AI Workforce Rollout
Implementation projects for AI functions in core business functions
We design and implement AI functions as part of a real operating workflow — with a clear role, data sources, tools, approval logic, and quality criteria. Not "just another bot," but a working function.
When this format is the right fit
You need a measurable pilot, not slides
There is one function with a clear bottleneck
You need integration into real systems and knowledge sources
You need a safe autonomy model and control layer
You are ready to adjust the workflow, not just "add AI"
AI function examples for implementation
Delivery model
Full path for implementing one AI function
A production-oriented approach to every implementation.
Audit of goals, priorities, workflows, data, and knowledge sources
AS-IS workflow description and TO-BE target model
Security, legal considerations, and access policy
Solution architecture and stack selection
Agent behavior design and autonomy levels
MVP / prototype
Testing and evaluation
Limited-scope production pilot
Workflow adoption and change management
Scaling and ongoing support
What we can connect
How we handle safety and control
Deployment contour: cloud, VPS, or on-prem LLM
RBAC and role-based permissions
Logging and audit trail
Retention and deletion rules
Human-in-the-loop policy
Approval levels by action and risk
Public range
Implementation of one AI function starts from €6,000. A typical project ranges from €11,000 to €29,000. Multi-function / enterprise scope starts from €35,000.
Frequently asked questions
Is this one agent or a full system?
In most cases it is not just one chat interface. It is a role-based function with data, tools, approval logic, and an evaluation model.
How long does a pilot take?
Usually 1–2 months, depending on data readiness, integration scope, and workflow complexity.
Do you only build text-based scenarios?
No. We design functions where AI reads context, makes decisions within safe boundaries, drafts actions, or performs limited actions.
Can we start without a perfect knowledge base?
Yes, but AI quality depends on the quality of data and knowledge. That is why we explicitly assess readiness and provide an improvement plan when needed.
What can be fully automated?
It depends on the risk level of the workflow. Low-risk scenarios can support limited autonomy; high-risk scenarios require approval.
Let's define the first AI function for your business
Describe the function, the system, and the main bottleneck. We will suggest a realistic starting scope and tell you whether a pilot makes sense.
Get in touch