AI is everywhere.Rarely in the right place.
The question is not whether AI can do something, but where it actually has an effect in your processes. We clarify that before the investment: data situation, use cases, governance – and we say openly when no case is worth it.
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fabAI flagged batch L-2481: three days from best-before – FEFO suggestion created.
- from €2,000
- Written result
- No obligation to buy
Why AI projects stall in mid-sized companies
Almost never because of the technology. Usually because of three questions that should have been answered before the first tool.
The use case is unclear
AI is on the agenda, but nobody can say which case pays off. The result is pilot projects that demonstrate something but change nothing.
Use cases identified and assessed commercially – with a ranking.
The data does not hold up
The most common reason pilots fail is not the models but the data: incomplete, inconsistent, not linked.
Process and data quality analysis before effort is spent.
Governance is unresolved
Who is allowed to do what, what gets logged, which obligations follow from the EU AI Act? Without an answer, every production deployment stays a risk.
Permissions, logging and regulatory assessment clarified.
What happens in an engagement
Five steps in a fixed order. At the end you have a document you can keep working with, even without us.
Needs analysis
- 1.Record business goals and processes.
- 2.Capture existing tools and data sources.
- 3.Clarify who is involved and who is responsible.
Without a target picture, every use case looks equally plausible.
Potential check
- 1.Collect and assess use cases.
- 2.Check data quality for each case.
- 3.Compare effort against expected effect.
- 4.Ranking with reasoning.
Recommendation & support
- 1.A concrete pilot recommendation with an effort estimate.
- 2.Stop criteria defined up front.
- 3.Governance, data protection and the EU AI Act.
- 4.Enabling your team instead of buying tools.
If no case holds up, the report says so just as plainly.
Consulting from people who also build it
We do not only advise on whether AI fits, but above all on how – because we developed fabAI ourselves and rolled it out in real operations. We know what gets expensive during implementation, and we say so beforehand.
- Experience from production AI rollouts, not from slide decks
- Local operation as an option when data must not leave the building
- A clear line between what works today and what is still a promise
- No obligation to buy – the recommendation can also advise against a project
from €2,000
fixed scope, written result
25+
years of experience in the DACH region
21
ready-made agents as a starting point
0
commitments after the consulting
About AI consulting
Do we have to use fabular?
No. The consulting is independent of which ERP you run. If an implementation looks sensible, the enterprise AI industry solution also offers a route via SAP, Microsoft Dynamics or other systems – but that is a consequence of the analysis, not a precondition for it.
What does the consulting cost?
From €2,000 for a defined engagement with a set number of workshops and a written result. More sites or departments are calculated and approved beforehand. There is no additional billing without your agreement.
How long does it take?
Four to ten weeks, depending on scope. The time is driven less by the analysis than by interviews and review rounds – those need calendar time, no matter how fast we work.
What happens to our data during the consulting?
For the analysis we need insight into structures and data quality, not into complete datasets. What we need to see is agreed beforehand. On request we work exclusively in your environment.
Let us clarify whether a case is worth it
Name a process where AI could help. In the free initial conversation we tell you whether your data supports it.