We map what your team actually does each week, pick what is worth automating, and build it on the tools you already use.
When a company says it wants to “add AI”, what usually sits behind that is a process held together by copying and pasting between four tools that don’t talk to each other. A model does not fix that on its own. What fixes it is describing the process precisely, deciding which part a machine can do, and connecting the pieces.
That description almost never exists in writing. It lives in the head of the person who has been doing it for five years, and it changes case by case. A good share of the work is getting it out of there before automating anything.
In most of the companies we work with the first candidates repeat themselves: inbound lead intake and qualification, preparing quotes and proposals, summarising and following up meetings, the recurring reports someone assembles by hand every Monday, and the first reply to emails or messages that always follow the same script.
None of these replaces anyone. What they do is take away the part of the job that needs no judgement, which is exactly the part that wears out the people who have it.
Hours freed per month and what they go into, end-to-end process time, share of cases completed without intervention, and errors the flow catches that used to slip through.
We measure the “before” with the initial map, because three months later nobody remembers how long it used to take. That baseline is half the value of the project.
We come from measurable marketing, not from process consulting. That shows in two ways: we start with what can be counted, and we distrust long projects that show nothing until the end. We would rather put a flow into production in weeks and argue over real data.
And we run it on ourselves first. The agency operates on its own agents for analysis, production and maintenance; when we tell you where one of these projects gets stuck, it is because it got stuck on us first.