Artificial Intelligence Experts in Munich

Product:

• Built a production-ready AI platform for generating brand-aware marketing images and videos from product data, user requirements, and uploaded media.
• Own the platform architecture, technical roadmap, API design, security, deployment workflow, operational reliability, and model-provider strategy.
• Developed the core platform in .NET and built supporting AI and workflow prototypes in Python, applying language-independent API contracts and structured interfaces between services and model providers.
• Implemented reliable background processing with RabbitMQ, persisted workflow state, idempotent handling, retries, failure recovery, logging, secure storage, authorization, and credit accounting.
• Made pragmatic build-versus-buy and model-routing decisions based on reliability, latency, cost, and maintainability rather than novelty.

Agent Orchestration & RAG Systems

• Built and compared agent workflows using Microsoft Agent Framework, LangGraph, and LangChain, including tool use, conditional routing, clarification steps, state management, and hand-offs between agents.
• Implemented reusable .NET components for agents, prompts, tools, model providers, structured responses, and retrieval with pyvector, making it easier to change AI providers without rewriting the core workflow.

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.

• A recurring problem in my own AI-supported projects: requirements analysis, use cases, and architecture decisions can be created quickly with AI support, but they remain hard to trace and scattered across Markdown files – knowledge is lost as soon as it is no longer in the context window. arknet turns requirements engineering and architecture knowledge into structured, verifiable data instead of plain text: requirements, use cases, and architecture decisions as a continuously linked knowledge graph, traceable from the requirement to the architecture decision – queryable for both people and AI agents alike. Technically based on RDF/OWL and its own MCP server.

• Result: MCP daemon running, Docker image automatically published on GHCR, nine hexagonal modules, eleven ADRs (including an open-core licensing model). Requirements engineering and ubiquitous language hexagon active. Publicly available since 07/2026 as a Community Edition under Apache-2.0 (github.com/kogn-io/arknet), together with the Claude Code plugin and the GHCR image; open-core model.

• Label: Java, Maven, RDF, RDF4J, OWL, SPARQL, Model Context Protocol, Spring AI, Docker, GitHub, Git, Claude Code, Obsidian, DDD, Hexagonal Architecture, ArchUnit, JUnit, AssertJ

• 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.

• Deployment and scaling of existing ML initiatives, including demand and cash flow forecasts.
• Building robust monitoring with mlflow for data stability, model performance, and drift detection, as well as implementing additional ML use cases.
• Further development of an Agentic AI chatbot for transparent and easy-to-understand model explanations.

• Designed role-based delivery assignment workflows, switchable between own fleet and partner carriers, with traceable status chains from „pending“ to „in delivery.“
• Designed AI-assisted route optimization, where dispatchers review drive-time-optimized route suggestions as drafts and apply them in one click.
• Designed a central planning interface for delivery and route management, bringing table view, map view, and route composition into a single workflow.
• Built interactive prototypes to align new product features early with stakeholders and engineering.

Key methods: AI-assisted Product Design, Workflow Design, Role-Based Workflows, Dashboard Design, Interaction Design, Prototyping, Logistics/Operations UX, Stakeholder Collaboration

• Led enterprise reporting modernization by migrating legacy SSRS reporting solutions to Power BI, supporting 500+ business users while ensuring full GDPR/DSGVO compliance.
• Designed and optimized Power BI and Microsoft Fabric semantic models using star schema, dimensional modeling, advanced DAX, and performance optimization techniques, reducing query latency by 25%.
• Delivered 20+ executive and operational dashboards featuring KPI scorecards, drill-through, bookmarks, and row-level security, improving reporting efficiency by 20%.
• Enabled self-service analytics through governed Power BI datasets, dataflows, and gateway architecture, increasing business-led reporting adoption by 35%.
• Configured an incremental refresh policy and query folding for a 50+ million row sales dataset, reducing daily report refresh times by 85%.
• Deployed automated ETL/ELT pipelines using Azure Data Factory, Microsoft Fabric, and Snowflake, reducing reporting delivery timelines by 40% through workflow automation.
• Spearheaded Microsoft Fabric analytics modernization initiatives including lakehouse architecture, OneLake integration, and centralized data platform development, reducing data latency from 2 hours to 20 minutes.
• Translated business requirements from 15+ stakeholders into scalable Power BI semantic models and dashboards, improving reporting consistency and reducing ad-hoc reporting requests by 25%.
• Applied Microsoft Copilot and generative AI tools to accelerate SQL development, DAX authoring, technical documentation, and testing activities, reducing development effort by approximately 15 hours per week.

• Spearheaded efforts to enhance product consistency and achieve significantly better usability, ensuring a more intuitive experience
• Partnered with the founders to define a new go-to-market strategy through product discovery
• Directed the process of creating a new company website from concept and wireframes to design and final implementation in Webflow
• Responsive Webdesign
• WCAG
• Corporate Branding
• Product Discovery
• MVP
• Product Design
• User Experience
• Rapid Prototyping

• Building, implementing and selling automated Data Science solutions such as Scorecard Factory and Forecast Factory
• Implementation of automated end-to-end cloud processes
• Development of LLM and NLP models
• Creation of interactive reports
• Support for national and international large corporations as well as medium-sized companies in implementing ML projects

• Designing AI-first workflows that integrate AI into existing product experiences
• Developing UX concepts for prompt management, reusable and combined prompt workflows, tagging, search and information organisation
• Creating user flows, wireframes, prototypes and high-fidelity interfaces in Figma
• Defining reusable UI patterns, components and interaction logic for scalable products
• Exploring human-AI interaction patterns with emphasis on user control, transparency and manageable cognitive load
• Translating product requirements and technical constraints into developer-ready UX/UI specifications

• AI-native B2B SaaS for freelancer sourcing; DACH market.*

• Enterprise partnerships across four industries: structured and closed multi-stakeholder deals with Telefónica (Telco), Emma Matratzen (Retail), Nürnberger Versicherungen and Flatex (Financial Services), Hubert Burda Media and Serviceplan Gruppe (Media).

• Revenue and growth: scaled FRATCH from €0 to €3.8M annual GMV, with ~80% of revenue sourced from founder-led direct outreach and partner relationships.

• Channel partnerships: sold FRATCH as a SaaS solution to recruiting firms (e.g., YER) — built the partner-enabled motion alongside direct enterprise sales.

• Team build: scaled FRATCH from solo founder to a team of 7 across engineering, product design, operations, and supply outreach.

• Proprietary network asset: onboarded 15,000+ freelancers as registered users — the proprietary DACH network powering FRATCH's matching.

• Built and launched FRATCH GPT (fratch.io/gpt): a production conversational AI agent. Architected the full stack — LLM orchestration, embeddings, re-ranking — with hands-on involvement in technical design and execution.

• GTM build: owned the full go-to-market stack — outbound, LinkedIn (organic + paid), content, and sales enablement.

• Strategic and operational overall responsibility for a specialized agency for UX Writing & Content Strategy
• Product development, client acquisition, and the setup and strategic further development of UX writing systems for clients in the IT and finance sectors

• Tackling challenges in the context of a transformation programme.
• Focus on leadership challenges.

Independent product design practice supporting startups and growing companies with enterprise SaaS, workflow architecture, product strategy, and AI-enabled product development.

• Deliver end-to-end product design for digital products, websites, and SaaS platforms, combining product thinking, UX, visual design, and implementation.
• Apply AI throughout the product lifecycle—from research, synthesis, information architecture, and prototyping to development, SEO, and content strategy.
• Design and build production-ready digital products using AI-assisted workflows, enabling significantly faster iteration and delivery.
• Advise founders and businesses on product positioning, UX strategy, and digital transformation.