KI-Agenten.shopPotential analysis for your first or next orchestration case.
We assess process maturity, data reality, risk, economic leverage, and the right starting path.
30 minutes one-to-one — pick your own slot
Instead of a fixed weekly session we talk about your case directly: one concrete bottleneck, 30 minutes on Zoom, free and without obligation.
After booking you receive the confirmation with the Zoom link. Free and non-binding, no purchase required.
What an AI potential analysis is
An AI potential analysis is a structured first assessment: before you invest, it clarifies which specific process AI agents can sensibly take load off — and which they cannot.
Five things are assessed: how mature the process is, what the data situation really looks like, the decision rights (what an agent may prepare and what people must decide), the risks from privacy, governance and the supply chain, and the economic leverage.
The result is an assessment, not an offer: one named entry case, the metric its success can later be measured against — and a clear statement when a case does not hold up.
What we capture in the potential analysis
Not as a pitch, but as a defensible first qualification.
- Which process currently creates friction, waiting time, or repetitive manual work?
- Which data sources and systems are involved?
- Which decisions may an agent prepare but must not take autonomously?
- Where do privacy, governance, or supply-chain risks appear?
- Which metric later proves that the rollout is economically worthwhile?
Frequently asked questions about the potential analysis
Who is a potential analysis worthwhile for?
For companies with at least one recurring, clearly describable process where it is genuinely open whether AI agents can carry it. Without that concrete process there is no basis — then a general orientation is more honest than an analysis.
How does it differ from the ROI calculator?
The ROI calculator estimates the economic effect of a process from a few inputs. The potential analysis additionally examines data situation, decision rights and risks — that is, whether that effect can be realised at all.
What should we gather beforehand?
A description of the process, the systems and data sources involved, and the question of which decisions must stay with people internally. The more concrete this is, the more defensible the assessment.
What happens if no case pays off?
Then we say so. An analysis that declares every case viable would be worthless — its value lies precisely in ruling out hopeless cases early.
What you can start with right away
Three entry points that work without an appointment — and make the later analysis more concrete.
From a process to a reasoned investment decision
Describe a typical case with its trigger, inputs, desired outcome and current manual steps. Add volumes, handling times and exceptions as measured values or explicitly labelled estimates. Anonymized examples are sufficient for an initial description; do not include credentials in the form.
A sensible decision may be a limited pilot, improving the data first or no automation for now. A pilot should have a defined scope, accountable person, permitted actions and acceptance criteria. Budget and timing depend on that scope, not on a blanket savings claim.
From a use case to the right implementation
AI agents for sales
Assess lead intake, CRM data and human approvals in one bounded workflow.
AI agents for customer service
Evaluate knowledge sources, answer quality and handoff to your service team together.
Calculate AI ROI
Model setup, operation, review and time savings with your own assumptions.
Understand AI implementation costs
Compare one-time implementation effort and ongoing costs separately.
Request analysis
The more concrete your information, the faster we can assess the case.
Start potential analysis
If you want to prioritize a real process, a few clear inputs are enough for a strong first assessment.