Selected work · 2024-2026
Case files
A mix of client engagements and personal systems. Client work is anonymized; the personal projects run on my machines every day.
CASE 01 · PERSONALRunning daily
FRIDAY, a voice assistant that actually does the work
A JARVIS-style voice AI, built end-to-end and always on.
ProblemI wanted hands-free, conversational access to my entire project knowledge base. Not another chatbot in a browser tab.
BuiltWake-word activation, local speech-to-text, Claude reasoning with my knowledge vault as memory, and natural voice replies. On top of that sits a work mode: one spoken instruction kicks off a real autonomous coding task.
OutcomeRuns always-on on my Mac. I hold full spoken conversations about my projects and hand off real tasks by voice.
PythonWhisper STTClaude agentsElevenLabs
CASE 02 · PERSONALRunning daily
Cortex, an AI-operated personal operating system
Everything I work on, tracked and partly run by agents.
ProblemA dozen parallel workstreams (research, client projects, university, applications) and no single place where their state lived.
BuiltA knowledge vault operated by AI agents: living mission-control dashboards with project lanes and timelines, automated session notes, and a morning triage agent that reads my inbox and pre-sorts opportunities before I wake up.
OutcomeOne glance shows the state of everything. The boring parts of staying organized no longer cost me time.
ObsidianClaude CodeAgent workflowsDashboards
CASE 03 · CLIENT · ANONYMIZEDLetter of intent signed
AI regulation monitoring for a German specialist publisher
The market research behind a new AI product.
ProblemCompliance teams at mid-sized companies drown in regulatory change. A specialist publisher wanted to know whether an AI product could carry that load, and whether anyone would pay for it.
My partI ran the market research: market sizing, competitor analysis and business-model options for the product. The findings fed the go/no-go decision and the product's positioning. The prototype itself was built by the engineering team.
OutcomePrototype validated with target users; an established publisher signed a letter of intent.
Market researchCompetitor analysisBusiness model
CASE 04 · CLIENT · ANONYMIZEDIn active use
Agentic lead research with human-in-the-loop gates
Multi-agent pipelines that find real people, and a human who approves every record.
ProblemB2B teams need named, verified decision-makers at target companies. Manual research doesn't scale; fully automated research can't be trusted.
BuiltA multi-agent research pipeline with strict pass/fail validation criteria (current employer verified, role matched by what the person does rather than by title keywords) and a mandatory human review step before anything is written to the CRM.
OutcomeVerified contact discovery at a fraction of the manual effort, without sacrificing data quality. The human-in-the-loop design is the point, not a compromise.
Agent orchestrationHuman-in-the-loopCRM
CASE 05 · UNIVERSITY × INDUSTRYPresented at Pixida, Munich
Eco-Score dashboard on live IoT sensor data
Making the energy behavior of real devices visible in real time.
ProblemDevice energy consumption is invisible until the bill arrives. The industry partner wanted a live eco-score that a non-engineer could read, instead of raw telemetry.
BuiltA real-time dashboard that scores device energy behavior from live sensor streams over MQTT. Team project, delivered against a running backend.
OutcomePresented to the industry partner at Pixida in Munich, 2026.
IoTMQTTLive sensor data