Everyone's talking about AI.
Nobody's shipping it.
I build AI systems that actually work in production - not demos. Strategy to deployment in regulated industries where the stakes are real.
- ✓
- Agentic Systems in Production
- 13+
- Years at the Forefront of Tech
- 1,000+
- Users Scaled
- 100%
- Client Retention
- 50+
- Workflows Automated
Services
I solve problems others walk past
Focused on the gap between AI strategy and production reality - where most engagements stall.
Too many tools, no clear path
You're inundated with AI tools and vendors, each promising to transform your business. The result? Analysis paralysis and zero shipping velocity.
Buried in manual work
Your team spends hours on tasks that should be automated. The fix exists - but no one has the time or depth to build it properly.
High stakes, no room for error
You operate in regulated industries where mistakes mean compliance failures or worse. Generic AI tools weren't built for your reality.
No one to own it
You've got consultants who advise and developers who build - but no one who does both and stays accountable end to end.
Process
From first call to production in weeks
Three engagement phases. One accountable person. No hand-offs, no gaps.
- 01Discovery 1–2 weeks
Understand your current state and map the opportunity
We audit your workflows, data, and tooling to identify where AI creates the most leverage. You get a prioritised roadmap - quick wins mapped against strategic plays.
- Current-state workflow audit
- Automation opportunity map
- Prioritised roadmap (quick wins vs strategic plays)
- Technical feasibility notes
- 02Build 4–8 weeks
Ship a production-grade AI system, not a demo
I design, build, and deploy the system - integrated into your existing workflow and tested with real users. No hand-off to a separate engineering team; I own it end to end.
- Working production system
- Integration with existing tools and data
- User acceptance testing
- Documentation and runbooks
- 03Maintain Ongoing
Monitor, iterate, and expand as you grow
AI systems need human oversight. I stay on as a fractional partner - monitoring quality, iterating on the model, and expanding capability as new opportunities emerge.
- Weekly quality monitoring
- Model iteration and fine-tuning
- Incident response
- Quarterly expansion planning
Work
Selected case studies
Multi-Agent FDA Document Review
Designed and deployed a multi-agent AI system for FDA regulatory document review. 6 specialized agents process 100+ page documents at ~18 seconds/page with 15-40% duplicate removal. Multi-million USD savings projected.
- 60-70% reduction in manual review time
- ~18 seconds per page processing
- Multi-million USD savings (client-validated)
Enterprise Data Governance Transformation
Led technical delivery of a €400K data governance transformation for a specialty pharmaceutical company across 13 countries - coordinating 25+ stakeholders, mapping 7 data domains, and delivering a framework for regulatory compliance.
When to Halt a Migration
Led assessment of a 400,000+ document clinical trial migration. Through rigorous data profiling, reduced scope by 92% - then recommended halting when validation revealed critical data quality issues.
Product-Led Growth Engine
Joined as employee #5 at a pre-revenue SaaS startup and built the complete commercial infrastructure - PLG strategy, 8-system tech stack, customer success, and enterprise readiness. Scaled 0 → 1,000+ users with 100% retention.
GSC → BigQuery Pipeline
Built an automated data pipeline ingesting Google Search Console data into BigQuery for a 60-customer SEO agency. 53M+ rows, 70,000+ daily ingestion, solving GSC's 16-month data retention limit.
Let's work together
Ready to ship something real?
I take on a small number of engagements at a time so I can stay deeply involved. If the timing works, let's talk.