Service
AI in the workflow
Finding the repetitive work inside a company and replacing it with AI that people trust and use, one workflow at a time.
Where AI actually helps
Not in the meetings about AI. In the four tasks nobody wants to do on a Friday afternoon: sorting incoming mail, drafting the same offer for the twentieth time, pulling numbers from PDFs into a table, answering the questions the handbook already answers. That is where an hour a day hides.
How it goes
- Workflow audit. A week of looking at what people really do, with a stopwatch where it helps. The result is a short list of tasks, ranked by time saved and by how much trust each one needs.
- One workflow first. We pick the one with the best ratio and build it end to end, with the people who own it. Real data, real edge cases, a human in the loop until it earns its way out.
- Measure, then widen. If the first one saves time, the second is easier to argue for. If it does not, we learned that cheaply.
Project or retainer
A single workflow is a project of four to eight weeks. Companies that want to keep going usually switch to a retainer: a fixed number of days a month to build the next one, tune the last one and keep the models and prompts from drifting.
What I will not do
Bolt a chat window onto a product and call it a strategy. Promise numbers before the audit. Send your data to a service your lawyers have not seen.
Have a workflow that eats time, a product that needs building,
or a team that should learn the tools?