One-minute narrated stories of a flow at work. The scenarios and figures are illustrative, not customer results.
Car rental
The challenge. Salim runs the fleet at one of Oman's biggest car rental companies, based in Muscat. When a tourist breaks down on the road to Nizwa, his team calls the nearest garage on their list. Too often it has closed, moved, or changed its number. The tourist waits in forty degree heat, and the company pays for a tow from across town.
The flow. With xMap Flows, Salim built Sentinel. Every Sunday morning, Sentinel takes the company's list of partner garages, looks each one up again, spots the ones that closed or changed their number, finds a well rated garage near each one that closed, and sends the fleet team the fixed list.
The result. On Sunday, Sentinel finds two garages that closed and three with a new number, and a well rated garage near each one that closed. The list is right before the week starts. On Tuesday a car broke down near Seeb, and help came in twenty minutes. Salim's garage list used to age in a drawer. Now it checks itself every week.
2closed garages caught
3phone numbers fixed
20 minfor help to arrive
Blocks: Schedule → My data → Map business scan → What changed → Nearby places → Email
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Bike sharing
The challenge. Bruna plans new docks for a bike-share company in Sao Paulo. Each dock costs as much as a small car. Her team puts docks where people ask for them on social media. Half the new ones see a few rides a day. Meanwhile, thousands of short trips around the metro stations are still made by car, stuck in traffic.
The flow. With xMap Flows, Bruna built Spoke. Every three months, Spoke lists the metro stations, universities and office towers, learns how people travel to each one, and how far they come, keeps the places where most trips are short and by car, ranks the best twenty, puts them on a map, and posts them to the planning team.
The result. This quarter, Spoke finds twenty spots where most trips are under three kilometres and made by car, half of them around Paulista and Faria Lima. Bruna puts ten new docks there, and each sees four times the rides of last year’s docks. Bruna stopped guessing where riders are. Now she goes where the short trips are.
20spots with short car trips
10new docks placed
4xrides per dock
Blocks: Schedule → Nearby places → Mobility Footfall → Filter → Sort and limit → Show on a map → Slack
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Car sharing
The challenge. Manon plans new stations for one of the largest electric car sharing services in Paris. Every week the city offers her a few streets for new stations. To judge one she pulls up population, charger and metro maps, and a single street takes a morning. The city wants answers by Friday, and good streets go to rivals while she checks.
The flow. With xMap Flows, Manon built Scout. When Manon types a street into the team's chat, Scout weighs it like a planner, counts the people living within five hundred metres, finds the public chargers already there, checks the metro stations and car parks nearby, and answers with a verdict and the numbers.
The result. This week the city offers nine streets, and Manon checks all nine before lunch on Monday. Rue de Belleville has fourteen thousand people within a short walk and just two chargers, so the city gets her yes that evening. Manon used to research streets. Now she just has a conversation about them.
9streets checked by lunch
14,000people near the best one
4 dayssooner than before
Blocks: Chat → AI agent → Demographics → EV charging → Nearby places → Reply
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Shopping malls
The challenge. Thiago is the marketing director of a group that owns three shopping malls in Sao Paulo. He spends millions on billboards and radio, spread across the whole city, because nobody knows where shoppers really come from. The yearly survey asks two hundred people at the door. By the time it is printed, a new metro line has changed everything.
The flow. With xMap Flows, Thiago built Lodestar. On the first Monday of every month, Lodestar takes his three malls, learns where their visitors come from and how they travel, picks the districts worth advertising in, makes a short report, and sends it to the media agency.
The result. This month, Lodestar shows that one in three visitors to the mall in Itaim come from Pinheiros and Vila Olimpia, and most arrive by car. Thiago moves half his billboards to those two districts, and puts a parking offer in every ad. Thiago stopped advertising to the whole city. Now he talks to his own shoppers.
1 in 3visitors from two districts
50%of billboards moved
3malls measured every month
Blocks: Schedule → My data → Mobility Footfall → xMap LLM → Make a report → Email
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Ride services
The challenge. Linh leads driver operations at one of Hanoi's biggest motorbike taxi services. When a storm breaks over the city, ride requests jump in minutes. Drivers are on the wrong side of town, riders wait in the rain, and half of them cancel. Her team only learns where the rain hit from the complaints, an hour later.
The flow. With xMap Flows, Linh built Rainwatch. Every morning at five and again at noon, Rainwatch looks at her twelve busiest districts, checks how much rain is coming to each one today, saves every forecast in the team's sheet, picks the districts where heavy rain is coming, and tells the dispatch room to send drivers there early.
The result. At five, Rainwatch sees heavy rain coming for Cau Giay and Ba Dinh. Dispatch moves one hundred and twenty drivers there before the afternoon rush. Waits stay under five minutes, and the sheet shows which districts fill up every time it pours. Linh's drivers no longer chase the storm. They are already there.
120drivers moved before the rain
5 minlongest wait in the storm
12districts watched
Blocks: Schedule → My data → Weather forecast → Google Sheets → Filter → Microsoft Teams
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Bike share
The challenge. Lars runs operations for a big city bike share in Copenhagen. On sunny days everyone rides to the harbour baths and Amager Strand. By noon those docks are full, while Norrebro has no bikes left. His van crew starts each morning guessing which docks to fill, and by the time they know, the sun has gone in.
The flow. With xMap Flows, Lars built Balance. Every morning at five, Balance reads how many bikes are in every dock, checks today's forecast at each one, works out each dock's shortfall with the team's own sunny day rules, keeps the docks that will run short, plans the van's loop from the depot, and sends it to the crew's phones.
The result. On a hot Saturday, Balance sees twenty six degrees coming and twenty two docks that will be empty by eleven. The vans leave at six with the loop planned and move four hundred bikes back into the city. Riders find a bike at every dock all day. Lars's crew stopped chasing the sunshine. Now they get there before it.
22docks filled before the rush
400bikes moved by eleven
0empty docks on a hot day
Blocks: Schedule → My data → Weather forecast → Custom code → Filter → Route planner → Telegram Bot
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Car rental
The challenge. Diego runs a small car rental business near the airport in Mexico City. His customers drop their cars back on the way to their flights. When the traffic turns solid, they arrive late and panicked, and some miss their plane. They blame him in their reviews, and he refunds the day.
The flow. With xMap Flows, Diego built Timekeeper. Every half hour from five in the morning, Timekeeper takes the day's returns and where each customer is staying, measures how jammed the roads around each hotel are, works out when each customer should leave, picks the ones who should leave soon, skips anyone already told, and sends each one a friendly message with the time to go.
The result. On Friday afternoon the roads around Polanco slow to a crawl. Timekeeper tells three customers staying there to leave forty minutes early. All three hand back their keys with time for a coffee, and one of them books again for next month. Diego can't clear the traffic. But his customers no longer miss their planes.
3customers warned on Friday
40 minearlier, before the jam
0missed flights since
Blocks: Schedule → My data → Traffic Flow → Calculated field → Filter → Only new → WhatsApp Business
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Electric delivery fleet
The challenge. Hannah leads a fleet of electric delivery vans for a big grocery delivery company in San Francisco. Her drivers run low on charge mid shift and call dispatch: where is a working fast charger near me? Dispatch looks it up on three apps while the van waits by the curb. That is twenty calls a day, and each one costs a delivery window.
The flow. With xMap Flows, Hannah built Spark. When a driver writes where they are in the team's Slack, Spark reads the question, finds the working fast chargers closest to the van, finds somewhere for a coffee while it charges, and answers in the thread within seconds.
The result. At two o’clock a driver in the Mission writes that he has twelve percent left. Spark answers in eight seconds with a fast charger four blocks away and a cafe next door. Dispatch takes no charging calls now, and the vans keep their windows. Hannah's drivers stopped calling for directions. They just ask, and go.
8 sto answer a driver
0charging calls to dispatch
20calls a day, gone
Blocks: Slack event → AI agent → EV charging → Nearby places → Reply
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Car rental
The challenge. Nora runs a small premium car rental at Geneva Airport: twelve cars and a very small office. Geneva sits right on the French border, and many customers cross it without the cover they need. She finds out when a car comes back with a ticket from Annecy, or a bent bumper the insurance will not pay for. Then she chases them for weeks.
The flow. With xMap Flows, Nora built Vega. Every half hour, Vega reads where each car is from her tracker table, notices any car that has crossed into France, looks up its booking, keeps the ones booked without the France cover, and sends the driver a friendly note with a link to add it.
The result. On Saturday morning two cars cross into France on the way to Chamonix. Within half an hour both drivers get her note, and both add the cover from their phones before they reach the mountains. This season she has not chased a single customer. Nora stopped chasing customers after the trip. Now she looks after them on it.
30 minfrom border to note
2covers added on Saturday
0customers chased this season
Blocks: Schedule → My data → Zone alert → Match with my table → Filter → WhatsApp Business
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