An AI employee is more than a bot. It's the core of an AI system: an agent that makes decisions, uses tools and is embedded in your workflows — with roles, clearances and defined goals.
No-code orchestrators like n8n or Make provide the flows. The agent decides which step comes next. Code nodes add integrations with your systems and custom logic.
A real AI employee gets a dynamic knowledge base synchronized 1:1 with a vector database. Simply put: the DB is for you to maintain knowledge; the vector DB is for the agent to work with it.
This way the AI employee interacts with your specific company data — and continuously improves through self-reflection and feedback loops.
We identify tasks with the highest leverage, assess data availability, risks and success criteria.
A working prototype or shadow mode run proves value and quality. Feedback loops are built in from the start.
We deploy to your production environment with monitoring and full documentation of every interface.
Training, handbooks and handover workshops ensure sustainable operation. We continue in short iterations.
My strength: I make complex things simple. I don't build overloaded all-in-one systems. Instead I sit down with you and ask: which three tasks are eating the most time, money and energy right now? We solve those first. Then we look at the next lever together.
This focused approach ensures you get maximum value with minimum overhead — solutions that actually help in day-to-day operations.
Book your free strategy callThrough roles, clearances, logging and escalation. The AI employee only acts within defined boundaries; sensitive steps require human confirmation.
We start minimal: relevant knowledge bases, access to CRM/ERP/PMS and defined interfaces. We prioritise by impact and risk.
Open interfaces, exportable data, documented flows and optional on-prem/cloud deployment — with a clear exit plan from day one.
First results within 2-4 weeks. A pilot in three weeks is standard, then gradual expansion based on proven ROI.