01
Test questions and sources
Real buyer questions and the information available to answer them are tested.
SERVICE 04
FOUND IN AI. USEFUL AT WORK.
Reliable sources help AI understand your offer. Safe assistants support clearly defined work steps.
WHAT THIS SOLVES
AI Visibility & Automati
AI should explain your business accurately and act only where value, data access and approvals are clearly governed.
YOU GET
- Visibility in AI search and reliable sources
- ChatGPT apps and internal assistants
- Secure interfaces, MCP or API
GEO audit €790 net · automation after feasibility review
PROCESS
From goal to a reliable solution.
02
Limit the use case
One concrete benefit is defined with data, permissions and approvals.
03
Deliver measurably
Visibility or workflow is implemented and compared with a documented baseline.
WHO IT IS FOR
For one clear workflow – not AI at any cost.
Delivery fits SMEs with a recurring, bounded work step in which information is found, structured, prepared or passed on after an approval.
- The workflow occurs regularly and creates meaningful manual effort.
- Inputs, intended output and responsible approval can be named.
- Required data is lawfully accessible and has an accountable source.
CONCRETE DELIVERABLES
What you receive.
The exact scope is stated in the proposal before work begins. These deliverables form the binding frame for this service.
01
Feasibility picture
Workflow, data sources, risks, permissions, costs and success criteria are described before implementation.
02
Bounded pilot
One prioritised work step is implemented with realistic test cases instead of changing several processes at once.
03
Controls and approvals
Sensitive outputs or actions remain reviewable. Failure cases, ownership and stop paths are considered from the start.
04
Measurable handover
Test cases, known limits, operating guidance and the decision to expand or stop are documented.
TIMING AND INPUT
Clear before we start.
Timeline and fixed price follow only after the workflow, data access and required approvals have been reviewed. You do not buy a large AI project on a hunch.
WHAT I NEED FROM YOU
- Real, sanitised examples from the selected workflow
- One subject-matter owner for rules, tests and approvals
- Documented access to the required systems or a technical contact
EXCLUSIONS / BOUNDARIES
- Exactly one clear use case is scoped first.
- Legal review, data protection impact assessments and employee agreements are not legal advice and may require separate expert review.
- Sensitive or irreversible actions are not automated without suitable approval.
- Licences, model usage and third-party services are disclosed separately in advance.
EXAMPLE PILOT
Prepare an inquiry rather than decide without review.
An assistant reads a new inquiry, organises the available information, flags missing details and prepares a reply draft. A person reviews and sends it. Further steps are considered only after the test cases work reliably.
The example demonstrates the safety principle. Data access, system integration and actual value must be assessed for your workflow.
FAQ
Clear before you decide.
Which process makes a good first pilot?
A frequent, clear step with known inputs and a verifiable output. Good candidates prepare decisions; they do not immediately replace critical approvals.
Does our data need to be perfect?
No. But its source, owner and minimum quality must be known. If data conflicts or cannot be accessed reliably, that foundation is addressed first.
Do we need MCP immediately?
No. MCP is one possible connection to approved tools and data. Some pilots need only an existing API or narrow import; the simplest reliable option wins.
Can AI send emails or change data itself?
That can be technically possible. In the first stage, sensitive actions are designed with preview, approval, limited permissions and auditable logging.
How is value assessed?
Test cases and an observable goal are defined before building, such as fewer manual steps, more complete preparation or more consistent outputs. Without a baseline there is no reliable evaluation.
What ongoing costs should we expect?
That depends on the model, usage, hosting and connected services. External costs are shown separately from implementation and support in the proposal.
What if the pilot is not convincing?
It is not expanded automatically. You receive the documented findings, limits and a clear recommendation to adjust, choose another approach or stop.
This fits when ...
- Your company is absent from relevant AI answers
- Knowledge exists but is not machine-readable
- One clear work step should be supported safely
FEASIBILITY BEFORE DELIVERY
Describe one recurring work step that takes time today.
I will assess whether AI offers controlled value there – and say clearly when simpler automation is the better choice.