One-minute narrated stories of a flow at work. The scenarios and figures are illustrative, not customer results.
Hotels
The challenge. Isla leads corporate sales at a big hotel near Haymarket in Edinburgh. Business travellers fill her rooms from Monday to Thursday. Her best accounts are companies growing in the city, but she finds them by chance. Last year, a tech firm hired eighty people and booked every interview guest at the hotel across the road. Isla heard about it from the doorman.
The flow. With xMap Flows, Isla built Envoy. Every Monday at eight, Envoy finds the companies hiring in Edinburgh, finds each one’s office, measures how far it is from the hotel, keeps the ones within two kilometres, skips the companies already on contract, finds the office manager, and sends a first hello.
The result. This Monday, Envoy finds thirty-one companies hiring within two kilometres. A software firm in the Quartermile wants fifty engineers. Isla’s hello lands on Tuesday, and by Friday they have signed for every interview guest this spring. Isla used to hear about new accounts from the doorman. Now she hears first.
31companies hiring nearby
50engineers, many interview guests
1new account by Friday
Blocks: Schedule → Job postings → Map business scan → Find nearest → Filter → Match with my table → Apollo → Outreach
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Boat tours
The challenge. Lucas runs sailing trips for tourists from the port of Buceo in Montevideo. Two boats, eight guests each. The wind on the river can turn in an afternoon. Lucas checks four weather sites every night and still gets it wrong. Last month he cancelled at the pier, with sixteen guests already in life jackets. Six asked for refunds, and left reviews to match.
The flow. With xMap Flows, Lucas built Lookout. Every afternoon at five, Lookout reads tomorrow’s bookings, checks the wind at the pier, asks if it is too strong to sail, picks the next calm day if it is, offers it to those guests on WhatsApp, and tells everyone else to bring sunscreen.
The result. On Thursday, Lookout sees gusts of forty-five kilometres an hour for the morning trip. By six, all eight guests have moved to Saturday, and seven of them said thank you. The afternoon trip sails full. Lucas still can’t change the wind. Now he just knows it a day early.
8 of 8guests moved a day ahead
0cancellations at the pier
7thank-you messages
Blocks: Schedule → My data → Weather forecast → Branch → xMap LLM → WhatsApp Business
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Hotels
The challenge. Minjun leads guest experience for a big hotel group in Seoul, with fourteen hotels from Myeongdong to Gangnam. Guests ask the front desk the same things all day: where to eat now, where the nearest pharmacy is, will it rain tomorrow. Most questions come after ten at night, in five languages. Lines form, and the night staff can’t check in arriving guests.
The flow. With xMap Flows, Minjun built Compass. When a guest writes in the hotel’s chat, Compass works out what they need, finds the places near their hotel, checks tomorrow’s weather, and answers in the guest’s own language.
The result. Tonight, Compass answers three hundred and ten questions. A family in Myeongdong finds a pharmacy four hundred metres away, rated four point six. The night desk checks in every late flight without a line. Every guest now has a concierge who knows the streets, even at two in the morning.
310questions answered tonight
5languages, one concierge
0lines at the night desk
Blocks: Chat → AI agent → Nearby places → Weather forecast → Reply
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Tours and excursions
The challenge. Marta runs the guide teams of a big tour company in Barcelona. Cruise passengers are a third of her business. Ships come in early, late, or not at all, and the port’s list changes overnight. Marta keeps forty guides on call just in case. Some mornings, half of them wait at the terminal for nothing. Other mornings, a ship arrives early and nobody is there.
The flow. With xMap Flows, Marta built Harbor. Every half hour from four in the morning, over the sea off Barcelona, Harbor listens for the passenger ships, keeps the ones heading for Barcelona, skips the ones already counted, works out the guides from each ship’s size, and calls the guides in on WhatsApp.
The result. At five this morning, Harbor hears a three hundred metre ship coming in an hour early, off Sitges. Twelve guides are told before six and meet it at the terminal. On quiet days, the rest stay home. Marta stopped guessing which ships would come. Now she watches them arrive.
1 hearly, and still met
12guides told before six
40guides no longer on call
Blocks: Schedule → Area of interest → Ships (AIS) → Filter → Only new → Calculated field → WhatsApp Business
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Group travel
The challenge. Ines is a freelance travel planner in Lisbon. Companies send her their conference groups, from twenty to two hundred people. Each new request lands in a shared Excel sheet. Ines then spends a whole day finding hotels near the venue, checking ratings and walking times. Clients want a proposal within hours. Last month, she lost two groups to a big agency that answered first.
The flow. With xMap Flows, Ines built Tempo. When a client adds a request to the sheet, Tempo draws a fifteen-minute walk around the venue, finds the hotels inside it, keeps the ones rated four or more, picks the best ten, writes the proposal, lets Ines check it, and sends it from her own address.
The result. On Wednesday at ten, a bank adds a group of one hundred and forty for a conference in Belem. By half past ten, Ines has checked the proposal: nine hotels within a fifteen-minute walk, all rated four or more. The bank books by lunch. Ines still works alone. She just answers like an agency of twenty.
30 minfrom request to proposal
9hotels within a 15-minute walk
140guests booked by lunch
Blocks: Microsoft Excel 365 event → Travel area → Nearby places → Filter → Sort and limit → xMap LLM → Approval → Microsoft Outlook
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Travel agencies
The challenge. Karan owns three travel agency shops in Mumbai. Families come in to plan their holidays and weddings abroad. He wants a fourth shop, and every landlord says theirs is perfect. Karan has spent four Sundays walking the suburbs. One lease in Andheri looked busy, but the street was full of office workers, not families, and three rival agents shared the lane.
The flow. With xMap Flows, Karan built Scribe. When Karan adds a shop he was offered, Scribe counts the children and adults living within two kilometres, counts the rival travel agents nearby, works out the families for each rival, says if the shop is worth a visit, and sends him the answer on WhatsApp.
The result. This week, Karan adds seven shops. Scribe rules out five within a minute each. The one in Borivali has ninety thousand children within two kilometres and only one rival. He signs the lease on Saturday, without walking a single street. Karan stopped walking the suburbs. Now the suburbs report to him.
7shops checked in a week
90kchildren within 2 km
1rival agent nearby
Blocks: New rows → Demographics → Nearby places → Calculated field → xMap LLM → WhatsApp Business
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Holiday lets
The challenge. Anna rents out two holiday flats near the Parliament in Budapest. Her guests love her little guidebook of places around the corner. Last month, a family walked to her favourite bakery and found it closed for good. A cafe on her list had slipped to two stars. Each surprise ends up in a review, and checking forty places by hand takes a whole weekend.
The flow. With xMap Flows, Anna built Curator. On the first of every month, Curator draws a five-minute walk around each flat, finds the cafes, bakeries and pharmacies inside it, spots the ones that closed or slipped, tells Anna about them, keeps the open ones rated four or more, rewrites the guidebook, and saves it in the folder her guests open.
The result. This month, Curator finds a new bakery two streets away and a cafe that closed in August. Both are fixed in the guidebook before the next guests land. Anna keeps her weekend, and her rating climbs back to four point nine. Anna’s guidebook used to age by the month. Now it renews itself on the first.
40places checked each month
0closed doors for guests
4.9rating, back up
Blocks: Schedule → Travel area → Nearby places → What changed → Email → Filter → xMap LLM → Google Drive
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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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