Frequently Asked Questions

Your business is ready for AI if you have repetitive processes, collect data regularly, or face challenges that need pattern recognition or prediction. You don’t need perfect data or technical expertise to start - we begin by understanding your business challenges, not your technical readiness. If you’re asking the question, it’s worth a conversation to explore the possibilities.

Our typical AI discovery sprint takes 2-4 weeks. In this time, we map your processes, analyse your data assets, identify opportunities with genuine ROI, and create a prioritised roadmap. We focus on being thorough enough to give you confidence, but quick enough to maintain momentum.

No, you don’t need any technical expertise to begin AI strategy work. Our role is to bridge the gap between business and technology. We speak your language first, understand your challenges, then translate technical possibilities into business opportunities you can evaluate.

You’ll receive a practical AI roadmap with prioritised use cases, detailed ROI calculations for each opportunity, a clear go/no-go decision framework, implementation timelines, and investment requirements. Everything is presented in business terms, not technical jargon.

Our AI strategy and discovery projects typically range from £5,000 to £15,000 depending on scope and company size. We always provide fixed or capped costs upfront - no surprise invoices. The investment often pays for itself by identifying either valuable opportunities or preventing costly mistakes.

Absolutely. Part of being “Justified” means being honest when AI isn’t the answer. If simpler solutions would work better, if the ROI doesn’t stack up, or if you need to sort data foundations first, we’ll tell you. We’d rather give honest advice than force an unnecessary solution.

Our strategy work typically identifies opportunities worth 10-50x the consulting investment. For example, we’ve identified £695K in annual savings for a security systems company and 2-4% profit improvements for retail clients. Even when we recommend not proceeding with AI, we save clients from costly failed projects.

A Proof of Concept (POC) proves whether something can work technically and delivers expected value - it’s about validation, not polish. An MVP (Minimum Viable Product) is the first production-ready version users can actually use. We recommend POC first to validate assumptions with real data before committing to full development.

Most proof of concepts take 4-8 weeks to develop. This includes defining success criteria, building a working prototype with your real data, testing assumptions, measuring results, and providing a clear path to full implementation. We keep them focused to get you answers quickly.

A “failed” POC is actually a success if it saves you from a costly mistake. If the POC shows the approach won’t deliver expected value, we’ll help identify why and explore alternatives. Sometimes we discover the solution needs tweaking; sometimes we find a simpler approach would work better. Either way, you’ve spent thousands learning, not millions failing.

You own all intellectual property created during the POC. We provide full code, documentation, and findings. Our value isn’t in keeping secrets - it’s in helping you succeed. You’re free to implement internally, work with us, or take it elsewhere.

A fractional Head of AI provides strategic AI leadership without the full-time cost. I develop AI strategy aligned with business goals, bridge technical teams and senior leadership, guide AI investment decisions, mentor your team, oversee AI initiatives, and ensure projects deliver real value. Think of it as having an experienced AI leader on your leadership team, just not every day.

Most clients engage fractional AI leadership for 2-5 days per month. Two days might cover strategic oversight and key meetings. Five days allows for hands-on involvement in projects and team mentoring. We can flex up during critical periods and scale down once foundations are solid.

Absolutely - this is one of the key benefits. I’m equally comfortable explaining strategy to your board and debugging code with developers. I help your team level up their AI capabilities, provide technical guidance, and ensure everyone’s pulling in the same direction. Your team gains a mentor, not a replacement.

Interim is typically full-time for a fixed period (3-6 months) to fill a gap. Fractional is part-time (2-5 days/month) for longer-term partnership. Fractional works well when you need ongoing AI leadership but don’t have full-time workload or budget. It’s about having the right expertise when you need it.

A full-time Head of AI costs £120,000-£180,000 plus benefits. Fractional typically costs £2,000-£5,000 per month (2-5 days), giving you senior expertise for roughly 20-30% of full-time cost. You get enterprise-level AI leadership that grows with your needs.

I work flexibly based on your needs. Most fractional engagements are primarily remote with regular on-site days for important meetings, workshops, or team sessions. I’m based in Norwich but work with companies across the UK. The key is being present (virtually or physically) when it matters most.

I become part of your leadership team, attending key meetings and contributing to strategic decisions beyond just AI. I understand that every organisation has its culture and politics. My role is to complement existing leadership, not disrupt it. I focus on collaboration and knowledge transfer, ensuring the organisation builds lasting AI capability.

Yes - knowledge transfer is built into every implementation. We document everything, use technologies your team can support, provide training at multiple levels, and ensure gradual handover rather than abrupt departure. If you don’t have technical team yet, we’ll help you understand what capabilities you need to hire.

Integration is a core part of what we do. We work with legacy systems, modern APIs, and everything in between. We design solutions that fit your current architecture rather than requiring wholesale changes. We’ve integrated with everything from 20-year-old databases to cutting-edge cloud platforms.

We build solutions to be maintainable and evolvable. Post-deployment, you can engage us for specific changes, transition to fractional support for ongoing evolution, or handle changes internally with the documentation and training we provide. We’re always available for questions even after formal engagement ends.

We offer flexible post-implementation support from ad-hoc assistance to regular fractional engagement. Many clients transition from implementation to fractional support (2-5 days/month) for ongoing optimisation and evolution. We ensure you’re never stuck with a system you can’t maintain.

We’re technology-agnostic and choose the best tools for your specific needs. We commonly use Python with frameworks like PyTorch and TensorFlow, cloud platforms (AWS, Google Cloud, Azure), modern MLOps tools, and various databases. We prioritise proven, maintainable technologies over bleeding-edge experiments.

Production readiness means robust error handling, comprehensive testing, monitoring and alerting, proper security and governance, scalability planning, and clear documentation. We’ve deployed systems handling millions of requests daily. We know the difference between a demo and production AI.

We combine rare end-to-end capability from strategy through implementation, deep technical expertise with clear business communication, and practical, ROI-focused solutions rather than theoretical frameworks. We’re a partner who speaks both boardroom and code fluently. Plus, we’ll honestly tell you when AI isn’t the answer.

We specialise in bringing enterprise-level AI expertise to ambitious SMEs and startups. While I’ve worked with global corporations, my sweet spot is companies that need senior AI expertise but can’t justify a full-time hire. We make advanced AI accessible to growing businesses.

We’re based in Norwich but work with companies across the UK. Most engagements are hybrid - primarily remote with on-site presence for key sessions. Geography isn’t a barrier to partnership. We’ve successfully delivered projects entirely remotely and with regular on-site presence, depending on client needs.

Not having a data science team isn’t a barrier. We can handle everything technically while training your existing team, help you understand what capabilities to hire, or provide ongoing fractional support. Many clients start with no technical team and build capability over time with our guidance.

We calculate AI ROI using tangible metrics: time saved multiplied by hourly costs, revenue increase from improved conversion or retention, cost reduction from automation or efficiency, and risk reduction from better predictions or detection. Every recommendation includes a detailed business case with conservative and optimistic projections.

We’ve implemented AI across retail, financial services, healthcare, manufacturing, education technology, climate tech, cybersecurity, and market research. Each industry brings unique challenges, but the principles of good AI implementation cross sectors. We bring cross-industry insights to your specific challenges.

Yes, we regularly help companies build AI capability including defining roles and required skills, reviewing CVs and interviewing candidates, creating technical assessments, mentoring new hires, and establishing best practices. We help you build a team that can thrive independently.

Yes, we offer a free one-hour discovery session. We’ll understand your challenges, identify potential AI opportunities, provide honest assessment of feasibility, and outline possible next steps. There’s no obligation and no sales pressure - sometimes the best advice is to focus elsewhere first.

Start with a free discovery session where we understand your challenges and explore possibilities. From there, we typically recommend either a discovery sprint to identify opportunities, a POC to prove a specific concept, or fractional engagement for ongoing support. Every journey starts with understanding your specific needs.

Definitely not. While we work with large language models when appropriate, we bring 15 years of machine learning experience across computer vision, time series prediction, optimisation, and traditional ML. We choose the right tool for each problem, not just the trending one. Sometimes the best solution is a simple decision tree, not a transformer model.