Claude or Copilot – for what?
Teams can use both tools, but lack shared guidance on tasks and data.
Already using Claude, or introducing it alongside Microsoft Copilot? We help you define clear guardrails, choose valuable use cases and build the skills your teams need – from the first decisions to everyday adoption.
The important decisions involve business teams, IT, data protection and leadership working together.
Teams can use both tools, but lack shared guidance on tasks and data.
Early users are enthusiastic; the wider team struggles to connect the tool to real work.
Documents, projects, shared content and connections to other systems raise questions.
Ideas are tested, but value, quality and accountability remain hard to assess.
Bring us in as a sparring partner for a specific question or work with us across rollout and enablement.
We review your starting point, goals, user groups, guardrails and Claude's place in your existing AI landscape.
We choose real tasks, test them with a team and review quality, effort and accountability.
We help employees, leaders and internal champions apply Claude to the work they actually do.
When both tools are in use, we clarify where each fits, which data is approved and who owns the decisions – without a blanket preference for either one.
Explore our Copilot advisory →A complete track covers the essentials, practical application, deeper workflows and adoption across the organisation. We tailor the specific priorities to roles, existing licences and approved capabilities.
Ask better questions, check results and handle confidential information appropriately.
Work with relevant tasks in research, documents, analysis and communication.
Create repeatable projects and skills; assess Cowork or Claude Code where roles and approvals allow.
Enable champions and leaders, share good practice and review impact.
These four themes suggest a possible structure. We agree the exact content and scope with you.
These examples show our work on AI adoption, use cases and enablement – themes that matter when introducing Claude, too.

In a setting with sensitive technical data, we connected people-focused enablement with practical AI use cases and business value.
View references →
A programme for people with different levels of experience used practical exercises and GPT assistants to make AI less daunting in everyday work.
View references →
Strategic AI exploration was translated into concrete use cases and a stronger foundation for future innovation.
View references →
AXA highlighted hands-on work on agent-based team workflows, structured patterns and guardrails applied to real use cases.
“The AI Engineering training was extremely hands-on.”
Head P&C Product / Applications · AXA
View course and testimonial →These examples come from our wider AI work and are not presented as purely Claude projects. Individual projects differ in scope and technology.
Yes. The key is to define where each tool fits, which data is approved, who owns decisions and how employees can get clear guidance. We work through these questions with you.
That depends on your users, administrative needs, security requirements and planned connections. We review the requirements before recommending a setup or wider rollout.
Before a pilot, we choose a few useful measures such as adoption, output quality, time spent and improvement in a specific workflow. The observations then inform your decision to scale.
Whether you already have licences, use two tools side by side or plan the enablement track, we can discuss your situation and a practical next step.