A Long-Term, Pragmatic Technology Partner

Calm, structured progress through complex product, platform, and AI decisions.

B2B SaaS companies often face important technology decisions before the path is fully clear. A product may need modernising, a new opportunity may need validating, customers may be asking for more, or AI may be creating pressure to act.

The challenge is knowing what to do next, what to delay, what to test, and what risks need managing before serious time and budget are committed.

I work with a small number of medium sized B2B SaaS companies on an ongoing basis, focusing on three areas:

Product & Technology Strategy

I work with the team to shape product and technology direction, clarifying the options and where to focus.

Understanding the product, market, customers, and operational practices
Identifying opportunities to improve, modernise, or extend the platform
Exploring where AI genuinely creates value within the business
Filtering out noise and avoiding unnecessary complexity
Prioritising initiatives based on value, feasibility, risk, and timing

Risk & Governance

I help make risk visible and manageable, using proportionate governance that supports confident decisions without slowing delivery down.

Practical risk registers, decision logs, and option matrices
Clear ownership and accountability for important technology decisions
AI governance where relevant, including policies, documentation, and responsible adoption
Assessment of organisational readiness, delivery risk, and operational impact
Ongoing review of assumptions, risks, and outcomes

Applied Research & Prototyping

I use focused research, experiments, and prototypes to reduce uncertainty before full-scale implementation.

Proactively identifying meaningful product, platform, and AI opportunities
Designing and validating selected initiatives before formal roadmap commitment
Building proof-of-concepts and early prototypes to test feasibility before committing to full implementation
Exploring legacy systems, workflows, data, and technical constraints
Producing structured findings to guide decisions and next steps

About me

With a background in software development and business, I take a practical, applied approach to product, technology, and AI strategy.

I've spent years building and supporting real software systems, so I approach strategy with implementation in mind. I'm interested in what can actually be built, adopted, maintained, and improved, not just what sounds good in theory.

Since 2021, I've focused deeply on machine learning and AI, combining practical experimentation with a solid understanding of the underlying concepts and limitations.

I like to feel part of the team, immersing myself in the product, market, users, business problem, challenges, and roadmap.

How it works

The partnership is structured as a monthly retainer, where I provide ongoing leadership without the cost and commitment of a full-time hire.

I work remotely but stay in regular contact via email, messaging and video calls, with the occasional on-site visit, where appropriate.

I intentionally keep the number of partners I work with low to ensure I have the capacity to provide focused attention and seamless integration into the client's team.

My approach is supported by practical documentation, decision tools, and structured research methods, helping teams move from discovery and assessment through to recommendations and implementation. Where AI is involved, I align with established frameworks such as the NIST AI RMF and Microsoft Responsible AI principles.

Discover

The discover phase is the foundation for everything that follows. A deep contextual understanding of the market, product, and operations is essential for making informed decisions.

I spend time onboarding through documentation review, hands-on use of the product, codebase or system exploration where relevant, and conversations with key stakeholders.

I use AI tools to accelerate this discovery work, helping me build context faster and surface useful questions earlier.

arrow_downward

The operating loop for continuous improvement

analytics

Assess

Evaluate opportunities, risks, constraints, and expected impact
Separate real value from noise and focus on what matters

arrow_downward arrow_forward

sort

Prioritise

Prioritise options by value, urgency, risk, effort, and readiness
Build a phased roadmap aligned with commercial and technical reality

arrow_downward

build

Implement

Support selected initiatives through design, prototyping, technical planning, or implementation
Integrate new capabilities into existing products, systems, and workflows

arrow_downward arrow_back

monitoring

Monitor

Track system performance and behaviour over time
Iterate and refine based on monitoring and real-world feedback

rotate_left arrow_upward

Implementation support

Where appropriate, I can support implementation under separately scoped projects.

Operational support for production systems remains with the client's internal team. My involvement is focused on strategic guidance, design, and implementation during working hours.

Who this is for

This partnership works best for small to medium sized B2B SaaS companies who:

Have an established product and team
Are facing important product or technology decisions
Want to modernise, explore, or build without overcommitting too early
Need senior judgement, but not necessarily a full-time technology leader
Value practical research, clear communication, and evidence-led decisions
Want to use AI where it genuinely adds value, without being distracted by hype

Rather than committing to a full-time hire or a large consultancy engagement, they value access to a long-term strategic partner who can understand the business deeply while bringing outside perspective from seeing how AI adoption, product decisions, and technology change play out across different organisations.

Pricing

Partnerships typically begin from £2,500 ex VAT per month, depending on scope and level of involvement.

This usually includes around three focused working days per month, regular communication, and retained context between sessions, so the partnership builds momentum over time rather than starting from scratch each month.

Higher-involvement retainers can be agreed where more hands-on research, prototyping, governance, or implementation support is required.

Getting started

Exploring whether this is a fit starts with a short, no-obligation conversation.