One-minute narrated stories of a flow at work. The scenarios and figures are illustrative, not customer results.
Mobile networks
The challenge. Chidi runs diesel deliveries to the generators at nine hundred mobile towers across Lagos. When the grid fails, the towers run on diesel. In the rainy season, roads flood and his tankers get stuck for a day. Towers run dry, and whole neighbourhoods lose signal. Last July, sixty towers went dark in one week.
The flow. With xMap Flows, Chidi built Juniper. Every morning at five, Juniper reads the towers running low on diesel from the company’s fuel list, checks the rain coming at each one, and where heavy rain is on its way, plans a refuelling run for today, sends it to the drivers in Teams, and keeps the rest on the normal schedule.
The result. On a Monday in July, Juniper sees heavy rain heading for Ikorodu and Lekki on Wednesday. Twenty-six towers are filled on Monday and Tuesday, before the water rises. That week, not one tower runs dry. Chidi can’t stop the rain. He just gets there before it.
900towers watched
26filled before the rain
0towers ran dry that week
Blocks: Schedule → My data → Weather forecast → Branch → Route planner → Microsoft Teams → Google Sheets
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Mobile networks
The challenge. Rachel is a radio network planner at a big mobile operator in Singapore. Weak signal complaints reach her in a spreadsheet, a week late, mixed with outages fixed long ago. She can’t tell a real coverage hole from a bad afternoon. So antennas go where people shout loudest, and customers wait days for an answer.
The flow. With xMap Flows, Rachel built Sonar. When a signal complaint lands in the support sheet, Sonar checks that address against the network’s outage list, and if it is an outage, tells the customer when it will be fixed, or, if not, adds it to Rachel’s map of real coverage holes.
The result. In three weeks, Sonar answers four hundred customers within minutes, and puts a hundred and twenty real complaints on Rachel’s map. They cluster around new tower blocks in Punggol and Tampines. Her next six antennas go exactly there. Rachel used to plan by the loudest complaints. Now she plans by the weakest signal.
400customers answered in minutes
120real coverage holes mapped
6antennas placed right
Blocks: New rows → Match with my table → Branch → WhatsApp Business → Show on a map
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Mobile retail
The challenge. Andres plans where a big mobile phone company opens its stores in Lima. Lima has grown fast, out into districts like Comas and Ate. His store map is ten years old. People there ride an hour into the centre to buy a phone, or give up and buy from a street stall. He cannot see which districts want a store.
The flow. With xMap Flows, Andres built Radar. Every quarter, across all of Lima’s districts, Radar finds every phone shop, repair stall and accessory store, sorts them into clean categories, measures how far each one is from the company’s nearest store, keeps the ones more than three kilometres away, and maps where they cluster.
The result. Radar finds twelve hundred phone shops in clusters more than three kilometres from any store. The biggest are in Comas, Ate and Villa El Salvador. Andres opens two stores there in spring, and both reach their target in the first month. Andres found his next stores by following the phone shops.
1,200phone shops far from a store
3districts with no store
2new stores, on target
Blocks: Schedule → Area of interest → Map business scan → Place classifier → Find nearest → Filter → Show on a map
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Telecom field services
The challenge. Emre is a freelance tower technician in Istanbul. He climbs mobile phone masts for the telecom companies. Above fifty kilometres an hour of wind, he cannot climb. Too often he crosses the Bosphorus in two hours of traffic, only to stand under a mast in a gale and drive home again. Each wasted trip is a day he isn’t paid.
The flow. With xMap Flows, Emre built Maple. An hour before each site visit on his calendar, Maple finds the mast in his list of sites, checks the wind there, looks for closures and accidents around it, weighs it all up, and tells him on Telegram whether to go.
The result. On a Thursday, Maple warns him the mast in Sariyer will see winds of sixty-five by noon. He swaps it for the Kadikoy job, where the air is calm. That month, he loses not one day to the wind, and finishes six more jobs. Emre still climbs in Istanbul’s wind. He just never drives into it.
50 km/hhis safe wind limit
0days lost to the wind
+6jobs a month
Blocks: Google Calendar event → Match with my table → Weather forecast → Traffic incidents → xMap LLM → Telegram Bot
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Business telecom
The challenge. Sakura leads business sales for a big telecom company in Tokyo. She sells office internet and phone lines. The best moment to win a company is when it moves office. But she hears about moves after the contract is signed with someone else. Her team calls hundreds of offices in Marunouchi and Shinagawa, asking if anything is changing. Almost nothing is.
The flow. With xMap Flows, Sakura built Birch. Every Monday at eight, Birch finds the Tokyo companies hiring office and facilities managers, looks up each company’s office, scores how likely each is to be moving or opening an office, keeps the top fifteen, and sends the list to her team.
The result. This week, Birch finds ninety companies hiring office managers, and fifteen that look like a move. Her team calls those first. Four are planning new floors in Shibuya and Toyosu, and two sign before they move. Sakura’s team stopped asking who is moving. Now they call the ones who are.
90companies hiring office staff
15likely to move
2contracts signed early
Blocks: Schedule → Job postings → Map business scan → Jev decision → Sort and limit → Email
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