The credit committee starts every week on fresh sales
Omar heads mortgage risk at one of Riyadh’s largest banks. His team signs off on thousands of home loans a year.
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The challenge
The credit committee prices risk from a valuation report that is three months old. By the time it lands, prices in the fast-growing north have moved. Two analysts spend a week each quarter pulling sales by hand, and the numbers still arrive late.
How the flow works
With xMap Flows, Omar built Ledger. Ledger is an AI employee: a flow of 6 blocks.
Every Sunday at seven,
Every Sunday at 7 (Schedule)
Ledger brings in last week’s recorded property sales across Riyadh,
Last week’s sales, Riyadh (Regional data sources)
keeps the homes that sold with a price,
Homes with a price (Filter)
labels each one a small, family or large home,
Small, family or large (Calculated field)
writes what moved, district by district,
What moved, by district (xMap LLM)
and sends the committee a report before Monday’s meeting.
The committee’s report (Make a report)
What it solves
- Three-month-old values: solved by Schedule and Regional data sources
- A week of manual pulls: solved by Regional data sources and xMap LLM and Make a report
- The north moves first: solved by Calculated field and xMap LLM
The result
On Monday the committee reads last week, not last quarter: about nine hundred home sales, and a note that family villas in the north sold for the most per metre. Omar’s analysts spend their week on the loans, not the spreadsheets.
The committee stopped looking back a quarter. Now it starts each week on fresh sales.
An illustrative scenario: the figures are modelled to show what the flow produces, not a customer's results.
The flow, block by block
- 1
- 2
Last week’s sales, Riyadh
Regional data sources · Regional data
xMap’s regional datasets: pick a country, then a dataset, such as real estate transactions in Saudi Arabia, property for rent or for sale listed right now in the United States, Japan and the United Arab Emirates, or Road traffic history in the United Arab Emirates (cars counted hour by hour since 2021).
- 3
- 4
Small, family or large
Adds fields worked out from the others: a number, a text or a yes/no.
- 5
- 6
The committee’s 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.
Templates to build it
Ready-made flows with the same blocks. Open one, change the city and the kind of place, and run it.
- Impact report for donors: people around each siteThe reach section of the donor report, from the people around each site.
- Stores competing with each otherYour stores that sit within 1 km of each other, with the people around them.
- Where to open sample collection pointsThe blocks of your city with the most adults and the fewest labs, scored and approved every month.
- Where to open serviced apartmentsThe blocks where business travellers need serviced apartments, scored and approved.
- Where to put scooter and bike hubsThe blocks for scooter and bike hubs, near stations and people, approved every month.
- Where to open my next cafeAreas with many residents and few cafes, scored for your next cafe.
Industries
Learn how it works
- Location intelligenceUsing where things are, and what is around them, to make business decisions.
- Site selectionChoosing where to open a store, branch, clinic or facility.
- Lead scoringRanking prospects by how likely they are to buy.
- The Market analyst: a weekly briefAn AI employee that reads what your other employees found and writes the brief, with charts and plain findings.
- Build your first flow in ten minutesFrom a blank page to a flow that emails you a ranked list every morning.
- Enrich a list onceA CSV of addresses or companies back with phone, website, rating and an AI score.
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Build this flow on your own city
Run a live search on the home page without an account, or let Ask xMap build the flow from one sentence.