A US marketing agency: a 13-agent AI roadmap, and client reports that build themselves

The problem

The agency was growing, and its operations were held together by people. Client reports were built by hand every month. Updates came through several notification channels that nobody had a shared picture of. And because there was no shared definition of "done", the next person in the chain often redid work to be safe: about 15 hours of duplicate checking every month that never showed up on a P&L.

What we found

We spent time with the team, mapped every workflow and costed each step. Two things stood out.

First, the monthly client report wasn't just admin. It was the moment each client decided whether they were getting value. A report full of screenshots and jargon was quietly working against retention.

Second, solving one bottleneck with AI just moves the bottleneck downstream. So instead of one tool, the agency needed a plan for the whole chain.

What we built

We sized 13 AI agents across the business and put them into a phased roadmap, ordered by what each one would save.

Then we built the first: a client reporting agent. It pulls each client's real delivery data, matches every record to the right client and turns it into a client-ready presentation deck. It follows strict writing rules: lead with the wins, no jargon. A person checks each report before it goes out.

The result

• 4,571 records matched automatically to 57 clients
• Client reports regenerated from real records instead of screenshots
• The first agent live and verified in production, with the rest of the roadmap sized and ready

Could this work for your agency?

If your team spends the end of every month building reports, start there. See automated reporting and Agent OS, or book a call.