Grok Experts in Germany

• 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).

End-to-end responsibility for all products - concept, architecture, development, and production operation as the sole developer; in addition, customer meetings, proposals, and marketing.

Underwriting Copilot - AI assistant for industrial insurance (in production at customer sites)

• Supports underwriters in analyzing industrial insurance submissions - in production use at an industrial insurer.
• Framework-independent RAG architecture with Hybrid Search (BM25 + pgvector) across large, mixed document sets.
• Two-stage evaluation and observability pipeline (code assertions + LLM-as-Judge) that makes answer quality, retrieval accuracy, and citation integrity measurable in a regression-safe way.

Kaiki Menu Analyzer - Data intelligence platform (in production at customer sites)

• Automatically captures and analyzes menu data from around 25,000 German restaurants.
• Scalable 7-container architecture (FastAPI, partitioned PostgreSQL, Redis/RQ) with LLM-supported extraction of structured data from PDF, HTML, and images.
• Full CI/CD pipelines (GitHub Actions), production cloud deployment, interactive dashboards (Dash).

Kaiki GEO Atlas - GEO platform (in production at customer sites)

• Measures brand visibility across five AI engines (ChatGPT, Gemini, Perplexity, Grok, Claude), each augmented with web search, orchestrated as a DAG workflow pipeline (Dispatcher → Sub-workflows → Scoring → Report) with fail isolation.
• 6-container deployment (FastAPI, Celery, Redis, PostgreSQL); LLM cost estimation, PDF audit report, rule-based cross-signal insights (no extra LLM cost).

Data Pipeline & Analytics Platform - competitive analysis in the automotive aftermarket

• Automated data pipeline with gap analysis algorithms and role-based access control; 230+ tests.
• Backend with FastAPI, PostgreSQL, SQLAlchemy.

Product development (actively in progress)

BankingGPT - AI assistant for complaint management in cooperative banking

• Security architecture at the core: no AI draft reaches the customer without human approval - the approval decision is in auditable code, not in the language model (monotonic: the model may escalate, never downgrade).
• Real agentic building blocks, each with its own boundary: the model chooses tools itself through an MCP server (read-only, allowlist, capped, fail-safe); sensitive cases are handed off via an open A2A protocol (JSON-RPC, Agent Card, message/send/tasks/get; client implemented by me) to a separate specialist agent (securities/law), which never lowers the review requirement (pinned by test).
• Evaluation-driven over ten analysis rounds; uncovered a security flaw through independent review and blind tests that nine automated runs had missed.
• Voice AI frontend, responding live: covered cases are answered in the conversation, sensitive ones escalate before generation; response latency < 7 s measured (local GPU STT/TTS).

Stack & production readiness: Python, pydantic-ai, FastAPI/Celery, PostgreSQL/pgvector, FastMCP, fasta2a, Docker; multi-tenant capable (physical vector isolation per tenant), PII encrypted, OWASP-LLM reviewed, 275 tests, CI/CD; vendor-portable (Ollama / EU Cloud Vertex).

After-Sales Assistant - agentic RAG/GraphRAG assistant on public OEM manuals (automotive after-sales)

• Genuinely agentic on LangGraph: ReAct agent with four tools and conversation memory - the model decides on its own whether to use the manual (RAG, Chroma), a knowledge graph (GraphRAG, Neo4j/Cypher - decodes warning lights), or a workshop/booking service.
• Human-in-the-Loop before the irreversible action: before every appointment booking, the graph pauses (interrupt) and gets the driver's explicit confirmation - the same approval-before-action discipline as in BankingGPT, in a different framework.
• Eval as CI gate: a three-part scorecard (RAGAS grounding + deterministic tool-routing accuracy + DeepEval safety: does the answer mention the warning first when there is a critical warning?) blocks the pipeline; provider-agnostic (OpenAI/Azure/Anthropic), FastAPI with token streaming.

Stack: Python, LangChain/LangGraph, Chroma, Neo4j, RAGAS/DeepEval, FastAPI, Docker.

• Developed YourBestChance.io, an AI-powered career resilience platform that leverages advanced machine learning to provide personalized guidance and resources for users.
• Architected and implemented a Retrieval-Augmented Generation (RAG) system supporting three languages, utilizing GPT-based large language models (including OpenAI and Grok variants) integrated with specialized vector databases for efficient semantic search and similarity matching.
• Built an interactive AI chatbot powered by generative AI and RAG pipelines to deliver real-time, context-aware responses and enhance user engagement.
• Optimized data pipelines and AI infrastructure for scalability, ensuring robust performance under increasing loads and reducing latency by 50%.
• Developed comprehensive AI strategies using ML and Gen AI to create customized growth plans; analyzed company data to identify strengths, weaknesses, risks, and opportunities for AI integration.
• Defined ethical frameworks for AI deployment, assessed workforce and leadership upskilling needs, and built phased action plans (short-, mid-, and long-term) with targeted AI integration recommendations.

• 145 hrs.
• Consulting and evaluation for replacing the existing d.velop long-term archive (approx. 36 TB) with a more cost-effective read-only archive solution
• d.velop DMS, Azure, NetApp SnapLock, iTernity iCAS
• Technical and logical consulting on how to set up a future archive system cost-effectively.

• Implementation of AI tools to increase data analysis efficiency and decision quality
• Process optimization in financial accounting and controlling to reduce costs and increase transparency
• Development of strategic business plans for market expansion

• Pilot testing local AI environments to explore local AI use cases and cloud-based AI solutions
• Evaluation of AI tools and techniques
• Use of local AI tools with own data sovereignty
• Prompt engineering
• Creation of example environments for speech-to-text, text-to-speech, text-to-image, text-to-video, and image-to-video

Tools: Grok, Perplexity, ChatGPT, Elevenlabs, Github, Ollama, HuggingFace, Open WebUI, Faster Whisper, LibreTranslate, WSL, Docker Desktop, Shotcut, Audacity, Sound eXchange, Ffmpeg, Coqui TTS, Pinokio, Stable Diffusion Web UI, ComfyUI, OWL, Void Editor

• Established and scaled a consulting firm specializing in digital transformation, remote/hybrid work, and leadership strategy
• Advised high-profile German and international business clients, including ARD ZDF Deutschlandradio, Johanniter, Diakonie, Stadtwerke Prenzlau, Bad Salzuflen & Parchim, Landau Media, and EMH
• Bootstrapped and grew the company to a 16-person team with €300K in annual revenue

• Didactical preparation and creation of illustrations, graphics and animations
• Web export and CMS maintenance
• Content planning and creation
• Quality management