Your data

Team findings

Team findings reads everything your other AI employees found and turns it into findings with their figures, this week against the week before (or this month against the month before): openings, closures and strong fits by city, a rival’s new branches within 1 km of your own places, who is hiring, road incidents, the kind of place that grew most. It is the Market analyst’s eyes: every figure is counted from your results, and an xMap LLM block after it only words them.

In the editor: Reads everything your other AI employees found and turns it into findings with their figures: openings, closures and strong fits by city this week against the week before, rivals’ new branches near your own places, who is hiring, road incidents. Put an xMap LLM block set to The whole list after it to word the brief, and Make a report to send it.

Settings

Look at

Pick one

This week against the week before, or this month against the month before.

Each finding compares this period with the one before it.

Last 7 days
Last 30 days

Your own places (optional)

A setting

A table of your stores or sites in My data. Rivals’ new branches within 1 km of them become findings.

A table of your stores or sites: rivals’ new branches within 1 km of them become findings.

Most findings

Pick one

The most notable first: the biggest moves, then rivals near your places.

What comes out

Each item that leaves the block carries these fields, to use in the blocks after it as {{field}}.

One item per finding

Read by an xMap LLM block set to The whole list, then Make a report.

name: The finding in a few words.
finding: The finding in a sentence, with its figures.
kind: Openings, Rivals, Closures, Strong fits, Hiring, Roads or Kinds.
figure, before, change_pct: This period, the one before, and the change in percent.
city: Where, when the finding is about one city.

How to use it

Retail

The Monday brief for the management team

Each employee watches its own corner; the brief puts them on one page, and its figures are counted, not guessed.

FMCG distribution

Rivals near our depots, monthly

Good to know

Only the flows the analyst’s owner may see count; a colleague’s private employee stays private.
It reads, it never searches: no credits for this block. The xMap LLM and Make a report blocks after it cost what they always do.
A preview in the editor shows example findings; a run counts the real ones.
Each run posts the brief in the analyst’s Team inbox thread.

Works well with

xMap LLM: Tell the AI what to do in plain words.
Make a report: Turns the items that reach it into a clean PDF report with your logo and colour: the summary an xMap LLM block wrote for the whole list, the figures, charts of kinds and cities, a map and the list.
Email: Sends one email per run with all the items, or one email per item.
My data: Brings in a table you uploaded or a list you saved on the My data page: your stores, customers, target accounts or sites.

Templates that use it

A monthly brief on your store network: One monthly brief on your store network from everything your AI employees found.
A weekly brief from your AI employees: One brief a week from everything your AI employees found.

Stories with it

The board brief that writes itself on Monday (Fuel and charging)
Twelve AI employees, one page for the partners (Management consulting)

Help articles

The Market analyst: a weekly brief: An AI employee that reads what your other employees found and writes the brief, with charts and plain findings.
Your AI employees as an org chart: See who feeds whom, and drag one employee onto another so it hands over what it finds.

Industries that use it

Retail & franchise · Investors & consultants

Try it

Build a flow with Team findings on the home page, no account needed, or book a call. Try it live