Timo Möbes · AI Workflow Architect
I combine healthcare technology discipline, enterprise support experience, and AI-assisted product shipping to turn messy work into practical systems for consulting, CRM, reporting, lead handling, and SaaS experiments.
What the portfolio proves
Looking for consulting?
Start with a paid AI Workflow Audit if the first automation worth building is unclear, or use OpenClaw when the workflow is already ready for implementation scope.
Workflow audits, agentic operations, human approval gates, and evidence-driven handoffs.
From local SaaS and SEO systems to consulting workflows, shipped fast and verified.
Technical services, regulated environments, GDPR-aware AI work, and clear escalation logic.
Relevant work behind the offer
I started in healthcare technology and technical services, where vague systems break trust fast. That shaped how I build with AI now: useful automation, clear handoffs, human approval where it matters, and evidence that the workflow actually works.
AI workflow audits, implementation scopes, and human-approved automation around lead handling, CRM enrichment, post-call execution, reporting loops, and internal operations.
AI-assisted local directory SaaS with data enrichment, SEO structure, full-stack deployment, and monetization logic for featured listings.
Technical services and AI champion work in healthcare SaaS, including GDPR-aware agent workflows and practical support-process improvements.
Experience
The background is not just a CV. It explains the way I build: keep the workflow clear, protect the human boundary, and verify the system before calling it done.
2025 - Present
Self-employed / OpenClaw direction
Building AI-powered SaaS products and practical consulting systems: workflow audits, implementation scopes, CRM enrichment, lead handling, reporting loops, and approval-gated automation.
2024 - 2025
Doctolib
Second-line technical support for complex product and infrastructure issues, AI initiatives for the German Technical Services team, and GDPR-aware agent workflow work.
2025
Doctolib
Designed a Dust-powered onboarding assistant with four interconnected agents for HR, IT, culture, and role-specific guidance after the Dust AI Agents Hackathon in Paris.
7+ years enterprise consulting and field support across smart home, networking, calibration, customer training, and troubleshooting.
B.Eng. Health Electronics background across embedded systems, microcontrollers, medical-device style documentation, and hardware/software projects.
Earlier media, SEO, content, and event-marketing work that now feeds practical consulting, positioning, and growth-system thinking.
Capabilities, not a random tech wall
The useful part is not knowing a list of tools. It is knowing how to combine them into workflows that people can operate, trust, and improve.
Featured proof
The point is not a long gallery. These are the strongest signals for AI workflow consulting, product shipping, and operational implementation.
Problem
Founder-led businesses have messy workflows, unclear automation priorities, and no evidence loop for what should be fixed first.
Built
Audit-to-implementation spine with human-approved automation around lead handling, CRM enrichment, post-call execution, reporting loops, and internal operations.
Proof value
Shows the consulting operating model behind my current work: diagnose first, scope tightly, build practical systems, keep approval gates where they matter.
Problem
Local gym discovery in Cyprus is fragmented, search intent is underserved, and monetization needs a clean directory structure.
Built
Business data enrichment, SEO content structure, full-stack directory deployment, local search pages, and featured-listing monetization logic.
Proof value
Shows end-to-end product thinking: market research, data processing, web development, SEO, monetization, and deployment.
Problem
Research across tools and sources gets slow, inconsistent, and hard to compare when the workflow is manual.
Built
LangGraph/OpenAI/Firecrawl/Pydantic workflow for discovery, scraping, structured extraction, comparison, and recommendation output.
Proof value
Shows agent architecture, structured data flow, and useful automation beyond a toy chatbot.
Simplify Yourself website remake — modern responsive rebuild, PWA work, Three.js interactions, SEO/performance cleanup.
Interactive portfolio — Next.js, TypeScript, Tailwind, Framer Motion, 3D background, chatbot integration.
ECG and blood-pressure monitoring projects — embedded systems, microcontrollers, sensors, wireless data, hardware/software integration.
3D printer monitoring — Raspberry Pi, OctoPrint, remote monitoring, Linux, safety logic.
PDF to MP3 converter — Python accessibility utility for turning documents into audio.
How I work
These principles are the bridge between my portfolio and the work I do through OpenClaw: practical automation with clear boundaries.
The workflow worth fixing first is rarely the loudest one. Diagnose the constraint before building the agent.
For client-facing, money-moving, or reputation-sensitive work, the best system keeps humans in the right loop.
A workflow is not finished because the demo looked good. It needs logs, checks, handoffs, and proof that the output arrived where it should.
The useful system is usually smaller than the exciting one. Start narrow, prove value, then extend deliberately.
Turn proof into a workflow
If you have a messy lead, CRM, reporting, follow-up, or internal workflow, book the OpenClaw AI Workflow Audit. We map the current process, identify the highest-leverage bottleneck, and decide what AI can safely prepare before anything gets built.
Paid 60-minute diagnostic session through OpenClaw Consulting.
Book via OpenClawSee OpenClaw firstBackground
The formal background supports the practical work: engineering fundamentals, healthcare/regulated context, AI training, data tools, and technical service pressure.