Reading Town Meeting Notes for Business Opportunities, Automatically

A construction and development firm we've been piloting work with has a business development team that watches town meeting notes closely. Planning board minutes, select board updates, zoning discussions — that's often where the earliest signal of a project worth pursuing shows up, long before it's a public bid.

The problem

Someone on the team was reading through town meeting notes by hand, town by town, looking for the kind of mentions that signal a future opportunity: a new project discussed, a permit application, a board raising a concern that might need outside expertise. It's exactly the kind of task that rewards experience and pattern recognition, and exactly the kind of task that doesn't scale past the one or two people who know what to look for.

What we built

We started with one town as a pilot. The team's business development lead wrote out, in her own words, what she actually looks for when she reads these notes — her "instructions to an intern." We used that as the actual criteria for the automation, rather than guessing at what counts as a signal, so it reflects how she really evaluates a mention, not a generic keyword scan.

The automation pulls a town's meeting notes and flags the passages that match those criteria, so the team can go straight to the handful of mentions that are actually worth a look instead of reading the whole document.

Where it stands

This is early. It's a working pilot for one town, not yet a rollout across every town the team tracks, and we're still gathering feedback on whether the flagged mentions match what a person would have caught. Real automations get tuned against real judgment before they're trusted at scale, and that's the stage this one is at now.

The takeaway

The most useful automations usually start this way: one process, one person's real criteria, one narrow pilot, before anything gets scaled up. If your team has a manual-scanning task like this — meeting notes, public filings, industry newsletters — that's the same shape a pilot with us usually takes.

If your team has a similar early-signal process buried in something like meeting notes or public filings, we'd be glad to talk through how we'd approach it.

Frequently asked questions

Can AI automatically scan town meeting notes for business opportunities?

Yes. Claude can read planning board minutes, select board updates, and zoning discussions and flag the passages that match a custom set of criteria — developed from what an experienced business development professional actually looks for. The result is a shortlist of mentions worth reviewing, rather than a full document to read.

How does an AI meeting notes monitoring pilot work for construction firms?

The process starts by capturing how an experienced person evaluates meeting notes — what signals matter, how they distinguish a real opportunity from routine business, what language patterns they watch for. Those criteria become the filter the automation applies. A pilot typically starts with one town's notes, runs them through the filter, and compares the output against what a person would have caught before expanding to more towns.

What business development signals appear in town planning board minutes?

New project discussions, permit applications, requests for proposals, zoning variance applications, and board discussions of outside expertise needs are the most common early signals for construction and development firms. These often appear months before a formal bid process begins, which is why teams that read meeting notes closely tend to have a first-mover advantage on certain types of work.