Services
Four ways I help.
From building the systems, to advising the boardroom and the cap table, to leading the team, to running the result in production.
AI Leadership & Teams
I embed and build the capability.
Fractional AI leadership that sets up the team, operating model and culture, so the capability outlasts me.
- ·Fractional Head of AI / interim product & transformation lead
- ·Setting up an AI / Data unit from scratch
- ·Hiring, coaching and high-performing teams
- ·Governance and ways of working that pass audit
Advisory & Consulting
I help you decide.
Strategy and diligence for the leaders and investors making high-stakes AI calls.
- ·AI strategy, transformation roadmaps and operating model
- ·Build-vs-buy and vendor / model selection
- ·Investment due diligence on AI deals (Groq, Replit, Together AI)
- ·AI accelerator and hardware selection
AI Automation & Engineering
I build the AI.
Turning manual, compliance-bound processes into AI systems that reach production and survive audit.
- ·Process automation: AML/KYC, credit, onboarding, documents
- ·Agentic systems and RAG on your data
- ·Conversational Voice AI agents, outbound at scale
- ·Automated trading solutions & price prediction models (Mamba/Transformer custom architectures)
- ·LLM evaluation, fine-tuning and MLOps
Managed AI Agents
I run it in production.
The value of an agent is decided after launch: models change, data drifts, regulation moves. I operate agents and automations as a continuous service with outcome SLAs, so the number in the business case keeps showing up every month.
- ·Agent and automation operations with agreed SLAs
- ·Evaluation, drift and cost monitoring in production
- ·A monthly outcome report in hours and euros recovered
- ·Guardrail and compliance updates as models and rules change
Engagements & terms
Fixed scope, agreed before we start.
AI Automation Audit
Fixed fee · 2–3 weeks
The de-risked way to start. I map your highest-cost manual processes, find where AI automation is genuinely safe and high-ROI, surface the compliance and risk constraints up front, and hand you a prioritised roadmap with effort and value estimates.
- ·Prioritised automation opportunities, ranked by ROI and risk
- ·Compliance & data constraints mapped per use case
- ·A clear build-vs-buy and sequencing recommendation
- ·A business case you can take to the board
Compliant Pilot Build
Fixed scope · 6–12 weeks
I build a production-intent pilot of your top use case, with governance, explainability and audit trails designed in from day one, not bolted on afterwards. The goal is not a demo; it is a system your risk team can sign off.
- ·A working pilot on your data and your stack
- ·Governance, logging and explainability built in
- ·Evaluation harness and model-risk documentation
- ·A realistic path and cost to full production
Fractional AI Lead
Monthly retainer
I embed as your senior AI product and transformation lead, covering strategy, vendor selection, team direction and delivery, until your in-house AI capability stands on its own. Senior firepower without a full-time hire.
- ·AI strategy and roadmap ownership
- ·Vendor and model selection, commercial negotiation
- ·Delivery leadership across data, engineering and risk
- ·Coaching so the capability outlasts the engagement
Managed AI Agents
Monthly · outcome SLAs
After a system ships, I operate it. Agents and automations run as a continuous service with agreed SLAs, evaluation and drift monitoring, and a monthly report of what they returned, so the number in the business case keeps showing up.
- ·Agent and automation operations with agreed SLAs
- ·Evaluation, drift and cost monitoring in production
- ·A monthly outcome report in hours and euros recovered
- ·Guardrail and compliance updates as models and rules change
How the Audit works
Week 1
Discovery
Interviews and a walk-through of your highest-cost manual processes and the constraints around them.
Week 2
Analysis
I map the automation opportunities, the ROI, and the compliance and risk that gates each one.
Week 3
Roadmap
A board-ready readout: prioritised, sequenced, costed and de-risked.
Where you sit
Start where you are.
The constraints differ by industry. Pick yours and see the relevant proof, then the next step.
Banking & lending
AI in credit, AML and onboarding that clears model risk.
- ·90%+ of AML/KYC and credit decisioning automated across three countries
- ·Compliance-first delivery model adopted bank-wide at Danske
- ·GDPR-ready data infrastructure, built before the regulation was in force
Asset management
Explainable AI your investment and risk teams can defend.
- ·Explainable AI for fixed income taken to product-market fit and acquisition
- ·Quant modelling, IFRS 9 and credit-loss provisioning
- ·Model risk and audit trails designed in, never bolted on
Enterprise & startups
AI that earns its place in the operation, not the roadmap.
- ·~1M CHF of annual value from enterprise AI at Ringier, across 100+ publications
- ·20,000+ manual hours recovered a year, roughly 12 full-time staff
- ·A RAG assistant lifting session duration 39% for 2M+ monthly users
Founders & investors
AI product strategy, and diligence that reads the model.
- ·Groq advisory: 4.02x net MOIC, 117% net IRR post-carry
- ·$100k to $4.5M ARR as Head of Product at Genesis Cloud
- ·Still building: ProtocolEngine runs eleven agents in production
FAQ
The questions regulated buyers ask.
How do you handle our data and compliance during an engagement?
I work inside your environment and controls: your cloud, your data boundaries, your model-risk process. Nothing leaves your perimeter without sign-off, and governance is designed in from day one rather than bolted on.
Can you work within our model-risk and approval process?
Yes, that is the point. I have shipped AML/KYC and credit automation through a bank's second line of defence. I design for explainability, audit trails and sign-off so your risk and compliance teams can approve rather than block.
Why fixed fees instead of a day rate?
Because AI has changed what a senior day produces. Most consulting buyers now prefer outcome-based engagements over time and materials, and they are right: hourly billing makes you pay for every efficiency your consultant gains. My engagements are fixed-fee and scoped to a result, so AI-assisted speed shows up as faster delivery, not a bigger invoice.
We already work with a large consultancy. Where do you fit?
Alongside them, usually. Big firms bring capacity; I bring the senior, hands-on layer that gets a specific system through model risk and into production. Clients typically use me to define, rescue or harden the AI work, then let their existing partners scale the rollout.
How long is the Audit, and what do we get?
Two to three weeks. You get a prioritised set of automation opportunities ranked by ROI and risk, the compliance constraints mapped per use case, and a business case you can take to the board.
Do you build, or only advise?
Both. I am hands-on: I fine-tune models, build RAG and agentic systems, and set up MLOps. I also lead strategy and embed as a fractional AI lead. Use me for any point on that spectrum.
Which industries do you work with?
Any company where AI has to work in production rather than in a demo. I have shipped in banking, asset management, media, cloud infrastructure and trading. The deepest experience is in regulated finance, which is the hardest version of the problem, and that discipline transfers: with the EU AI Act, governance is now everyone's question, not just a bank's.