AI Agents Experts in Germany

• AI product development: Design of an AI-supported GRC platform to automate compliance processes.
• AI expertise: Strategic deepening in Agentic AI and GenAI as a core asset for modern IT governance
• IT interim management and strategic consulting

In-house consulting provider and driver of transformation within the group, multi-stakeholder environment and C-level.

Realignment and stabilization of a cross-functional transformation and scaling program within the group. Sharpening the target picture, priorities, and set of measures, as well as building reliable governance, planning, and steering structures. Structuring roles, responsibilities, and strategic initiatives while including AI and IT automation ideas.

• Designed program realignment and project portfolio management

• Developed strategy model and target picture for IT projects

• Structured portfolio, roadmap, and priorities

• Established governance and regular meetings

• Worked out operating model for flagship projects

• Assessed AI and automation ideas

• Clarified roles and responsibilities

• Implemented change measures

• Developed, moderated, and evaluated workshops

• Transformed 17 initiatives into a steering model

• Increased transparency and decision-making ability

• Strengthened commitment in steering

• Sharpened the operating model structurally

• Integrated three top-5 institutes

• Involved over 80% of stakeholders

• Governance

• Portfolio steering (PPM)

• Change management

• Artificial intelligence

• Workflow automation

• AI use case assessment

• Confluence

• Jira

• Stakeholder management

Stabilizing an Azure/.NET landscape in live operation.

• Architecture, DevOps, and operational readiness; technical decisions under time pressure
• Azure DevOps, monitoring, ETL/ELT, cloud security, FinOps, and data-mesh-related topics

Technologies: Azure DevOps, .NET, CI/CD, monitoring, FinOps

• Building a scalable nearshore IT developer hub (Croatia, Czech Republic, Poland) as an independent company using a BOT model (Build – Operate – Transfer)
• Identifying, selecting, and managing full-service agencies; introducing governance and control mechanisms including KPIs, SLAs, and regular service reviews
• Creating and reviewing data processing agreements and framework contracts in coordination with Legal & Compliance; integrating regulatory requirements (including KRITIS) into process design
• Advising on cloud-vs.-on-premise strategies, data storage, and authorization concepts; supporting procurement with tendering and vendor evaluations
• Change management and process harmonization between internal teams and nearshore partners; reporting to management board, CFO, and CIO

Result: Scalable IT developer hub with an audit-proof governance model, lower operating costs, and faster product development.

• Development of a production-ready Enterprise AI solution for the automated processing of invoices and business documents
• Integration of Azure AI Document Intelligence and LLM technologies into existing business processes
• Development of robust REST APIs for automated document processing and system integration
• Extraction, validation, and storage of structured invoice data in Azure SQL as a base for analytics and machine learning models
• Development of an AI-based recommendation engine with machine learning and deep learning to generate personalized product recommendations based on historical purchase data
• Implementation of logging, monitoring, error handling, and validation mechanisms for stable production use
• Collaboration with business teams to define business rules and integrate the solution into existing enterprise processes

Technologies: Python, Azure AI Document Intelligence, Azure OpenAI, Azure SQL Database, REST APIs, Machine Learning, Deep Learning, OCR, Pandas, JSON, Workflow Automation

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.

• Task Engineering: Evaluating Coding Agents.
• Asset Creation: Building realistic task environments using datasets and files in German. Crucially, these assets must remain in the target language to genuinely measure multilingual handling.
• Prompting & Translation: finding failure points where AI does not work, in German.
• Implementation & Verification: Supporting the development of robust solutions (reference implementations) and write highly reliable, deterministic verifier scripts (using rubric-based judging only when strictly necessary).
• Calibration & Execution: Analyze execution logs and calibrate task difficulty (Easy to Very Hard) using standard Terminal-Bench run configurations against various model tiers (Haiku, Opus).
• Quality Assurance: Participation in a rigorous, 4-layer human quality control process (creation, human review, calibration review, and audit) alongside automated LLM-based checks to ensure fairness, grammatical accuracy, and benchmark integrity.
• Linguistic Review: Reviewing AI benchmark tasks across Hindi, Arabic, Japanese, Chinese, Czech and Turkish.

• 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

Most mid-sized companies already have their numbers. What is missing is the translation: a dashboard with forty tiles does not answer a single question that is actually asked in management.

Analysis

• Evaluation of existing data with Python and SQL
• Checking data quality and methodology before making a statement
• The result is an analysis that leads toward a concrete decision

Preparation

• Reports in Power BI and Tableau
• Interactive calculators and visualizations on the web
• Presentations and specialist texts for customers, sales and the public
• Analysis and communication from one source — that

This is what LocalConnect offers you

• Guaranteed 30+ new guests in just 30 days
• Specifically designed for restaurants, hotels, cafés & bars in the DACH region
• More full tables without discounts
• More regular guests who keep coming back
• More positive Google reviews
• More revenue and profit per guest
• Higher occupancy – even on slow days
• Faster recruitment of qualified staff
• Building your own guest database for follow-up offers
• Fully automated WhatsApp marketing system
• Meta ads for predictable guest acquisition
• WhatsApp newsletter for long-term guest retention
• Recruiting campaigns for new staff
• GDPR-compliant implementation
• Turnkey system – we handle the entire setup
• No tech stress and no extra work
• Measurable results through live tracking
• More predictability, security, and sustainable growth
• You focus on your guests – we'll take care of the rest

• Stabilization of customer service, logistics and order processing during a transformation phase
• Management of the international warehouse relocation from Switzerland to Germany
• Optimization of processes and reduction of manual steps in day-to-day operations
• Coordination of international stakeholders to ensure on-time delivery of strategic projects

• Develop custom AI agents delivering 90%+ reduction in manual workload and significant efficiency gains
• Provide end-to-end AI strategy consulting: from digital assessment to implementation and change management
• Design and deliver tailored training programs and workshops on AI adoption, prompt engineering, and automation
• Support clients in implementing scalable AI solutions integrated with existing technology stacks
• Focus areas: AI strategy, automation, workflow optimization, and capability building

• LLM-based features for automated CO₂e data extraction from unstructured documents (70% reduction)

• Agentic AI pipeline for automated Scope 3 emissions calculation with 150,000+ validated data records

• Smart API workflows for real-time carbon footprint calculations in ERP and ESG systems

• ML algorithms to predict emission hotspots and optimize product design

• Automated data validation pipelines with NLP for quality assurance of CO₂e datasets

• Led a 15-person cross-functional team to develop 10+ AI features

• Strategic product planning and AI roadmap with 35% shorter time to market

• Stakeholder management with DAX companies (40% higher satisfaction, 95% retention)

• On-time project delivery with 95% budget adherence through data-driven backlog management

• Agile methods (Scrum, Kanban) with continuous AI/ML integration (25% team velocity increase)

• Product-market fit for AI features through A/B testing and analytics (60% higher adoption rate)

Concept and implementation of a unified-commerce platform for SMEs for selling and building multi-product bundles

Successes: On-time concept, delivery, and customer acceptance of a 100% functional, CPQ-based buy flow process for configuring and selling multi-product bundles within the given 90-day time frame. Successfully tested integration of various interface services for the following areas: customer search, customer data enrichment, address validation, service qualification, phone number validation, credit check, appointment selection, and quote-to-order transition.

Responsibilities:

• Strategic target delivery: deriving and implementing strategic customer goals (e.g. release content, business value).
• Backlog management: creating and refining backlog items (initiatives, epics, user stories, defects) in close coordination with the project team and customer.
• Prioritization & releases: responsibility for prioritizing the product backlog and delivering defined release goals.
• Deliverable tracking: tracking work results on both the supplier and customer side.
• Roadmap & release planning: developing and implementing roadmaps and release plans together with the customer.
• Scope responsibility: responsibility for the contractually agreed scope of services.
• Claim management: active claim and change management toward the customer.
• Team coordination: steering and coordinating the development team.
• Using synergies: making use of synergies between customer projects and product development.
• Offer preparation: preparing offers (with supervision) and presenting them on site to customers and partners.

Skills: development, communication, and implementation of product visions; product backlog management; stakeholder management; regular reporting to management and steering committees; requirements analysis & engineering; planning and documenting workshops; functional leadership and coordination of (distributed) project teams and external service providers; epic management; user story specifications; creating use cases, support with software tests and user acceptance testing (UAT); release management and sprint planning; design of target processes; process optimization; planning, concept, and specification of interfaces to existing and new systems; identification, assessment, and steering of project risks; active claim and change management; facilitation of sprint planning and reviews; data migration; Scrum; Kanban; REST API; JSON; XML; BPMN; UML; Jira; Confluence