We start by finding the task
Before any model is chosen, we sit with your team and find where the hours actually go. It is usually somewhere unremarkable: reformatting supplier quotes, triaging inbound email, summarising call notes into the CRM, checking documents against a checklist.
The best candidates share three traits: done often, judgement-light, and currently done by someone expensive.
What we build
Drafting tools that produce your first version in your own format. Triage that routes and tags before a human looks. Extraction that pulls structured data out of invoices, contracts or forms. Summarisation that writes into the system your team already uses, not a separate window.
The interface is usually a small web tool or an addition to software you already open, not another login.
Keeping a human in the loop
For anything that leaves the building or touches money, the tool proposes and a person approves. That single design decision is the difference between automation that gets adopted and automation that gets switched off after one bad output.
Measuring whether it worked
We agree the number before we build: minutes saved per task, share of items needing correction, volume handled without escalation. If the tool does not move it after a month of real use, that is a finding, and we would rather report it than let the thing quietly rot.
Where this connects
If the task is answering questions from your documentation, AI chatbots and RAG assistants is the more specific service. Tools that touch business records usually sit alongside custom software.