Commercial-first diagnosis
Every engagement starts with the business problem: margin, forecast accuracy, pricing discipline, CRM quality, or reporting drift.
Services
I help European businesses, especially in Germany and the DACH region — fix the commercial decision problems that sit underneath unreliable forecasts, margin noise, pricing confusion, CRM friction, reporting sprawl, weak customer-service workflows, and rushed AI software decisions. The commercial problem comes first; analytics and AI are there to make decisions more reliable. The difference is that I do not stop at diagnosis: I also help teams choose the right tooling and build the reporting, workflow, automation, and ML mechanisms that make the fix operational.
Why Choose Me
I am useful when a business has enough dashboards, enough data, and enough meetings, but still lacks one trusted decision system. I bring a rare combination: commercial operating depth, analytics architecture, and hands-on ML and workflow implementation.
Sales growth personally generated through frontline sales roles, including €3M against an initial target closer to €300k.
Inside Sales growth turnaround across 38 markets.
Years across commercial leadership and analytics since 2013, including frontline sales experience before moving deeper into analytics architecture and decision systems.
10+ years building with TensorFlow since 2016 — hands-on ML implementation, not just advisory.
Every engagement starts with the business problem: margin, forecast accuracy, pricing discipline, CRM quality, or reporting drift.
Commercial leadership and analytics, enterprise BI transformation, hands-on ML implementation, and applied AI are all part of the same track record.
I build systems your team can understand, govern, and extend, with documentation and enablement included.
Based near Stuttgart. Available for onsite DACH work and remote engagements across Europe.
I write code, build workflows, and work through implementation constraints. This is not strategy theater wrapped in AI language.
Commercial Insight
The goal is not to add AI because the market is noisy. The goal is to improve one real business decision or workflow without creating hidden review cost, governance risk, or adoption drag.
A strong demo does not tell you whether the product is fine-tuned, retrieval-based, or simply calling a third-party API. That affects data flow, differentiation, cost, and control.
The right question is not only “does it work?” but “what are we actually buying, and what happens when it fails?”
AI usually removes tasks before it removes roles. Without process redesign, exception handling, and a benefits owner, many savings remain theoretical.
The better early test is whether the workflow creates measurable capacity or just scattered convenience.
If avoidable contacts are driven by poor documentation, missing order visibility, or weak escalation rules, a chatbot automates the symptom before the cause is fixed.
The safer route is often ticket-root-cause analysis, internal copilot support, and better handoffs before customer-facing AI.
Buyer Aids
The strongest entry conversations start with clearer buying logic. These assets help leadership teams pressure-test vendor claims, build-vs-buy tradeoffs, and where workflow control should sit before money is committed.
AI software diligence
Use this before you approve copilots, document AI, agent platforms, or service tools with AI built in.
It keeps architecture, permissions, failure modes, and production cost in the room before enthusiasm turns into commitment.
Workflow control
Use this when leaders are comparing vendors before anyone has decided whether the workflow belongs in software, API orchestration, retrieval infrastructure, or a higher-control internal path.
The wrong control model creates rework, governance drag, and hidden switching cost that no shortlist comparison will surface.
A focused diagnostic for leaders dealing with unreliable forecasts, unclear margin movement, pricing confusion, CRM quality issues, or dashboard sprawl. The goal is simple: find where decision quality is breaking, then leave with written next steps on what to fix first.
Public entry pricing
EUR 950 net
A short fit conversation comes first. If the issue is real and relevant, the paid diagnostic is the first structured step.
For teams evaluating copilots, agent platforms, document AI, customer-service tools, or workflow software with AI built in. The point is to understand what you are actually buying before the demo becomes a commitment.
Use the checklist first if you want to pressure-test the vendor internally before you ask for a buy, pilot, or reject view.
A two-week sprint for teams facing too many ideas, too little trust, and no clear sequence for what to fix or automate first. We start with decision pain, data readiness, ownership, and ROI. Applied AI stays on the table, but only where it earns its place, and only when the use case can survive real operating conditions.
Clean up the analytics foundations leaders rely on. This offer is designed for businesses where dashboards exist, but the underlying KPI logic, ownership, CRM data, or reporting structure is still distorting decisions.
Build one practical workflow that improves decision speed, reporting quality, or commercial control in a real operating environment. This can include analytics automation, decision support, or applied AI, but the objective is measurable value, validation, stakeholder adoption, and repeatable execution. I can help design it and build it, not just recommend it.
Practical training for sales, finance, analysts, managers, and executives who need better judgment around forecasting, pricing, CRM, reporting, and applied AI without hype, unsafe habits, or fragile processes. The training is grounded in real build and delivery experience, not generic awareness material.
Engagement Flow
The process is designed to reduce ambiguity fast, create visible progress early, and leave the business with a stronger operating model after delivery. It is built for real execution, not endless transformation theater.
Start Diagnostic ReviewWe go into the business challenge, data landscape, and review rhythm deeply enough to separate symptoms from root causes.
I define a tailored approach with clear milestones, decision owners, success measures, and realistic timelines.
The work moves in iterative sprints so you can see progress, challenge assumptions, and steer before the solution hardens.
Deployment includes documentation, governance, and practical knowledge transfer so the work remains useful after launch.
Investment
The right format depends on how clear the problem already is. My recommendation is to publish the first paid step, because it lowers friction and filters for serious buyers, but not pretend larger implementation work can be responsibly priced from a website alone.
20-minute qualification call to confirm fit. No free consulting.
Free
Best when you want to check whether the issue is real, urgent, and worth the diagnostic
90-minute working session plus written summary covering forecasting, pricing, margin, CRM, reporting, service workflow, and AI-tooling decisions
EUR 950 net
Best public price to show because buyers can understand the value and you retain control over larger scoping
Vendor diligence, prioritization sprints, workflow deployment, foundation repair, enablement, and advisory support
Scoped after diagnosis
Best when the workflow, decision owner, data burden, and risk profile need to be understood before a credible commercial quote
For DACH B2B work, public prices should normally be shown as net and then scoped formally with VAT treatment handled at quote stage if applicable.
It is built for Managing Directors, Finance Directors, Commercial Directors, Sales Directors, COOs, Transformation Leads, and Heads of BI or Analytics who know the numbers are not trusted.
Forecast inaccuracy, pricing confusion, unexplained margin movement, CRM quality issues, KPI disputes, dashboard sprawl, overloaded analysts, and applied AI pilots that never land operationally.
Both. I diagnose the commercial decision-system problem first, then help design and implement the right analytics or AI workflow with validation, governance, and adoption in mind. That includes hands-on implementation where the engagement calls for it.
Yes. Most work is remote, with structured workshops, async review, and regular working sessions. I am based near Stuttgart and can support DACH onsite work where needed.
Yes. That is one of the clearest places I can save money for a client. I help teams understand what the vendor is actually selling, where data goes, what the review burden looks like, and whether the right answer is off-the-shelf software, an OpenAI API workflow, or tighter internal control.
If there is a strong fit, I scope the next step clearly: Diagnostic Review, AI Software & Vendor Due Diligence, Prioritization Sprint, Foundation Fix, workflow deployment, or team enablement. No vague transformation language and no AI theater.
Ready to Get Started?
If the numbers are not trusted, the customer-service workflow is noisy, or the AI tooling choice is unclear, the issue is usually logic, ownership, or governance before modeling. Start there, then decide what should actually be built after a 90-minute working session and written summary. The outcome is practical clarity from someone who understands both the business pressure and the implementation work.