Data · Analytics · AI Consultant
Most organisations have data. Very few have data that works.
Broken dashboards. Untrusted data. AI projects that never reach production. I fix the foundations, build what is missing, and deliver systems that actually work — from strategy through to production.
No pitch. No obligation. Just an honest assessment of where you are.
For organisations asking
“Why don't we trust our numbers?”
Your dashboards contradict each other. Your team spends more time cleaning data than analysing it. The issue is not your BI tool — it is what sits underneath it. Until the foundations are fixed, every report is a guess wearing a chart.
“Can AI actually help us — or is it just noise?”
It can. But not if your data is unreliable, your use case is vague, or the solution is built to demo well rather than run in production. I start with the boring work — fixing your data — because that is what makes the exciting work actually land.
“We have data everywhere but nobody can tell me what is driving performance.”
You do not need more dashboards. You need a measurement strategy that connects activity to outcomes and a reporting system your team trusts enough to act on. That is a design problem, not a technology problem.
Services
Consulting built around outcomes. Not tool names.
Every engagement starts with a business problem. The approach is always the same: understand the problem, design the right solution, build it to production standard, and measure whether it worked.
Data & AI Audits
I run structured assessments that map your current data maturity, analytics coverage, reporting reliability and AI readiness — then prioritise the highest-value problems to fix first.
You walk away with: A written report with scored findings, root causes, and a prioritised action plan.
Marketing Analytics & Measurement
I build measurement frameworks, attribution models, and analytics systems that connect marketing activity to business outcomes — so your team stops guessing and starts making decisions based on evidence.
You walk away with: A dashboard your leadership team opens every Monday that shows exactly which channels are making money and which are burning it. Attribution models that hold up when finance asks the hard questions.
Data Engineering & Platforms
I design and build the warehouses, pipelines, cloud platforms and integrations that give your organisation a single, trusted source of truth — the foundation everything else depends on.
You walk away with: Automated pipelines, a properly modelled warehouse, and clean data flowing into your reporting layer — documented and handed over.
Data Science & Machine Learning
I build models that forecast demand, predict churn, score leads, detect anomalies, recommend products and surface patterns humans miss — engineered for production use, not just notebooks.
You walk away with: A deployed, validated model with documentation — built to run in your business, not sit in a research environment.
AI Applications
I build practical AI tools — LLM-powered assistants, intelligent interview systems, document automation, and workflow tools — designed for real teams in real organisations.
You walk away with: A working AI application your team uses daily — with measurable impact on the process it was built to improve.
Data & AI Advisory
Growing businesses and early-stage data teams often need senior guidance without the cost of a full-time hire. I help set direction, make architecture decisions, evaluate vendors, and build a technical roadmap.
You walk away with: A data strategy, technical roadmap, clear architecture decisions, and a path from where you are to where you need to be.
Engagement Models
Three ways to work together.
Audit
2–4 weeksA structured assessment of your data, analytics, or AI readiness. Written report with findings and prioritised action plan. Full value as a standalone deliverable.
Best for: Organisations that want clarity before committing budget.
Project Build
6–14 weeksA scoped engagement to design and build a specific system. Fixed scope, clear deliverables, production-ready output with documentation and handover.
Best for: Organisations that know what they need built.
Advisory
OngoingRegular data and AI guidance. Architecture decisions, strategy direction, vendor evaluation, technical roadmap. Flexible commitment.
Best for: Growing businesses that need expertise without a full-time hire.
How I Work
Audit first. Build second. Measure always.
Every engagement follows the same discipline — because skipping steps is the single most expensive mistake in data and AI delivery.
Diagnose
Understand the business problem, current systems, data quality and opportunity before recommending anything.
Most failed data projects start with someone building before they understood what was broken. This step prevents that.
Design
Create the architecture, data flows, specifications, model approach or AI blueprint.
You see and approve the plan before a single line of code is written. This eliminates the most common cause of build failures.
Build
Engineer the pipelines, dashboards, models, APIs or AI systems to production-ready standards.
Not prototypes. Not proof-of-concepts. Systems that operate in your business from day one.
Measure
Track whether the solution improves decisions, saves time, or creates measurable value.
If it does not move a number that matters, it was not worth building.
Who I Help
I work with leaders who know data matters but need help making it work.
Heads of Data & Analytics
Inherited messy pipelines, unreliable dashboards, or no data strategy. Need a partner who can fix what is broken and deliver results.
CTOs & Technical Leaders
Need AI or ML capabilities but don't have the in-house team. Need someone who goes from business case to production model.
Founders & Managing Directors
Know data matters but not sure where to start or who to trust. Need honest guidance, not a sales pitch.
Marketing & Commercial Leaders
Can't prove what's working because measurement is broken. Need analytics that connects spend to revenue.
Selected Work
Built across analytics, ML, APIs and AI.
All projects shown anonymously. The focus is always on the problem, the system built, and the outcome.
Data Engineering · Cloud · BI · Automation
Automated Executive Reporting Platform
Built an automated data platform extracting from multiple systems, transforming through layered architecture, delivering fresh dashboards to stakeholders every morning.
Outcome
Eliminated manual reporting. Improved data trust. Daily automated insight.
Marketing Analytics · Tableau · Attribution
Marketing Intelligence & Attribution
Consolidated scattered advertising data into a central reporting layer with automated ingestion, transformations, and executive dashboards.
Outcome
Single source of truth. Automated cross-channel reporting. Faster decisions.
Generative AI · LLM Applications
AI-Powered Interview & Assessment System
Built an AI interviewer that conducts structured interviews, evaluates responses against job criteria, ranks candidates, and delivers gap analysis reports to HR.
Outcome
Scalable assessment. Consistent evaluation. Structured reports with gap analysis.
Machine Learning · Customer Analytics
Personalised Recommendation System
Designed recommendation models analysing behaviour and interaction patterns to deliver personalised suggestions and improve content discovery.
Outcome
Improved relevance. Better experience. Increased engagement and retention.
ML · Predictive Modelling · Product Analytics
Churn Prediction & Retention Analytics
Built churn and engagement prediction models with behavioural segmentation, delivering retention insights that informed targeting strategy.
Outcome
Early risk identification. Improved targeting. Faster product decisions.
Analytics Engineering · Data Pipelines · BI
Enterprise Data Pipeline & Analytics Foundation
Built analytics engineering frameworks, transformation logic, data pipelines, and quality processes to make reporting trustworthy.
Outcome
Reliable reporting. Consistent metrics. Stronger decision-making.
Insights
Thinking on data, analytics and AI.
Why Your Dashboards Are Lying to You
Most dashboard problems are not BI problems. They are data foundation problems. Here is how to tell the difference.
Read articleWhat I Learned Building an AI Interviewer
A practical walkthrough of building an LLM-powered interview system — what worked, what broke, what I would do differently.
Read articleIs Your Business Ready for AI? A Checklist
A structured assessment any organisation can run before committing budget to an AI initiative.
Read articleThe Measurement Problem Nobody Talks About
Why most marketing analytics setups measure activity, not outcomes — and how to rebuild around decisions.
Read article
About Raphael
Technical depth. Commercial thinking. End-to-end delivery.
I work across the full data and AI lifecycle: strategy, architecture, engineering, analytics, machine learning, generative AI and production deployment.
My background spans retail, e-commerce, financial services, NGOs, media, marketing and cyber security — building and delivering in environments where the data was messy, the requirements were unclear, and the pressure to ship was real.
I believe most data and AI projects fail not because the technology is wrong, but because the foundations were skipped. My approach is to fix the foundations first, build to production standard always, and measure whether the work delivered value — not assume it did.
I diagnose why your reports don't match. I rebuild the pipeline underneath. I design the dashboard on top. I train the model that predicts what happens next. I build the AI tool that acts on it. One person. One engagement. Everything connected.
Available for speaking engagements — conference talks, panels, podcasts, and workshops. Get in touch →
Common Questions
Straight answers to the things you are probably thinking.
“How is working with you different from hiring a freelancer or an agency?”
A freelancer gives you their time. An agency gives you a team you have never met. I give you one person who owns the outcome from diagnosis through to production — the same person who scoped the work is the person who builds it. No handoffs, no junior substitutions, no project manager sitting between you and the person doing the work.
“What does a typical engagement cost?”
Audits start in the low thousands. Project builds range from mid four figures to mid five figures depending on complexity and duration. Advisory is a monthly commitment scaled to your needs. Book a call and I will give you a realistic number for your situation within the first ten minutes.
“Do you work with businesses outside the UK?”
Yes. I work with organisations across the UK, Nigeria, Africa, and internationally. Most of my work is delivered remotely. If your business has a data or AI problem, geography is not a barrier.
“Can you really cover data engineering, analytics, ML, and AI?”
It is broad. That is the point. Most data problems do not sit neatly inside one discipline. A broken dashboard is often a data engineering problem. An AI initiative that stalls usually has a data quality root cause. I work across the full stack because that is what the work actually demands — and because having one person who understands the whole picture means fewer handoffs and faster delivery.
“What if I don't know what I need yet?”
That is exactly what the audit is for. I assess where you are, identify what is broken or missing, and produce a prioritised recommendation. You then decide what to act on. No pressure, no obligation to continue.
Start Here
Book a discovery call.
Thirty minutes. You tell me what is happening. I tell you what I would do about it. If there is a fit, we scope it. If not, you leave with a clearer picture than you walked in with.
No pitch. No obligation. No slide decks.
I will tell you honestly if I can help — and if I cannot, I will point you to someone who can.