Head of Product in Germany

Evidence-led health intelligence platform turning published research into personal health protocols. It scores 430 habits, foods, and supplements against the studies behind them, and moves the score when the evidence moves. Built solo.

• Built the daily ingestion pipeline across PubMed, bioRxiv, and medRxiv: 43,000+ papers from 3,400+ journals processed into 230,000+ typed evidence claims, each one traceable back to the study it came from.
• Designed the six-factor evidence scoring model and the public changelog behind it, so no recommendation ever appears without the papers underneath it. 23,000+ grade changes recorded and explained to date.
• Shipped an entity information model connecting every intervention to its mechanisms, biomarkers, and outcomes: 118 biomarkers with region-specific reference ranges, 77 mechanisms, 32 graded outcomes.
• Built the personalisation layer: blood panel ingestion that reads lab PDFs with a vision model and corrects results for draw time against the user's wake anchor, plus Oura, WHOOP, and Withings integration for daily readiness context.
• Operate eleven specialised review agents over the corpus and codebase, covering paper curation, retrieval quality, health-claim compliance across EU and US regimes, and security.
• Shipped the Evidence Assistant, a RAG assistant that answers from the claim database and cites the underlying papers, plus a B2B practitioner tier, an Expo React Native app, and localisation across 3 languages and 7 markets.

Stack: Next.js 16, TypeScript, Supabase, pgvector, Anthropic Claude, Vercel, DeepInfra.

• Built and validated SupportPiloten, an AI-powered content operations service; won the first paying pilot customer
• Tested agentic workflows with Claude Code and Codex for analysis, research, documentation, and prototyping
• Continued developing my own AI product; training in AI governance, AI compliance, and the EU AI Act (ongoing)

• Project lead for all transformation projects since 01/2018

• Advisory role for the IT development team to ensure the best possible implementation of customer communication workflows within the new IT structure

• Monitoring cross-department process harmonization to create a unified approach for B2B customer communication

• Introduction of a new agile working method, including an optimized IT development process with clearly defined responsibilities

• Reduction of process redundancies by 35% through effective system integration and workflow optimization

• Successful unification of customer communication across three previously separate systems

• Introduction of customer journeys and customer experience

• 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)

Workflow-automation SaaS for operations teams (Berlin, 120 people); full-time freelance engagement reporting to the CEO: an initial 12-month interim mandate, extended twice through the AI build-out; owned product for one squad and coached the other product managers on process.

• Led generative AI (LLM) integration into the core product: from LLM-powered steps to natural-language workflow authoring and step-level automation suggestions, plus AI-managed dynamic workflows, shipped behind eval gates with human-in-the-loop fallbacks: AI-drafted workflows grew to 31% of all new workflows, and median time-to-first-workflow fell from 3 days to 4 hours.
• Packaged the AI capabilities as a usage-based add-on priced on executed automation steps, working with sales and marketing on positioning: ~€800K added ARR in the first year, and adopting accounts churned 1.8 pp less.
• Owned the roadmap end to end: replaced feature-request-driven quarterly planning with an outcome-based rolling roadmap built on quarterly bets and explicit kill criteria, presented monthly to the executive team and quarterly to the board.
• Rebuilt the product-management operating system: weekly customer-discovery cadence incl. workshop facilitation, RFC/decision-doc reviews and a single quarterly metrics narrative; coached four product managers, one promoted to senior during the engagement.
• Closed the engagement as scoped: hired and onboarded the permanent VP Product, handed over the process playbook and roadmap, and exited on schedule in June 2026.

Public sector, regulated environment with legal deadlines and interfaces to justice, finance offices, and authorities. Took over a software product, condition unknown. The handover reported 89 percent completion.

Description / Results:

Review of the current state showed only two months of remaining runtime until year-end. Stabilized the product base in four weeks, including setup. Process logic proven instead of estimated: 181 workflows with 28 steps each verified against the legacy system.

Advising tech companies and founders on product strategy, customer discovery, AI-driven product development, and product operating models.

• Established a new venture focusing on AI-powered UX and rapid prototyping

• Leading the development of an AI-based prototyping framework and prompt optimization for product design

• Managing stakeholder relationships and strategizing go-to-market approaches

• Planning and creating coaching programs (to be launched in 2025) on AI-driven product discovery

• Developed internal processes enabling prototype creation in minutes

• Published best practices and insights on LinkedIn, driving industry interest and awareness

• Developing a product vision and strategy

• Creating a roadmap

• Improving stakeholder communication

• Introducing an outcome-oriented roadmap

• Aligning with stakeholders and creating transparency

• Defining relevant product metrics as a KPI tree

• Initiating measures to improve product quality and measurability

• Supporting the introduction and migration of the new Identity Provider (IDP)

• Responsible for driving digital transformation and aligning country organizations with the Rhenus platform model

• Initiated the digital transformation roadmap for five countries, ensuring alignment with global group strategy

• Built and led a high-performing digital transformation consulting team, expanding delivery capacity from one to three value streams and thereby fast tracking the roadmap from 3 to 2 years

• Acted as strategic advocate for 5 country organizations, ensuring group-wide cross-functional alignment

• Redefined business analysis into an agile approach, reducing time-to-value for platform harmonization by 50%

As a freelance employee / independent consultant, I supported a wide range of development projects and advised clients on digital innovation initiatives. A common role was acting as project manager / product owner at the interface between the client and the development team.

• Product Consulting — (Fractional) Product Owner, Freelance Product Management
• AI Services — AI consulting, training, vibe coding / agentic engineering, AI agents
• Tech Services — full-stack web development, design/UX, MVP delivery.

Led product strategy, cross-functional delivery, and the evolution of the platform and operating model at a VC-backed B2B SaaS company (~60 FTE at peak) operating a multi-sided enforcement platform — connecting brand owners, marketplace operators, and enforcement workflows — scaling from founding-stage concept to commercially validated product.

PRODUCT STRATEGY & BUSINESS IMPACT

• Defined and iterated product strategy aligned to ICP refinement, competitive positioning, and long-term revenue growth
• Refined segment focus to concentrate capacity on highest-value enforcement use cases, improving customer retention and average contract value
• Redesigned pricing and packaging after identifying that a modular, feature-based model was enabling customer cherry-picking and creating confusion at the point of sale. Collapsed a multi-page pricing structure into a single-page, outcome-based model — anchored on what the customer actually wanted to protect, not which modules they selected. Contributed directly to a 10× ACV increase on a key account (€500 → €5,000/month)
• Replaced ad-hoc stakeholder-driven prioritisation with a structured decision framework — coupling OKR alignment, ICE scoring, and a fixed roadmap split (50% strategic initiatives / 30% customer feedback / 20% tech debt) — ending a pattern where sales requests and leadership interventions routinely displaced planned work mid-quarter
• Redesigned the customer onboarding process after identifying a recurring failure pattern: misaligned sales commitments, missing customer-side inputs, and siloed handoffs between sales, CS, and product were routinely delaying time-to-value. Introduced structured pre-onboarding requirements and cross-functional handoff protocols — ensuring customers arrived with the data needed to go live, and internal teams operated from a shared baseline

LEADERSHIP, DELIVERY & OPERATING MODEL

• Built and led a 20-person cross-functional organisation spanning product management, engineering, design, and operations
• Introduced OKR-driven planning and quarterly review cadences, providing consistent strategic alignment across functions and seniority levels
• Built decision-routing frameworks that pushed operational and product decisions down to team level — replacing a pattern where analysts and PMs escalated routine calls (e.g. enforcement actions, edge-case handling) to leadership by default. Defined clear ownership boundaries and decision criteria so the team could act independently on the vast majority of cases, freeing leadership capacity for genuinely non-standard situations

AI-ENABLED PRODUCT & WORKFLOW TRANSFORMATION

• Led the development of an AI-enabled website detection system that replaced much of a previously manual review process, reducing analyst workload by 70–90%
• Redesigned key operational workflows to incorporate AI-enabled classification and decision routing, increasing detection throughput 20× without linear cost growth
• Defined AI product KPIs covering coverage, accuracy, and false positive rate — embedding measurable quality standards into the development cycle
• Defined where automation should replace, support, or escalate human decisions, balancing scale, quality, and customer-facing risk

Freelance work for a large German family office

Built and further developed a modular B2B SaaS platform for professional wealth management and family offices, alongside freelance delivery of production-ready AI, data management, and automation solutions for the wealth management sector.

• Developed an AI governance framework for regulated finance and asset management workflows, aligned with DORA, BaFin-related governance expectations, and data protection requirements, including role definitions, access levels, and decision rules.
• Designed an agentic system with a locally operated open-source language model, including Qwen2.5 via Ollama, for secure querying of an asset database through text-to-SQL-to-text workflows.
• Built AI-supported analysis and reporting capabilities that generate structured answers, tables, and charts from asset data, with domain validation through resolver logic and RAG elements.
• Developed production-grade data import workflows for financial service provider data from CSV, PDF, and API sources, including validation, plausibility checks, and reconciliation with existing asset data.
• Solved the asset matching problem without a cross-system primary key through multi-stage validation rules and human-in-the-loop approvals.

Results:

• Secured EUR 250,000 in SaaS revenue in 2024, exceeding the forecast by 20%.
• Acquired family office clients with EUR 1.6bn in assets under management.
• Reduced manual effort for the largest client by approx. 3 days per month through automated data import and reconciliation processes.
• Reduced operational error risk through structured data validation, multi-stage asset matching, and human-in-the-loop approvals.

• Development of a scalable operating model and commercial concept
• Analysis of market, positioning, revenue, governance, and implementation
• Development of target picture, service model, and go-to-market strategy