University spin-outs
Spin-out Product & Data Readiness Review
Controller, processor, data-flow, and infrastructure questions made explicit.
01 · Primary offer
Engineering-led reviews for healthtech, AI, and research-led software teams preparing for customers, funders, regulatory scrutiny, or technical diligence. I help teams understand architecture, data-flow, GDPR/privacy, and AI governance risk, then turn it into practical engineering priorities.
This is engineering-led readiness work, not legal advice. The goal is to help founders and technical teams see risk clearly, prioritize remediation, and work more effectively with legal, security, or regulatory specialists where needed.
University spin-outs
Controller, processor, data-flow, and infrastructure questions made explicit.
Healthtech startups
Data-flow and architecture risks mapped in language founders and engineers can act on.
AI SaaS founders
AI/data governance exposure translated into implementation tasks.
Funding or diligence prep
Top risks prioritized by business impact and engineering effort.
AI-built app operators
Security, privacy, dependency, and ownership risks surfaced before launch.
Each review is scoped around the same practical outputs: data-flow map, risk register, DPIA/data governance gap notes, architecture risk review, integration or discoverability notes where relevant, and a prioritized engineering backlog.
Tier 1
€1,200 fixed
The easiest first step when you need a senior technical read on architecture, data flow, privacy, and compliance risk.
Early prospects, founders with a specific concern, or teams deciding whether deeper work is needed.
Book a diagnostic audit callTier 2
€3,000-€6,000
A serious consulting engagement for teams preparing for scale, funding, regulated customers, or investor/client diligence.
Seed to Series B teams, AI or sensitive-data products, and teams that need a concrete engineering roadmap.
Plan a deep auditTier 3
€2,000-€6,000/month
Recurring technical leadership after the audit, so architecture, privacy, security, and diligence work stays owned.
Teams that need ongoing senior judgment without hiring a full-time CTO or staff/principal engineer.
Discuss stewardshipWe confirm stage, product risk, data sensitivity, and whether an audit is worth doing.
You get a focused read on the main technical and compliance risks plus a 30-day action plan.
If the risk is material, the deep audit turns code, infrastructure, data, and compliance findings into priorities.
For teams that need continuity, I stay involved as a fractional technical steward.
11+ years shipping production software
Sensitive-data systems for 5,000+ users
Healthcare, AI, education, and SaaS delivery
Architecture, privacy, GDPR, DPIA, and AI governance readiness
Have questions? Email first, or book a diagnostic audit call.