AI Consulting Germany — Cost-vs-Value AI Audits

What I do

Someone is selling you AI — or you're wondering whether it could take real work off your plate. The question nobody answers is whether it costs less to run than the value it brings back — held against your margin. I run that number before anything gets built, count risk and reputation avoided as real value, and recommend the change only when it genuinely improves the business: growing it, or protecting it. Change for the sake of looking busy isn't improvement.

The math decides — not the demo

Three real calls. Two of them point opposite ways.

These aren't packages to pick from — they're case studies from my own work. Two calls I made in consultations, one system I built and run myself.

Case study: Security-check agent · designed and costed in a consultation — finds weak spots in software before attackers do

Cost to run

A small fee per scan plus a bit of supervision time. Adds to the people you already pay — doesn't replace them.

Value

Your team keeps the job but spends far less time — the agent does the first pass. Problems get caught before they cost real money.

Verdict BUILD IT Reversible — it never acts without your team’s say-so.

Case study: Admin-rules agent · costed in a consultation — drafts routine internal rules automatically

Cost to run

Real running cost plus the human time to check what it drafts.

Value

Genuine in some setups, marginal in others — it sits right on the line of worth-it.

Verdict DEPENDS I'll show you what tips it either way before you spend.

Case study: Content-pipeline agents · built and run by me — the system behind this brand

Cost to run

A few specialized agents, orchestrated — fraction of a hire.

Value

Drafted a 70,000-word published novel end-to-end, and runs the content for this brand. I built it myself.

Verdict BUILT IT Proof I design and ship these, not just advise on them.

A worked example

Worked with illustrative figures — your real numbers replace them during the audit.

The decision: Run a security-check agent that scans your software after every update and does the first pass on what it finds — supervised by your engineer, with an off switch — covering the gaps between the quarterly expert tests you already pay for?

What it costs to run

Each scan (computing + AI model + tools): ~€45 × ~25 software updates/month → ~€1,125/month
Supervision (an engineer checks the agent’s shortlist, not raw output): ~€900/month
All-in: ≈ €2,000/month → €24k/year — your dev/security team stays; this adds to it

What it's worth

Checking time saved (the measurable line): your people keep the job, but the agent hands them a ranked shortlist instead of a haystack. ~35 hours/month × ~€90/hr ≈ €3,150/month → ~€38k/year — more than the run cost on its own.
Risk avoided (the upside): continuous coverage catches weak spots in the gaps a quarterly test misses; one security incident commonly costs €200k–€1M+.
Plus: helps you pass big customers’ security checks faster, and can lower cyber-insurance premiums.

Verdict: BUILD IT — it pays for itself on checking time saved alone; the risk reduction is upside. And it's reversible: the off switch means it never acts without your team's say-so.

Where this flips to NO: if you rarely update your software or your team is tiny, there's little checking time to save — the quarterly expert test already covers you. Then I'd tell you to keep the budget.

How I work

Step-by-step, not big-bang.

I don't rip out what works and replace it in one go. Every change is incremental, reversible, and supervised — so a wrong call costs you a small step, never your reputation.

Run the number first

Cost vs. value vs. margin on one specific workflow — before a line of it is built.

Ship the smallest reversible step

Narrow scope, human-supervised, with a way to stop it. It enhances your team; it doesn't replace them on day one.

Measure, then widen — or stop

If the number holds, we expand. If it doesn't, we roll back the one step and keep the budget.

Where to start

The AI Cost-vs-Value Audit

A fixed-scope read on one decision in front of you — an AI receptionist for your practice, an agent that chases unpaid invoices, a chatbot answering member questions, or the system a vendor is pitching. You leave with a number and a recommendation — and if the recommendation is not to build it, that's the result you paid for.

You get

The run cost vs. value vs. margin calculation — risk avoided counted as value
A go / no-go verdict you can take to your board
If it's a go: the conditions, the safety design, and the smallest first step

Need a steady hand afterwards? A monthly oversight engagement keeps watch on run cost and architecture as you scale — added only when it earns its place.

Why trust the call

I've designed and built these systems — and decided when not to.

A security-check agent with an off switch

Finds weak spots in software before attackers do. Runs on demand, supervised, reversible — and it supports the existing team rather than replacing it. The judgment and the safety design are the work.

An admin-rules agent I costed honestly

The case that sits on the edge of worth-it — which is exactly why I show both verdicts, not just the ones that say yes.

The content pipeline behind this brand

A few specialized agents I built and orchestrated myself — they drafted a 70,000-word published novel and run the content you're reading the brand of now.

I built the agent pipeline that wrote The PROMPT — a 70,000-word published novel. That's the kind of system I help you decide whether to build. See the book →

Start the conversation

Tell me what you're trying to decide.

One sentence on the AI or automation decision in front of you. I'll tell you honestly whether it's worth a call — and whether it's worth building at all.

Prefer email? advisory@valorhub.eu · Munich, Germany · replies within one business day