Overview
Since 2023, alongside my core ventures, I have taken on a select number of technical leadership and advisory engagements with early-stage and growth-stage companies in AI, HealthTech and DeepTech. These range from short-sprint technology audits to longer-term fractional CTO arrangements where I work embedded with a founding team.
These engagements are for companies that need deep technical expertise and strategic thinking, but not necessarily a full-time CTO hire. Whether the need is a rigorous assessment for an investor, architecture guidance during a critical build phase, or hands-on leadership through a transition, each engagement is shaped around what the company actually needs.
What I bring
My background spans hardware, embedded systems, cloud architecture, AI/ML, and regulated product development. That means I can assess and contribute across the full technology stack, not just the software layer. I have built and scaled engineering teams, managed complex regulatory programmes, and brought hard technology to market as both a founder and a technical leader.
Having spent over a decade as a co-founder and CTO in a regulated, high-stakes domain, I understand what separates a technically sound system from one that will hold up under clinical validation, investor scrutiny, or rapid scale. That perspective is what I bring to advisory and fractional roles.
Typical scope
Engagements typically cover one or more of the following:
- Carrying out technical due diligence for investors, assessing a company’s technical maturity, architecture decisions, IP, team capability, and scalability risks, and delivering a written report with clear findings and recommendations.
- Reviewing system architecture and product roadmaps, evaluating technology choices and the feasibility and sequencing of planned work, and identifying gaps and improvement areas.
- Providing interim engineering leadership during a gap, transition, or critical build phase, covering team management, process improvement, and delivery continuity.
- Assessing AI and LLM feasibility, helping companies evaluate whether and how AI-based approaches can create genuine value for a specific product or workflow, and advising on model selection, data requirements, infrastructure, and governance.
- Supporting team scaling and hiring by defining engineering needs, writing role profiles, supporting interview and selection processes, and advising on team structure.
Domain expertise
Most engagements to date have been in HealthTech and MedTech, where I have deep hands-on familiarity with MDR, ISO 13485, ISO 27001, ISO 42001, IEC 62304, and NEN 7510, and extensive experience bringing a medical AI wearable through the full CE marking process.
A growing part of the work is in AI and LLM platforms, covering architecture, infrastructure, and governance for AI products, including private LLM deployments, retrieval-augmented generation, agentic systems, and AI management systems under ISO 42001.
I also regularly work with companies in broader DeepTech and regulated markets, particularly where the product involves embedded systems, hardware-software integration, or multi-disciplinary complexity where the margin for architectural error is low.
Confidentiality
Select engagements are confidential by agreement with the companies involved. Details of specific clients and projects are available on request.
Details available on request. Select engagements are confidential.