One-minute narrated stories of a flow at work. The scenarios and figures are illustrative, not customer results.
Fuel retail
The challenge. Ali manages forty fuel stations across Bahrain for a big energy company. When a rival opens down the road, his sales there drop by a fifth within weeks. He hears about it from the station manager, a month late. By then the rival has its regulars, and his price changes and promotions come too late.
The flow. With xMap Flows, Ali built Polaris. Every morning at six, across the whole of Bahrain, Polaris scans the maps for fuel stations, picks out the ones that were not there before, finds which of Ali’s stations each is closest to, keeps those within three kilometres, and emails that area’s manager the same morning.
The result. On Sunday, Polaris spots a new station on the Riffa highway, two kilometres from one of Ali’s busiest. His area manager has a car wash offer and a coffee deal ready that week. Sales there hold steady, and the rival’s first month is quiet. Ali used to hear about rivals from his managers. Now they hear it from him.
1 dayfrom opening to alert
40stations watched
0%sales lost at Riffa
Blocks: Schedule → Area of interest → Map business scan → Only new → Find nearest → Filter → Microsoft Outlook
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Fuel and charging
The challenge. Tomas heads strategy at a large fuel and charging company in Prague. His company already has AI employees watching rivals, openings and closures across the city. But every Monday he spends the morning copying their numbers into slides for the board. By the time the deck is ready, the week has moved on.
The flow. With xMap Flows, Tomas built Quill. Every Monday at six, Quill reads what the other AI employees found this week against last, writes a short brief from their figures, turns it into a report, and emails it to the board before they arrive.
The result. This Monday, the brief leads with five new rival chargers within a kilometre of their sites in Smichov and Karlin, and two closed stations in Chodov. The board reads it over breakfast. By ten they agree on two new sites. Tomas stopped reporting on the week. Now he gets to act on it.
5rival chargers near ours
4 hsaved every Monday
2sites agreed by ten
Blocks: Schedule → Team findings → xMap LLM → Make a report → Microsoft Outlook
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Power networks
The challenge. Emma leads the line crews at a large power network company in Wellington, one of the windiest cities on earth. When a southerly storm hits, trees fall on lines and suburbs go dark. She hears the warning on the radio and calls crews in at midnight. By the time the trucks reach the hills of Karori, four thousand homes have been dark for hours.
The flow. With xMap Flows, Emma built Sentinel. Every day at five, Sentinel reads every line and substation from the company’s asset list, checks the wind forecast at each one for the next two days, keeps the ones where the wind passes ninety kilometres an hour, puts the worst first, and warns the crew leads a day ahead.
The result. On Tuesday, Sentinel flags eleven feeders in Karori and above Petone, with wind of a hundred and ten by Wednesday night. Emma books her crews in daylight and parks a truck in each valley. When the storm hits, power is back within the hour. Emma no longer chases the storm. She waits for it, ready.
24 hwarning before the storm
11feeders flagged
<1 hto bring power back
Blocks: Schedule → My data → Weather forecast → Filter → Sort and limit → Telegram Bot
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EV charging
The challenge. Elise chooses where a large electric vehicle charging company builds next in Montreal. Each site costs about two hundred thousand dollars, and she picks them from spreadsheets and gut feel. Last year, two stations opened a block from a rival’s fast chargers, and sat idle. Meanwhile, busy malls in Laval had nowhere to charge.
The flow. With xMap Flows, Elise built Compass. On the first of each month, across greater Montreal, Compass finds the supermarkets, gyms and shopping centres, counts the chargers within a kilometre of each one, keeps the ones with no fast charger nearby, asks how good each would be for a charging stop, keeps the best ten, and puts them on her map.
The result. This month, Compass looked at six hundred and forty places and found twenty-three with no fast charger within a kilometre. Elise takes the top ten to the board on one map. Her last three stations were busy in their first week. Elise stopped guessing where drivers will stop. Now she knows where they can’t.
640places checked this month
23with no fast charger near
3 of 3new sites busy in week one
Blocks: Schedule → Area of interest → Map business scan → EV charging → Filter → Jev decision → Sort and limit → Show on a map
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EV charger installation
The challenge. Jordan is an electrician in Denver who installs charging points for electric cars. Hotels are his best customers: guests with electric cars pick the hotel where they can charge overnight. But he cold calls down a list, and most already have chargers or don’t care. Three days a week on the phone bring one job a month.
The flow. With xMap Flows, Jordan built Socket. Every Monday at seven, across metro Denver, Socket finds every hotel, counts the public chargers within five hundred metres, keeps the hotels with none, puts the best rated first, and emails him the list, with every phone number.
The result. On Monday, Socket sends him thirty-four hotels, from Cherry Creek to Aurora, where a guest has nowhere to charge for half a kilometre. Jordan calls ten. Three book a site visit, and two sign before the end of the month. Jordan stopped selling chargers. He started showing hotels what they’re missing.
34hotels with nowhere to charge
3 of 10calls that booked a visit
2jobs signed in a month
Blocks: Schedule → Area of interest → Nearby places → EV charging → Filter → Sort and limit → Email
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Solar installation
The challenge. Takumi runs a small solar installation company in Osaka. He puts panels on factory and warehouse roofs. He drives the streets by Osaka Bay, squinting up from the van. From the ground, he cannot tell how big a roof is, or which buildings are new. Half his quotes go to roofs that are too small. And each new warehouse hears from another installer first.
The flow. With xMap Flows, Takumi built Skylight. Every Monday at six, across Osaka Bay and Higashiosaka, Skylight searches the maps for warehouses and factories, keeps only the ones it has not shown him before, takes a fresh satellite picture of each roof, and lays them in his inbox, roof by roof.
The result. On Monday, Takumi scrolls through thirty-one roofs over coffee. He picks the nine widest, on new buildings, and calls only those. By Friday, four owners want a quote, and every roof is big enough. Takumi used to look up at roofs. Now he looks down on them.
31roofs seen from above a week
9roofs worth a call
4quotes, every roof big enough
Blocks: Schedule → Area of interest → Map business scan → Only new → Satellite images → Email
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Commercial solar
The challenge. Jake owns a small solar company in Phoenix. He puts panels on the flat roofs of warehouses and workshops. The roofs are easy to see from the street, but finding who owns them is not. He knocks on doors and meets tenants who cannot decide. Weeks later, he learns the owner lives in another state, and the roof went to a bigger installer.
The flow. With xMap Flows, Jake built Sunray. Every Monday at seven, across west Phoenix, Sunray finds the warehouses and workshops, skips the ones he has seen before, looks up who owns each building in the county records, scores the best roofs for solar, and emails Jake each owner’s mailing address.
The result. This Monday, Sunray finds thirty-eight new buildings, each with its owner and their mailing address. Twenty-two owners live out of state. The best roof, near the airport, belongs to an investor in Chicago. By Friday, Jake has booked a site survey. Jake stopped knocking on tenants’ doors. Now he writes straight to the owner.
38new buildings this week
22owners out of state
1survey booked by Friday
Blocks: Schedule → Area of interest → Nearby places → Only new → Property changes → xMap LLM → Email
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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 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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