The problem.
AI is everywhere in marketing material, but almost nowhere in actual business operations. Most businesses know it could help, but don't know where to start, what's genuinely useful versus hype, or how to avoid wasting money on tools that don't integrate with how they work.
The gap isn't the technology. The technology exists and it works. The gap is implementation: knowing which processes to automate, how to design systems your team will actually use, and how to integrate AI into existing workflows without creating more problems than it solves.
AMRIX builds practical AI systems, not theoretical demos. If it doesn't solve a real problem in your business, we don't build it.
What's included.
- Operational workflow analysis: mapping your current processes to identify automation opportunities
- Claude and ChatGPT integrated into the tools you already use: email, documents, quoting, CRM and reporting
- Business process optimisation first: the workflow gets fixed before it gets automated, because automating a bad process just makes it fail faster
- Model and platform selection assessed against your use case rather than against whatever is fashionable
- Prompts and instructions kept in version control, not pasted into a chat window and lost
- Guardrails and human review points, so nothing is sent, quoted or committed without a person approving it
- Custom internal tooling development: purpose-built tools for your specific workflows
- Operator system design and implementation: AI-enhanced decision-support and process management
- Document processing and data extraction automation: invoices, contracts, reports, forms
- Integration with existing business systems: accounting software, CRMs, M365, databases
- Workflow automation using no-code and custom-code approaches depending on requirements
- Staff onboarding and adoption support: practical training for real world use
- Ongoing iteration and system refinement based on actual usage
Which model, and where it runs.
We build primarily on Claude and ChatGPT. Between them they cover nearly every practical business case, and both are stable enough to put a real process on top of. Which one a given workflow uses is a technical decision made against the job, not a loyalty.
Claude tends to hold up better on long documents, careful reasoning, and following a detailed set of rules without drifting. ChatGPT tends to win on breadth of integrations and on steps where speed matters more than depth. Plenty of builds use both, at different points in the same workflow.
Where material genuinely cannot leave your network, we will say so at the quoting stage and build that step on a locally hosted model, or leave it as a manual step, rather than quietly sending it somewhere it should not go.
Who it's for.
Businesses with repetitive, high-volume processes that currently rely on manual effort: data entry, document review, email triage, report generation, approval workflows. Businesses where a team member is spending hours on tasks that could be handled automatically. Businesses that have seen AI demos and want to understand what's actually applicable to their situation.
This is not about replacing your team. It's about removing the friction and repetition so your team can focus on the work that requires human judgment.
How we deliver.
We start with your operations, not the technology. We spend time understanding how your business actually works, where the time goes, what gets done manually, what falls through the cracks, and identify where AI creates measurable value: time saved, errors reduced, decisions improved, bottlenecks removed.
We build incrementally. A working system that solves one problem well is more valuable than a complex platform that's never fully adopted. Once one system is running, we extend and iterate.
No proof-of-concept graveyards. No tools purchased and abandoned. If it doesn't create real, measurable value for your business, we won't recommend building it.