Applied AI · Automation Case Study
How I built an AI-assisted pipeline that takes a customer from request to finished deliverable on its own, turning an hour of manual work per order into minutes.
Running a client deliverable end to end was a chain of manual steps: take the request, gather the data, generate the visual, write up the findings, and send it. Each one ate time and didn't scale past a handful a day while I was also doing the actual customer work.
I wanted the whole path, from a customer filling out a form to a finished report landing in their inbox, to run without me touching each step.
An end-to-end automated pipeline. A customer submits a short form; the system gathers the data, generates a visual report, assembles the writeup, and emails the finished deliverable, all without a manual handoff between stages.
The same pattern maps straight onto customer success and operations work. Health snapshots, business-review prep, onboarding nudges, and at-risk flags can all be generated from data automatically, so the human time goes to the conversation instead of the busywork. That's the kind of AI-in-the-loop workflow I build and like to own.