AI where it removes work, not where it adds risk
Most AI projects fail on the boring parts: the data isn’t clean, nobody owns the output, and the workflow around it never changed. We start from the workflow and work backwards.
What this actually looks like day to day
Somebody in your business is re-keying the same information into three systems. Somebody else is reconciling numbers by hand every month-end.
Meanwhile the AI conversation is happening at a level of abstraction that never touches either task. The useful question isn’t what AI can do — it’s which of your recurring hours can be given back, and what it costs to do that reliably.
Signs this is you
- The same data gets typed into more than one system
- Month-end reconciliation is a manual, dreaded ritual
- “AI strategy” conversations never turn into anything running in production
- Nobody would notice for weeks if an automated process quietly broke
AI & Automation, end to end
Automation audit
Where the repeat hours actually go, and what's worth automating first.
Document & invoice processing
Extraction, validation, and routing into your existing systems.
Forecasting & planning
Demand, purchasing, rostering, against your own history.
LLM-based workflows
Drafting, summarising, classification, and internal assistants over your own data, with the guardrails and review steps that keep them safe to deploy.
Integration
Into what you already run, rather than another tool nobody opens.
Evaluation & monitoring
So you find out when quality drifts before your customers do.
Three ways to work with us
Advisory
We assess what you run today, architect what should replace it, and hand you a roadmap with sequencing and costs. You take it from there, or we build it.
Build
We deliver the work: design, development, integration, migration and rollout, against a scope and price agreed up front.
Run
We stay on to operate and support what we built, with stated response times and a regular review of what to fix or add next.
Deliverables, not just a plan
- Automation audit with ranked opportunities and effort estimates
- Working automations in production, not a pilot
- Documentation and handover
- Monitoring so you know when something breaks
Is this the right fit?
Businesses with a recurring, rules-heavy workload and enough volume to make automating it worth the effort. If you’re looking for an AI strategy deck, we’re not the right firm.
Start with an honest look at what you run
Tell us what you're running today and where it hurts. We'll come back with the two or three changes worth making first — and if the answer is that your setup is fine, we'll say that instead.