Automation and AI that start with the problem, not with the tool.
Process analysis, workflow automation, system integration and the introduction of AI assistants with governance and data protection. The starting point is a target picture, not a tool.
Starting point
A lot of work consists of moving data between systems by hand, and company knowledge sits in mailboxes, folders and people’s heads. At the same time the pressure to use AI grows, while it remains open which use case actually delivers value and which data may be used for it.
Goal
Automations that run reliably and can be followed, and AI applications with a clear purpose, defined permissions and data protection settled. The basis is a target picture worked out together: what should get better, which data may go where, what stays in-house.
Services
The order is deliberate: need and target picture first, then automation, then AI.
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Process analysis and target picture
Which processes cost time, where is knowledge stuck, which use cases are worth it? Prioritised by benefit and effort.
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Workflow automation
Approvals, notifications, data transfers and recurring tasks with Power Automate or n8n, documented and maintainable.
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System integration
Connecting line-of-business applications, Microsoft 365, databases and cloud services through APIs and scripts.
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Copilot rollout
Preparing and rolling out Microsoft 365 Copilot: permissions, data quality, governance, a pilot group and training.
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AI assistants and knowledge bases
Preparing documentation, contracts and manuals so AI assistants can answer from them in a way you can follow, with sources cited.
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Data protection and on-premises models
AI governance and rules for staff, and where the requirements for data sovereignty are higher, models on your own infrastructure.
Tools, when they fit the target picture.
Tools only come into play once the goal and the flow of data are clear.
- Power Automate
- Workflow automation within Microsoft 365.
- n8n
- Open-source workflow automation, self-hosted, connecting line-of-business applications, Microsoft 365 and AI models.
- Microsoft Graph & APIs
- Programmatic access to Microsoft 365 and other systems.
- Microsoft 365 Copilot
- An AI assistant in Word, Outlook, Teams and Excel, working within existing permissions.
- Cloud and on-premises models
- Models from OpenAI, Anthropic or Microsoft, or open-source models on your own hardware.
How a project usually runs.
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01
Analysis
Observing how work actually runs, quantifying the effort, locating the data and permissions involved.
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02
Target picture
Agreeing one or two use cases with a clear benefit and a data protection assessment.
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03
Delivery
Prototype, test with real data, pilot group, then production.
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04
Further development
Build on what works. Name what does not.
What clients want to know in advance.
Not finding what you want to know? Ask me directly.
None, until the target picture is clear. Only once it is settled which problem is to be solved and which data is involved can you judge which tools help. Sometimes it is Copilot, sometimes an on-premises model, sometimes no AI at all.
The first question: which data may go to which provider, and which has to stay in-house? That determines whether cloud models, Copilot or on-premises models are the right fit, and what rules apply to your staff.
That is the goal. Automations are documented and built so your team can understand and adjust them.
Want to know where AI would genuinely help in your company?
Send me a couple of lines about it, or just call. You reach me directly, no call centre.