Automate your territory evidence gathering with an AI agent

The attributes behind the polygons

A feature layer is a table with a shape attached, and the table is where the decisions live: which accounts sit in which territory, what each is worth, when it was last visited.

A companion reads those attributes and reports the imbalance in plain numbers. It reads every account in every territory, which is why the imbalance arrives as a number instead of an impression.

What does the outside world say about your regions?

Which employers announced expansions, which closed, where new development was approved, which competitor opened a branch. None of it is in a layer.

A companion gathers that for every region and attaches it to the attributes you already hold, which turns a static territory table into something with a reason for changing. The research habit is automate market research.

• Public signals gathered per region with sources recorded.
• Findings written back as attributes or as a report, with the writes waiting for approval.
• Regions where the evidence contradicts the current plan flagged rather than ranked.

How do you keep a feature layer from going stale?

Operational layers rot the way CRM records do.

Sites that closed, addresses that moved, a status field that stopped being maintained when its owner changed jobs.

A companion checks every feature against public reality and proposes the updates. Scheduled quarterly it fits with your other operations routines.

Where the GIS team stays in charge

Everything spatial, plus the data model.

Projections, joins, geocoding quality, symbology and the analysis workflows are a specialism.

GIS answers where, and a companion answers what changed there. Both are needed to redraw a boundary defensibly.

Frequently asked questions