AI Startup Specialist

Fractional CTO for AI Startups

Senior technical leadership for AI companies navigating model selection, infrastructure scaling, and the build vs buy decisions that define your product. I bring a business-first perspective to AI infrastructure, helping founders make technical choices that serve revenue, not just research.

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Why AI Startups Need a Specialist CTO

AI products have unique technical challenges that generalist CTOs rarely encounter. The decisions you make about model architecture, data pipelines, and infrastructure in the first year will define your cost structure, product quality, and ability to scale.

Model Architecture Decisions

Choosing between foundation models, fine-tuning, and training from scratch has massive implications for cost, performance, and differentiation. These decisions need someone who understands both the technical trade-offs and the business context.

MLOps and Infrastructure

Production ML systems are fundamentally different from research notebooks. You need robust pipelines for data ingestion, model training, evaluation, deployment, and monitoring. Getting this wrong early creates technical debt that is expensive to unwind.

Data Strategy

Your data is your moat. How you collect, store, process, and govern data determines the quality of your models and your competitive position. A clear data strategy is essential from day one.

Build vs Buy AI

Not every component needs to be built in-house. Knowing when to use off-the-shelf APIs, when to fine-tune, and when to invest in proprietary models is a strategic decision that affects your burn rate and time to market. My build vs buy framework applies directly here.

Responsible AI and Compliance

The EU AI Act and evolving UK regulations mean AI companies must build with governance in mind. Bias testing, explainability, data provenance, and audit trails are not optional. As with any regulated startup, these need to be architected in from the start.

Scaling from Prototype to Production

The gap between a working demo and a production system serving real users is where most AI startups struggle. Inference latency, cost optimisation, reliability, and graceful degradation all require careful engineering.

Relevant Experience

Risika

CTO at Risika

ML-powered credit risk and business intelligence platform

  • ✓ Built and scaled data infrastructure powering ML-driven credit risk assessments
  • ✓ Led transformation from VC-funded to profitable in 18 months through business-first engineering
  • ✓ Managed data pipelines processing large-scale financial and corporate datasets
  • ✓ Scaled distributed engineering team across Denmark and India

I understand the practical reality of building data-intensive products. From designing pipelines that feed ML models to making the infrastructure decisions that keep costs sustainable as you scale, I have done this work hands-on.

How I Help AI Startups

AI Infrastructure Strategy

Designing the technical architecture that supports your AI product at scale. Model serving, data pipelines, feature stores, monitoring, and the cloud infrastructure to run it all without burning through your runway.

Team Building

Hiring the right mix of ML engineers, data engineers, and full-stack developers. Defining roles, setting technical standards, and building a team structure that lets your AI product evolve without bottlenecks.

Vendor and Model Evaluation

Objective assessment of model providers, cloud platforms, and AI tooling. Cutting through vendor marketing to find the solutions that actually fit your use case, budget, and scaling requirements.

Technical Due Diligence

Preparing your AI startup for investor scrutiny. Technical due diligence for AI companies means articulating your technical differentiation, demonstrating responsible AI practices, and presenting a credible scaling roadmap to investors who understand the space.

Scaling from Demo to Production

Bridging the gap between your proof of concept and a reliable production system. Inference optimisation, cost management, reliability engineering, and the operational maturity needed to serve real users.

Frequently Asked Questions

What does a fractional CTO do for an AI startup?
A fractional CTO provides senior technical leadership on a part-time basis. For AI startups specifically, this means guiding decisions on model architecture, data infrastructure, build vs buy trade-offs, MLOps, and scaling from prototype to production. You get experienced leadership without the full-time cost.
When should an AI startup hire a fractional CTO?
The best time is before you make expensive infrastructure decisions that are hard to reverse. If you are choosing between model providers, designing your data pipeline, or preparing for a funding round that requires technical due diligence, a fractional CTO helps you avoid costly mistakes early.
How is a fractional CTO different from an AI consultant?
A consultant typically delivers a report and leaves. A fractional CTO embeds with your team, takes ownership of technical strategy, and stays involved through execution. I attend standups, review architecture decisions, help hire engineers, and ensure the technical roadmap aligns with your business goals.
Do I need a fractional CTO if I already have ML engineers?
Strong ML engineers are essential, but they are not always equipped to make business-level technical decisions. A fractional CTO bridges the gap between your engineering team and the commercial reality of your product, covering areas like vendor negotiations, technical due diligence for investors, and long-term architecture planning.
What does a fractional CTO engagement look like in practice?
Typical engagements range from one to three days per week. I work directly with your engineering team and founders, attending key meetings, reviewing technical decisions, and driving strategic initiatives. Many AI startups start with an intensive assessment period before moving to ongoing advisory.

Building an AI Product?

Book a free discovery call to discuss your technical challenges and see if we are a good fit. Or try a free day of Fractional CPTO support.

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