Large Language Model Experts in Nuremberg

Medikamendo: E-health platform for digital repeat medication & follow-up prescriptions

• End-to-end implementation: UX conception, UI design, and frontend development for three connected portals (patients, medical practices, pharmacies).
• AI prototyping: Efficient creation of interactive prototypes using Figma and GitHub Copilot.
• Design system: Creation and continuous development of a consistent design system and UI components.
• Corporate design: Maintenance and further development of the consistent brand presence and websites.

Embedded Analytics & AI-assisted BI

Design and development of an integrated analytics solution based on ASP.NET Core, Power BI Embedded, and LLM services to provide context-based business information.

Development of an AI agent with Function/Tool Calling for the secure orchestration of REST APIs, SQL data sources, and technical services within defined business processes.

Building automated BI workflows including workspace management, deployment processes, and scheduled refresh via the Power BI REST API.

Implementation of secure service-to-service communication with Microsoft Entra ID and Service Principal, and integration into existing enterprise system landscapes.

Technologies: ASP.NET Core, C#/.NET, Power BI Embedded, Power BI REST API, LLM API, AI Agents, Function/Tool Calling, Entra ID

• Fine-tuned and evaluated alternative backbone architectures for the AFFGAN handwriting style encoder to better capture writer-specific features, benchmarking against the original baseline architecture and replacing the legacy VGG19 architecture with a custom Transformer-based encoder.
• Extended the system beyond word-level synthesis to line-level handwriting generation, integrating and adapting an existing line-generation architecture to support full-sentence output.
• Deployed the handwriting generation pipeline as a web application, enabling users to select a writing style, input custom text, and instantly generate a corresponding handwriting image.
• Integrated TrOCR into a teacher–student distillation framework to evaluate and improve readability of generated handwriting, improving OCR accuracy by 20% over the baseline.
• Boosted user-study pick-rates by 40%, demonstrating a significant leap in the perceptual quality and realism of the generated handwriting compared to the baseline model.

Tech: PyTorch, Python, GANs, CNN, ViT, TrOCR, Streamlit, CUDA.

• Pioneering work in personalized AI: developing a framework for “Interactive Content” (RAG) for novels, lectures, expert debriefing
• Successful launch of Einbug, the Pantopia chatbot, with media coverage (SZ interview)
• Creating compelling AI personalities: AI blog ([link] 100% personalized learning environments, Perry Rhodan, among others.

• Developed KPI dashboards using Power BI and DAX for 4+ business units, improving reporting transparency and strategic decision support.
• Migrated enterprise finance data views into dbt models, implementing modular SQL transformations, version-controlled data pipelines, and automated documentation to create a scalable analytics layer.
• Built dimensional data models in Snowflake for enterprise finance data, enabling scalable forecasting and supporting executive decision-making.
• Designed end-to-end ETL/ELT pipelines using Snowflake and SAP HANA, integrating data from 3+ enterprise systems.
• Automated monthly reporting workflows using SQL and Power BI, delivering strong business impact by reducing manual effort by 80%.
• Collaborated with finance stakeholders to translate business requirements into analytical data models, supporting strategic decision-making cycles.
• Delivered ad-hoc financial reports using Power BI, reducing turnaround time by 60%.
• Implemented data validation logic in SQL, resolving 95% of recurring data quality issues.

• Delivered 40+ AI projects and 23 strategic consultations for international clients (US, Europe, Middle East), achieving a 98% job success rate and building long-term partnerships.
• Developed and deployed production-grade AI solutions in computer vision, NLP, deep learning, and generative AI (LLMs, RAG pipelines, Stable Diffusion, OCR, chatbots), enabling automation and improving client efficiency by up to 70%.
• Designed and fine-tuned large language models (LLMs), including prompt engineering and integration with enterprise knowledge bases, leading to smarter decision-making and reduced manual effort.
• Built real-time computer vision applications (detection, segmentation, OCR) and integrated them into business systems, significantly enhancing accuracy and scalability.
• Consulted startups and enterprises on AI strategy, architecture, and deployment (cloud & on-premise), accelerating product development and reducing time-to-market.
• Managed complete AI project lifecycles (requirements gathering, solution design, deployment, support) in agile, international, and cross-functional environments, ensuring high-quality delivery.

• Built a CRNN model with VGG16 and BiLSTM backbone for text-based CAPTCHA recognition
• Achieved 9.37% character error rate and 68.36% sequence accuracy on validation data
• Expanded data augmentation pipeline with distortions, noise injection, and clutter to improve robustness
• Conducted detailed error analysis on confusable characters (O, Q, D) and proposed error-specific augmentation
• Tech Stack: Python, TensorFlow/Keras, OpenCV, NumPy, Matplotlib

• Integrated complex AI-based energy system models into the frontend framework, enabling the visualization of insights for 6+ key clients and maximizing energy utilization.
• Maximized energy efficiency and utilization by architecting the seamless data flow between AI models and the user interface for rapid, actionable reporting.

• Built a custom AI chatbot for an e-commerce client using GPT-4 and LangChain with RAG, reducing customer support ticket volume by 45% and improving response accuracy to 92%.
• Designed and deployed an intelligent document processing system using LlamaIndex, Pinecone, and FastAPI for a FinTech startup, enabling semantic search across 100K+ financial documents.
• Developed multi-agent AI workflows using CrewAI and LangGraph for a marketing agency, automating lead research, content generation, and outreach — saving 20+ hours/week of manual work.
• Created AI-powered automation pipelines using n8n, Make, and Zapier integrated with CRMs (GoHighLevel, HubSpot), reducing manual data entry by 80% for a real estate firm.
• Delivered prompt engineering and LLM fine-tuning consulting for multiple clients, optimizing AI model outputs for customer support, content creation, and data extraction use cases.
• Built production-ready REST APIs with Python and FastAPI to serve AI models on AWS and GCP, handling 10K+ daily requests with 99.9% uptime.

• Developed a synthetic data generation framework using 3D simulation (NVIDIA Omniverse) and Generative AI (Stable Diffusion) to model and augment industrial surface defects.
• Trained and evaluated Computer Vision models (YOLO, DETR), achieving 94% detection accuracy on real-world samples and demonstrating successful simulation-to-reality transfer.
• Applied domain adaptation to improve simulation-to-reality transfer, enabling scalable Industrial AI for automated quality inspection and reducing manufacturing downtime.

• Gathered tire images and their feature descriptions.
• Cleaned dataset of image metadata using pandas.
• Stored image feature embeddings in Chroma vector db.
• Used image augmentations to increase dataset size.
• Used sklearn to create shuffled datasets and imbalanced-learn to balance class sizes in dataset.
• Used PyTorch to train and test different neural networks.
• Validated model using custom accuracy metric based on similarity search in ChromaDB.
• Visualized accuracy predictions using matplotlib.
• Plugged trained model into DreamBooth to train stable diffusion model and generate new images of tires.
• Created custom Docker image in Amazon Elastic Container Registry for machine learning script.

• Intent-driven approach to configure all models across all series automotive in all distribution markets of this car manufacturer
• Developed a customer-facing, conversation-driven integration layer to achieve 100% hallucination-free technical configurations
• Utilized Microsoft Azure AI Services: AI Foundry, Agent Service, AI Search; Prompt Shield Services; Content Security; Terraform; API Gateway; AI Gateway; Container Services; Azure Agent SDK; Agent Skills; RAG; MCP Servers and tools

• Focused on exploring the intersection of Music and AI.

• Engineered high-performance APIs with FastAPI + MongoDB, integrating live weather data (NOAA, NWS).
• Developed an AI chatbot with OpenAI APIs — context-aware by location, profession & interests.
• Created admin dashboard APIs for real-time monitoring and zero-downtime configuration.
• Integrated Stripe Embedded Payments with secure transactions & subscription management via webhooks.