AI Automation
Use AI where it genuinely helps — drafting replies, classifying enquiries, summarising documents and cutting repetitive decisions.
The problem
Teams spend hours on repetitive reading, writing and sorting: triaging enquiries, drafting the same replies, summarising documents, categorising records. It's slow and inconsistent.
Who it suits
- →Service businesses
- →Sales & support teams
- →Founders drowning in admin
- →Anyone with high message/document volume
Example workflow
- 1A new enquiry or document arrives
- 2AI classifies it (topic, intent, priority) with your rules
- 3AI drafts a suggested reply or summary
- 4A human reviews and approves before anything is sent
- 5The result is logged for tracking and follow-up
What gets automated
- →Enquiry classification
- →First-draft replies
- →Document & meeting summaries
- →Data extraction from messy text
- →Routine categorisation
Our approach
We start with one high-volume, low-risk task, keep a human in the loop, and only expand once it's reliable. AI runs behind a provider-agnostic layer so we use the cheapest capable model per task.
Honest limitations
AI assists — it does not replace judgement. We keep approval steps for anything customer-facing or financial, and we never let AI present an unverified guess as a fact.
What you can expect
Less time on repetitive reading and typing, more consistent responses, and a clear log of what happened.
We describe outcomes qualitatively and don't invent numbers — real results depend on your process and data.
FAQ
Which AI models do you use?
Whatever fits the task and budget — the system isn't locked to one provider. Simple jobs use cheaper models; harder ones use more capable models.
Is my data used to train models?
We configure providers to avoid training on your data where the API supports it, and keep keys server-side.
Interested in ai automation?
Tell us your situation and we'll suggest a practical next step.