EU AI Act Experts in Munich

CXO AI OS is an agent system made up of six building blocks. Instead of using AI as a chat window, it creates a system that understands a company’s context, makes decisions according to its rules, and acts on its behalf.

• For mid-sized companies: a guided sprint followed by operation for a team, department, or prioritized cluster, based on an AI assessment
• For self-employed professionals: a program in which participants build their own agent system
• Sequence in the company: assessment, prioritization, sprint, operation
• Implementation in Claude Cowork or ChatGPT Work, without coding
• Architecture: Chief of Staff, Goals, Advisors, Agents, Context, Catalog

AI telephone assistant platform

Claude Code, Google AI Studio, Python, LLM / Voice-AI, PostgreSQL

• Conception and hands-on development of an AI-supported telephone assistant platform (voice AI / LLM) – from idea and architecture to MVP/product.
• Built agentic workflows and full automations with Claude Code and Google AI Studio.
• Also delivered AI-supported work in client engagements: used Claude Code for governance documentation, requirement drafts, and automations.

• Consulting across two integrated areas: Commercial Strategy (pricing, sales steering, marketing strategy, market expansion, margin management) and Operational Efficiency (process automation, AI integration, workflow design, last-mile automation).
• Development of custom SaaS solutions, explicitly tailored to the specific requirements and processes of each company.
• Delivery of AI training and change management workshops for managing directors and specialist departments, including AI competence training with a certificate of attendance under Art. 4 of the EU AI Act.

• Developing a model-based AI where natural language is interpreted as formal relations.
• Natural language terms are not considered rigid but fluid and can be negotiated in a context so meaning resolves by iteratively specifying.
• Develops all kinds of model solutions.
• Backed by natural language and data annotation.
• Requirements to code and other solutions.

Tasks & results:

• Developed measures to improve management steering during a restructuring program (approx. 80 participants)
• Set up a PMO to ensure transparency, reporting and data-driven decisions
• Created an integration template to transfer team s...

• Governed multi-agent orchestration for regulated, EU-based companies – self-hostable, compliant with the EU AI Act and GDPR („by design“), BYOM (own models/GPU).
• Two-gate governance: agent deliberation + mandatory human approval, full signed audit trail; graduated autonomy model („internal → autonomous per skill“).
• Verified knowledge graph („Company Brain“) with source evidence for every answer; own orchestration framework (Virtual Team Framework).
• Industry solutions for financial services: compliance monitoring, invoice and contract review; hands-on development with LLMs (including Anthropic/Claude), agentic workflows, RAG.
• Building the governance-focused multi-agent platform TeamIntel (see AI reference projects).

• Strategic consulting and implementation of AI-supported automation solutions for service processes (email communication, document handling, review processing, voice agents)
• Technical orchestration using n8n (workflow automation), Claude and ChatGPT (LLMs), as well as custom API integrations into existing enterprise tools
• Measurable customer results: response times reduced from hours to minutes, 8 fewer hours of invoice processing per week, 75% fewer routine calls
• Assessment of regulatory requirements (GDPR, compliance) as part of customer consulting
• Technical Product Ownership (backlog, roadmap, prioritization)
• Formal contracting vehicle for freelance assignments, including 1&1 Telecommunications
• Building & scaling enterprise AI platforms

Introduction: Companies today face two major challenges: maintaining a pristine Workday tenant AND simultaneously developing an AI strategy that goes beyond mere experimentation. With CloudMcFly, I combine 10+ years of experience as a Workday Architect & PMP with cutting-edge AI strategy consulting. I don't offer theoretical concepts; I deliver implementable solutions. Core Services:

• 1. AI Readiness & Process Audit Not every process requires AI. I analyze your HR/Finance processes (Workday & Non-Workday) to identify "low-hanging fruits" for automation and AI integration. Outcome: A concrete action plan including ROI calculation.
• ️ 2. AI Strategy & Governance Roadmap From vision to execution. Together, we define guidelines (Ethics, Data Privacy, EU AI Act) and select the right tools (ChatGPT Enterprise, Copilot, Custom Agents). Outcome: A secure roadmap approved by Management and IT.
• ️ 3. Workday Architecture & Optimization As a certified Architect, I ensure your Workday tenant remains stable while we integrate new technologies (Launch, PEX, Delivery Assurance).
• 4. Enablement & Workshops An "AI Driving License" for your teams. Hands-on workshops on Prompt Engineering, Automation (n8n/Make), and operational efficiency.
• Interested in Pricing & Packages? Visit [link] The AI chatbot on my homepage knows all my consulting packages and can provide immediate details on pricing and availability. Give it a try!

Two parallel workstreams: (1) Tech due diligence for acquisitions and portfolio companies. (2) AI strategy certification and AI governance consulting.

• Tech assessments for PE/VC acquisitions: code reviews, architecture analysis, scalability evaluation

• Tech assessment frameworks and integration roadmaps for portfolio companies

• TÜV SÜD certification program: AI governance, EU AI regulation (EU AI Act)

• Strategic AI roadmap development for mid-market companies

• Delivered several tech DD reports for investment decisions

• Developed integration roadmaps for portfolio companies

• TÜV SÜD 'AI Strategy & Application Expert' (expected 04/2026)

• Topics: Business Analysis, Data Privacy, Data Management, Stakeholder Management, Conceptualization
• This project focuses on developing and implementing a strategic approach for data deletion in SAP systems. The goal is to identify the relevant data and structures during system migration to ensure both data privacy and IT system efficiency. At the same time, downtime should be minimized and regulatory requirements met.
• Development of a comprehensive approach for data deletion in SAP systems, considering data privacy and business requirements.
• Ensuring efficient and structured data transfer to the new system.
• Optimizing system efficiency and reducing downtimes during migration.
• Creating functional and technical concepts to ensure compliant and sustainable data management.
• Topic preparation: Detailed study of the "data deletion" area to lay the foundation for a structured data migration.
• Definition of project structure: Setting roles, interfaces and the project's organizational structure.
• Regulatory requirements: Analysis of data privacy regulations and business requirements to define deletion criteria.
• Approach: Developing possible scenarios and methods for data cleansing and deletion.
• Deletion concepts: Creating functional and technical deletion concepts that structure the implementation and provide clear guidelines.
• Setting deletion criteria: Defining which data and structures to delete or transfer.
• Responsibilities: Clarifying responsibilities within the project team and among stakeholders.
• Analysis of ongoing activities: Identifying and collecting existing activities in the "data deletion" area.
• Effort, cost and timeline planning: Creating estimates for resources, effort and budget.
• Implementation initiatives: Developing and executing concrete measures to apply the defined deletion strategies.
• IT system efficiency: Analyzing the existing IT infrastructure to identify optimization potential for data deletion and transfer.
• Technology trends: Evaluating new technologies and tools that can support the data cleansing process.
• Cost-benefit analysis: Assessing the financial impact of data cleansing and the introduction of new solution approaches.
• Risk management: Identifying potential risks during implementation and developing appropriate mitigation measures.
• This project lays the foundation for a sustainable and compliant data transfer to a new SAP system. With a clear approach to data deletion, it meets data privacy requirements, reduces downtimes and increases the efficiency of the new system. The results and recommendations will help companies develop a future-proof data strategy that meets legal and business needs.

• Developed the AI strategy for a major Austrian retailer with over €10 billion in annual revenue.
• Developed a go-to-market strategy for AI services for a Norwegian consulting firm specializing in SAP technologies.
• Delivered AI for Business training programs to a leading German supermarket chain.
• Defined AI governance project structure and roadmap for a large German manufacturer.
• Certified facilitator for AI Design Sprint™, leading use case discovery workshops for large enterprises.
• IEEE Certified AI Ethics Assessor with expertise in building AI governance frameworks aligned with the EU AI Act.
• Founder of aiethicsassessor.com as knowledge base for AI governance and AI legislation.
• Author of a best-selling Udemy course on Data Architecture.
• Developed intelligent agents using low-code/no-code platforms to automate complex business processes.

• Lecturer for the AI Manager in Insurance certification course

• Built scalable end-to-end machine learning pipelines for a major telco company, covering feature engineering, model development, deployment, and a Streamlit visualization app.
• Initiated and embedded data science within the Customer Experience team, collaborating daily with stakeholders to deliver end-to-end solutions; under my ongoing support, customer satisfaction score, NPS, remained stable at a record >30pt.
• Advised a client on GenAI tools, AI development strategies, and Responsible AI practices, shaping internal adoption and governance approaches.

• Agile setup of a multimodal analysis platform for training materials (video, audio, documents) using Scrum
• Extraction of context-relevant content based on user profiles & competency dimensions
• Personalized delivery of learning content to boost sales performance
• Close coordination with sales teams & stakeholders to validate features
• Use of Gemini, Whisper, Python & JavaScript, deployment on AWS, Perl for scripting data imports
• Integration into existing tools & CRM systems for smooth adoption
• Technologies used: Python, OpenAI, DB tech like PostgreSQL, CI/CD for Airflow DAGs, FastAPI