01 · Primary offer

Readiness
Reviews

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.

Book a diagnostic audit call

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.

Segment-specific review outcomes

University spin-outs

Spin-out Product & Data Readiness Review

Controller, processor, data-flow, and infrastructure questions made explicit.

Healthtech startups

Healthtech Data & Architecture Readiness Review

Data-flow and architecture risks mapped in language founders and engineers can act on.

AI SaaS founders

AI Product Evidence Review

System boundaries and personal-data flows captured in a form technical and non-technical reviewers can use.

Funding or diligence prep

Funding / Due Diligence Technical Readiness Review

Top risks prioritized by business impact and engineering effort.

AI-built app operators

AI-built App Production Readiness Review

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.

For AI SaaS founders

AI Product Evidence Review

An engineering-led review for AI teams preparing for customer, procurement, pilot, funding, or regulatory scrutiny. It makes product and data assumptions explicit, identifies missing evidence, and turns the result into work your team can ship.

What I review

  • Product, model, integration, vendor, and responsibility boundaries
  • Personal and sensitive-data flows
  • User disclosure and transparency
  • Human oversight and escalation paths
  • Logging, traceability, versioning, and change control
  • Evidence needed for customers, pilots, procurement, or diligence

What your team receives

  • Bounded system and data-flow map
  • Risk and evidence register
  • Disclosure and oversight findings
  • Documentation and evidence gap matrix
  • Prioritized 30-day engineering backlog
  • Founder or team readout

The €1,200 Diagnostic Audit is the fixed-scope entry point. This is engineering-led readiness work, not legal advice, certification, conformity assessment, or a guarantee of compliance.

Discuss an AI evidence review

Illustrative output

From system assumption to owned engineering work

A review connects the product boundary, evidence gap, risk, owner, and next action. This fictional example shows the level of specificity, not a client finding.

System boundary

AI-generated customer communication

Application sends customer content to a hosted model provider, then presents an editable draft to an authorised user.

Evidence gap

Disclosure state, model/version record, reviewer action, and retention behaviour are not captured together.

Risk / owner

Customer assurance and traceability
Product + Engineering

Priority

Before pilot

Backlog item

Record disclosure version, model/provider version, human-review outcome, and retention rule for each generated communication; expose the record in the internal review view.

Three ways to work together

Tier 1

Diagnostic Audit

€1,200 fixed

The easiest first step when you need a senior technical read on architecture, data flow, privacy, and compliance risk.

  • +60-90 minute call
  • +Architecture and data-flow review
  • +Risk register
  • +DPIA/data governance gap notes
  • +Top technical/compliance issues
  • +30-day engineering backlog

Early prospects, founders with a specific concern, or teams deciding whether deeper work is needed.

Book a diagnostic audit call

Tier 2

Deep Audit + Roadmap

€3,000-€6,000

A serious consulting engagement for teams preparing for scale, funding, regulated customers, or investor/client diligence.

  • +Codebase and infrastructure review
  • +Data-flow map and privacy review
  • +GDPR, DPIA, and governance gap notes
  • +AI/data governance risks where relevant
  • +Integration/discoverability notes where relevant
  • +Prioritized engineering backlog
  • +Founder/team presentation

Seed to Series B teams, AI or sensitive-data products, and teams that need a concrete engineering roadmap.

Plan a deep audit

Tier 3

Fractional Technical Leadership

€2,000-€6,000/month

Recurring technical leadership after the audit, so architecture, privacy, security, and diligence work stays owned.

  • +1 day/week technical leadership
  • +Architecture review
  • +Compliance-aware product planning
  • +Dev team oversight
  • +Security/privacy hygiene
  • +Vendor/platform decisions
  • +Investor/client due diligence support

Teams that need ongoing senior judgment without hiring a full-time CTO or staff/principal engineer.

Discuss technical leadership

How the funnel works

01

Conversation

We confirm stage, product risk, data sensitivity, and whether an audit is worth doing.

02

Diagnostic audit

You get a focused read on the main technical and compliance risks plus a 30-day action plan.

03

Roadmap

If the risk is material, the deep audit turns code, infrastructure, data, and compliance findings into priorities.

04

Monthly technical leadership

For teams that need continuity, I stay involved as a fractional technical leader and steward the decisions that follow.

Best for

  • +University spin-outs leaving research infrastructure for commercial deployment
  • +Healthtech and AI startups handling sensitive or regulated data
  • +Founders preparing for hospital, university, public-sector, investor, or enterprise review
  • +Teams with engineering capacity who need senior prioritization before implementation

Not the right fit if

  • -Pure legal advice or formal legal sign-off
  • -Checkbox compliance without engineering follow-through
  • -Pre-idea founders who do not yet have a product, repo, or data flow to review

Proof points

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

Implementation support

Compliance Engineering

Hands-on implementation of privacy controls, documentation, and audit-ready engineering changes.

Ongoing support

Engineering & Architecture

Monthly architecture review, product planning, privacy hygiene, and diligence support.

Have questions? Email first, or book a diagnostic audit call.

[email protected]Book a diagnostic audit call