requirements and success measures. From there, we map the relevant workflows, understand where time, cost or operational friction exists, and assess potential AI opportunities against value, feasibility, risk and governance requirements. Where a build is justified, we define ownership, human approval points, data boundaries and success measures before implementation begins. This keeps the work focused on measurable outcomes rather than technology for its own sake.

No. AI Tappers is technology-agnostic. We recommend platforms, models and tools based on the client’s existing environment, security requirements, workflow, data, governance needs and commercial objectives. Depending on the use case, that may involve Microsoft, OpenAI, Anthropic, cloud platforms, automation tools or other technologies. Where possible, we design for portability, client ownership and flexibility rather than unnecessary vendor lock-in.

Governance is built into the engagement from the start rather than added at the end. We consider data access, privacy, ownership, accountability, human approval, operational risk, security and regulatory requirements before deployment. Where judgement, risk or accountability matters, we keep humans in the loop. Our aim is to help clients adopt AI in a way that is practical and proportionate, while maintaining control over how systems are used, monitored and improved over time.

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