About Neil Austin
CFO judgement with hands-on AI delivery
I help UK mid-market businesses move from AI interest to working automation. My difference is simple: I have led finance teams, owned board reporting, worked through ERP reality, and then learned to build the systems myself.
That means I do not treat AI as a novelty. I look for the places where better data flow, fewer manual steps, stronger controls, and faster decisions can make a measurable difference to how the business runs.
Neil Austin
AI and automation consultant for UK mid-market businesses
Built for real operations
Why the CFO background matters
The hard part of automation is rarely the code on its own. It is knowing which process is worth changing, what controls cannot be broken, who needs to trust the output, and where the return actually comes from.
Commercial operator
I have sat inside the business, owned the numbers, supported board decisions, and dealt with the reality of systems that have to work during a busy trading week.
Hands-on builder
I write the code, connect the APIs, shape the data model, and test the workflow myself. You are not buying a strategy layer with delivery passed elsewhere.
Finance-grade control
Automation only helps if people can trust it. Reconciliations, exceptions, audit trails, and handover are part of the build from the start.
Experience
From finance leadership to practical AI delivery
Now
AI and Automation Consultant
Helping mid-market businesses turn AI from a boardroom topic into working systems across finance, operations, reporting, and decision support.
15+ years
CFO / Finance Director
Finance leadership across hospitality, retail, and multi-site operations, including board reporting, forecasting, ERP delivery, management information, and team leadership.
The bridge
Finance Leader Who Codes
Started automating the painful finance processes I was responsible for. That became the practical bridge between commercial judgement and technical delivery.
How I Work
Practical automation, built around the business
I prefer useful, boring reliability over AI theatre. A good project gives people back time, removes avoidable errors, improves visibility, or creates a decision process the business can repeat.
Start with the commercial problem, not the AI demo.
Build around the systems and people already running the business.
Keep finance ownership, controls, and review points visible.
Ship usable systems in weeks, then improve from real feedback.
Toolkit
Technologies I work with
AI & ML
- Claude / Anthropic API
- OpenAI
- Natural Language Processing
- Prompt Engineering
Languages & Frameworks
- Python
- TypeScript
- React
- Next.js
- Flask
- FastAPI
Enterprise Systems
- SAP Business One
- SAP HANA
- SSAS Tabular
- Power BI
Cloud & Integration
- Microsoft 365 / Graph API
- Azure AD
- SharePoint
- REST APIs
Data & Databases
- SQL Server
- HANA
- PostgreSQL
- Data Warehousing
- ETL Pipelines
Built for mid-market reality
Mid-market businesses often have the complexity of larger organisations without the spare capacity, specialist teams, or unlimited project budgets. That is exactly where practical AI and automation can help, provided it is grounded in the way the operation actually works.
My role is to bring enough commercial judgement to choose the right problem, enough technical depth to build the solution, and enough finance discipline to make sure the result can be trusted.