I help small and mid-sized businesses in Munich and worldwide discover, validate, and plan where AI can make a real difference — before investing in full-scale projects.
With a background in machine learning engineering and hands-on experience in LLMs, automation, and optimization, I bridge the gap between technical possibilities and business impact.
Whether you want to explore AI opportunities, test a proof of concept, or develop a roadmap for adoption, my focus is always the same: fast validation, measurable value, and practical next steps.
Most small and mid-sized businesses know that AI can make them more efficient — but they’re unsure where to start or what will actually work. The AI landscape is moving fast, and it’s easy to waste time exploring shiny tools or expensive pilot projects that never create real impact.
The AI Opportunity Sprint is a structured, time-boxed engagement that helps you quickly cut through the noise. In just 2–4 weeks, we identify, prioritize, and validate your most valuable AI opportunities — combining strategic insight with hands-on technical exploration. You’ll walk away with clarity, a validated proof of concept, and a practical roadmap to scale what works.
1. Discovery & Process Mapping
We start with an in-depth look at how your business operates — your workflows, repetitive tasks, pain points, and data sources. Through short interviews and process mapping, we uncover where automation, prediction, or intelligent data handling could save time or reduce costs.
2. Opportunity Identification & Scoring
Next, we translate those insights into concrete AI use cases. Each idea is evaluated for impact, feasibility, and ROI potential using a simple scoring framework. You’ll see clearly which initiatives are worth testing first — and which ones to skip.
3. Proof of Concept (PoC) Validation
For the top-ranked opportunity, I build a lightweight prototype using your real data (or realistic synthetic data). The goal is to show — quickly and tangibly — whether the idea delivers measurable business value. This could be anything from automating document processing or forecasting demand to creating an internal AI assistant that speeds up decision-making.
4. Results, Roadmap & Recommendations
At the end of the sprint, you receive a clear, actionable report:
– A ranked list of validated AI opportunities
– Insights from the proof of concept (performance, impact, next steps)
– A roadmap outlining how to scale or integrate the solution into your existing systems
– AI Opportunity Report — Ranked list of high-ROI ideas tailored to your workflows and data.
– Validated Proof of Concept — A working demo that demonstrates value within weeks.
– Strategic Roadmap — Clear next steps for scaling, integrating, or further developing the solution.
– Executive Debrief — Walkthrough of findings, results, and recommendations in plain business language.
The AI Opportunity Sprint is designed for speed, clarity, and impact — not endless analysis. You get the best of both worlds:
– The strategic perspective of a consultant who understands business processes,
– And the technical depth of an engineer who can quickly prototype real solutions.
Instead of betting on long, uncertain projects, you can test and prove value fast — with minimal risk and measurable results.
The AI Opportunity Sprint is designed for speed, clarity, and impact — not endless analysis. You get the best of both worlds:
– SMEs exploring AI for the first time
– Companies with scattered automation ideas but no clear plan
– Teams wanting to test and demonstrate AI impact before major investment
– Business leaders who want to align technical innovation with tangible ROI
After a sprint, clients usually:
– Identify 5–10 promising AI use cases ranked by ROI potential
– Validate one of them through a small proof of concept
– Gain a clear, actionable roadmap for implementation
– Build internal confidence and alignment on how to move forward with AI
Each sprint lasts 2–4 weeks, depending on the scope and data availability. It’s fully remote but can include in-person workshops around Munich if desired. All meetings are short and focused — respecting your team’s time and ensuring momentum throughout.
→ Outcome: You leave the sprint knowing exactly where AI can help your business, what works, and how to move forward — with proof, not guesswork.
Once you’ve identified and validated your most promising AI opportunities, the next step is to turn them into working, scalable solutions. That’s where my AI Roadmap & Implementation Support service comes in.
Many companies struggle to move from successful prototypes to real deployment. Projects stall because the technical requirements are unclear, vendors oversell, or internal teams lack AI expertise to manage integration confidently. I help you avoid those pitfalls — guiding you from concept to production with a clear, practical roadmap and hands-on support.
1. Strategic Roadmap Development
Together, we translate your validated ideas into an actionable AI roadmap — outlining scope, priorities, technical options, data needs, and potential ROI. The roadmap gives your team clarity on what to build, what to buy, and in which order to act.
2. Vendor & Technology Selection
Whether you’re choosing between SaaS tools, cloud services, or custom solutions, I provide independent advice based on your goals and constraints. You’ll get transparent comparisons and recommendations — not sales pitches — so you can make decisions with confidence.
3. Technical Design & Oversight
I help your internal or external development teams design the technical architecture, define success metrics, and ensure that data handling, integration, and scalability are set up correctly from the start. My role can range from strategic advisor to hands-on technical lead, depending on your team’s capacity.
4. Implementation Support & Quality Assurance
Throughout implementation, I stay involved to ensure the project stays aligned with business objectives, timelines, and budgets. I review deliverables, validate results, and help your team overcome technical roadblocks as they arise.
– AI Roadmap Document — A clear, step-by-step plan for implementation and scaling.
– Vendor & Tool Recommendations — Independent guidance on the best-fit technologies.
– Implementation Oversight — Technical and strategic support throughout the build phase.
– Measurable Outcomes — Defined KPIs and success metrics to ensure tangible results.
Moving from prototype to production is where many AI projects fail — not because the idea was bad, but because execution was unclear or overcomplicated. With my background in both machine learning engineering and business consulting, I bridge the gap between technical teams and management, ensuring that your AI initiatives deliver on their promise.
You stay in control, avoid unnecessary costs, and bring your validated ideas to life with confidence.
– Companies that completed an AI Opportunity Sprint or PoC
– Teams ready to scale AI solutions into production
– Businesses needing expert guidance for vendor or tool selection
– Organizations wanting independent, non-biased technical oversight
→ Outcome: You move from proof-of-concept to production — strategically, confidently, and without wasted effort.
Not every company needs (or can afford) a full-time senior AI engineer. But many teams still face critical AI challenges — from reviewing vendor proposals and improving existing models to steering ongoing projects in the right direction.
That’s where my Fractional AI Expertise service comes in. I join your team part-time or on-demand to provide high-level strategic guidance and hands-on technical support, giving you senior-level expertise exactly when you need it — and none of the overhead when you don’t.
1. Flexible Collaboration
You decide the level of involvement — from a few hours per week for reviews and strategy calls to deeper, ongoing project support. I can integrate seamlessly into your workflows, joining stand-ups, advising developers, or supporting your leadership team on key AI decisions.
2. Strategic Oversight
I help you define success metrics, evaluate whether your current AI direction makes sense, and identify where improvements or simplifications can yield the biggest impact. This often includes reviewing external vendor proposals or aligning AI projects with your business goals.
3. Technical Guidance & Review
I act as a senior technical sounding board — reviewing data pipelines, model architectures, evaluation methods, or deployment plans. My goal is to help your team move faster and avoid common pitfalls that slow down AI projects.
4. Hands-On Contributions
When needed, I can contribute directly — refining a model, optimizing workflows, or integrating AI APIs into your existing stack. You get real, immediate progress without the complexity of hiring or long onboarding.
– Strategic Direction — Clear, reality-based guidance for your ongoing AI initiatives.
– Expert Code & Model Review — nsure your solutions are efficient, reliable, and scalable.
– Collaborative Support — Seamless integration into your team and processes.
– Measurable Results — Immediate technical impact combined with long-term capability building.
AI projects often fail not because teams lack effort — but because they lack the right kind of expertise at the right moment. Fractional AI support gives you access to a senior AI/ML engineer and advisor who can help your team stay on track, make better technical choices, and deliver results faster — without the cost or risk of a full-time hire.
This approach works especially well for SMEs and startups that are experimenting with AI, scaling early prototypes, or managing external AI vendors.
– Companies running ongoing AI or data projects
– Teams with developers but lacking senior AI/ML leadership
– Startups needing interim or part-time AI expertise
– Businesses wanting independent expert review of external solutions or vendors
– Reviewing and improving existing ML or LLM implementations
– Supporting internal teams during critical delivery phases
– Evaluating AI tool options and integration strategies
– Providing technical leadership during transitions or scaling phases
→ Outcome: You get ongoing, high-level AI expertise — flexible, practical, and perfectly aligned with your needs.
Artificial Intelligence (AI) is no longer reserved for big tech companies. Small and medium-sized enterprises (SMEs) in Germany, Europe, and worldwide can now take advantage of affordable AI solutions to save time, cut costs, and unlock new opportunities. From automating document workflows and improving customer support to forecasting demand and optimizing energy usage, AI can be integrated into everyday business processes with measurable results.
On this page, you’ll find a comprehensive list of practical AI applications for SMEs — including concrete examples of how AI can create real business value. Whether you run a manufacturing company, a service provider, or a family business, these use cases will show you how AI consulting and workflow automation can be applied in your company today.
AI can read, extract, and process information from large volumes of text, images, and even video — reducing manual work and minimizing errors.
Examples:
– Automatically extract key information from invoices, contracts, tax forms, and emails.
– Turn scanned PDFs or images into structured, searchable data.
– Summarize long compliance documents or translate legal text into plain language for decision-makers.
– Detect missing clauses or risky terms in contracts and agreements.
– Translate any document to another language.
AI-powered assistants can improve customer service while saving staff resources.
Examples:
– Build a custom AI chatbot for your company website that answers FAQs 24/7.
– Automatically draft and send personalized responses to customer emails.
– Analyze customer feedback sentiment from surveys or social media.
– Generate tailored marketing copy, ads, and newsletters.
AI helps automate repetitive processes and supports employees in their daily work.
Examples:
– Draft contracts, business reports, or presentations automatically.
– Generate professional website content or product descriptions in seconds.
– Use speech-to-text for meeting notes, or generate slides from internal documents.
– Teach employees how to use tools like ChatGPT effectively to save time in research, reporting, or documentation.
By analyzing historical and real-time data, AI provides predictions and recommendations that improve decision-making.
Examples:
– Demand forecasting to reduce storage costs and optimize supply chain planning.
– Predict seasonal trends for better resource allocation and workforce planning.
– Optimize energy usage and electricity purchases to cut costs.
– Suggest optimal machine settings in production to increase yield and reduce waste.
AI makes company knowledge accessible and usable — even across unstructured documents.
Examples:
– Make thousands of internal documents, images, and videos fully searchable.
– Build an AI-powered knowledge assistant that answers employee questions based on company policies, manuals, or technical guides.
– Classify incoming emails, tickets, or documents into the right categories automatically.
AI bridges different data formats and creates synthetic data where real data is limited.
Examples:
– Convert speech or video into text for analysis.
– Generate realistic synthetic time series data for testing business scenarios.
– Create synthetic energy consumption profiles to simulate PV/battery sizing before investment.
– Produce synthetic customer behavior data for marketing experiments.
AI can detect errors, anomalies, or risks earlier and more reliably than manual checks.
Examples:
– Computer vision models for detecting defects in production lines.
– Automatic classification of quality inspection images or sensor data.
– Monitor operations and raise alerts when patterns indicate maintenance needs.
AI supports better financial decisions and opens up new opportunities in markets.
Examples:
– Analyze company performance data to spot new business opportunities.
– Use AI for cashflow forecasting and risk assessment.
– Apply predictive models to stock or commodity market data for investment insights.
– Automate reporting for tax or compliance purposes.
AI is not just for large corporations. With today’s technology, small and medium-sized businesses can also automate tasks, gain deeper insights, and improve profitability without huge upfront investments.
