80%
strong interest in seat matching
Our survey
Intelligent seating for shared travel
Better Seatmates. Better Journeys.
Intelligent seating optimization for more personalized shared travel experiences. SeatUp optimizes who sits next to whom, not just where people sit, under your hard rules.
First focus: tour operators running guided coach tours.
You can choose your flight, meal, hotel, seat... But seatmates are still a big gamble.
Ever had a train ride feel like an eternity next to a loud seatmate? Or a six-hour flight fly by in a captivating conversation? Seatmates make a trip memorable or miserable.
Travelers care. And they're letting us know.
92%
would share their travel mood
Our survey65%
fear a chatty seatmate
Expedia study, 1,000 U.S. adultsOperators are interested: several calls with tour operators confirmed their interest.
Our survey: exploratory online survey, 150+ respondents in 20+ countries; stated preferences, not a representative sample.
How it works
Three steps, no new system
Travelers answer a few questions
Optional, at booking or before departure. You choose the questions that matter for your trips.
SeatUp sits everyone
Our algorithm weighs travel mood, languages and interests and keeps groups together. Premium travelers can get priority, never above hard constraints.
Seats land in your booking flow
Our goal: an API that drops SeatUp seats into your reservation system. Today, the prototype produces the full seating plan. Nobody ever sees anyone else's answers.
Seats are chairs, not the whole table. SeatUp does all dimensions.
Not Seat Selection. Cabin Optimization.
| First Come | Operator Choice | SeatUp | |
|---|---|---|---|
| Seating | Passenger decides | Operator-led | Passenger-matching agent |
| Compatibility | None | Guide's intuition | AI + Behavioral Sciences |
| Families & accessibility | No guarantee | Manual | Hard constraints |
| Operator effort | Low | High | Minimal |
Behavioral modelForm and optimization model built with sociologists of Centre de sociologie de l'innovation (CSI), PSL (UniversitΓ© Paris Sciences & Lettres), powered by AI
For travel operators
It's a win-win deal
Seating becomes part of the trip you sell, not a last-minute back-office task. These are the effects our pilots will measure.
Well-seated passengers
- ExpectedFewer complaintsLower customer-service costs
- ExpectedBetter reviews & word of mouthFree publicity, more bookings
- ExpectedA unique selling pointTravelers choose you over competitors
- ExpectedLoyalty & recommendationsMore repeat trips
- LaterPriority matchingNew revenue per passenger
- LaterData insights on how passengers travelBetter offers and pricing
More revenue
Expected effects, to be measured against a control group in our first pilot.
See the difference
Same passengers. Better seatmates.
The numbers here are computed live in your browser by the SeatUp engine. In the demo, answer four questions, then see the same coach without and with SeatUp, side by side.
Try Smart Seating βTravelers well matched (predicted)β β β
Quiet travelers next to a talkerβ β β
Great-match seatmate pairs (predicted)β β β
Simulated 48-seat tour coach, synthetic travelers. Compatibility is predicted by our model, not measured satisfaction.
Who it's for
Starting with guided coach tours
One operator decides and controls every seat, travelers spend days together, and a guide can invite everyone to answer. Other shared journeys come next.
Tour operators & guided coach tours
One buyer controls every seat of a 40β50-seat coach. The seating plan becomes part of the experience, and a pilot needs no complex integration.
Coach & shuttle companies
Long rides in full vehicles, where the right seatmate makes the trip.
Airlines
Turn seat selection into a premium matching option.
Rail operators
Long-distance and night trains, where neighbors matter most.
Booking & distribution platforms
Our vision: offer SeatUp seating to all your partners through one API.
Under the hood
Seating you up right, every time
Transport-agnostic
π π βοΈ
Coach, bus, train and plane layouts already run in our prototype.
Simple passenger form
Anonymous, non-intrusive and optional. At purchase or before departure.
Travel moodLanguagesInterestsAgeOwn words (keyword reading)Travel style (planned)
Explainable engine
- Human behaviorWhat travelers tell us
- Compatibility modelExpert-informed rules
- Seat optimizationWhole cabin, hard rules first
Deterministic and explainable today. Learning from real trip feedback is on our roadmap.
Expert-informed matching: CSI, PSL (below).
The science behind the seats
An expert-informed compatibility framework
Our compatibility framework was developed with input from sociologists at the Centre de sociologie de l'innovation (CSI), PSL (UniversitΓ© Paris Sciences & Lettres), an internationally recognized research center in Science and Technology Studies (STS). Founded in 1967, the CSI has been one of the world's leading STS centers since the 1980s. About the CSI β
Their input shaped four things:
- Question design: what each question reveals about a traveler, and why it matters.
- Individual and group compatibility: how much travel mood, languages, interests and age should count, for two people and for a group sharing the same space.
- Preferences and interactions: languages and interests matter only if people want to talk.
- Weighting principles: avoiding a bad pairing matters more than creating a perfect one.
Expert input shaped our design; it is not a validation of our results, and not an institutional partnership. Calibrating the model on real trips is what our pilots are for.
Compatibility Score, 0β100%
Seatmatetravel mood Β· languages Β· interests Β· age
+Around youfront Β· back Β· aisle atmosphere
Cabin zones, front to back
Hard rules, always kept
- πͺ Booked together sit together
- βΏ Accessible seats for those who need them
- β Kept-apart requests
- π Operator pins
Evidence
How we validate SeatUp, step by step
-
Done
1Expert-informed design
Questionnaire and weighting principles developed with sociologists of the CSI, PSL: what makes two people, and a group, get along.
-
Done
2Algorithmic validation
Automated tests and a reproducible benchmark on 1,000 synthetic cabins, with the same hard rules on both sides:
1,000 / 1,000cabins where SeatUp beats the best of 10 random valid seatings (modeled score)2.8 β 0.2predicted seatmate clashes per cabin0hard rules broken -
Next
3Real-world impact
Pilots with tour operators: traveler satisfaction measured against departures seated the usual way, then the weights calibrated on real trips. Until then, every SeatUp number is a model prediction on synthetic travelers.
Built for trust
Risks Managed. Impact Measured.
Passenger Adoption
RisksLow participation, digital exclusion
Our approachOptional 30-second survey. Everyone gets seated, even without answers.
KLM Meet & SeatProfiles and picking your own seatmate: too much effort
Matching Quality & Fairness
RisksPredicted β actual satisfaction, bias
Our approachCompare with control groups, assess fairness and recalibrate.
Malaysia Airlines MHbuddyFacebook friends only: no matching between strangers
Privacy & Trust
RisksPersonal data, consent, GDPR
Our approachOpt-in, anonymized data. We do the matching: operators get seats, never answers.
SatisflyMatching from social-media data
Operational Integration
RisksExisting workflows, seat constraints
Our approachHard rules, manual overrides, white label: one button opens our hosted form.
KLM Meet & SeatOne airline, a few routes only
Business model
Simple, scalable pricing
Pay per traveler seated, or subscribe for volume. Hypotheses we are testing with operators: no contract or validated price yet.
β¬1per traveler
- No subscription
- Pay for travelers seated
β¬249/ month
- 300 travelers a month
β¬1,999/ month
- 3,000 travelers a month
Custom
- Unlimited travelers on your own tours
- Priced on size and forecast volume
Subscriptions count distinct travelers seated in the month: re-optimizing the same traveler is not billed twice. Overage rules are still to be defined.
+ Premium+β¬2 per premium traveler (β¬3 in total): priority matching, never above hard rules
Just β¬1 per traveler
< 0.1% of an average β¬1,081 tour
European market
50M bus tour passengers a year β 2% share β > β¬1M / year
Pay per traveler β Recurring subscriptions β Enterprise partnerships
Team & advisor
The team
Tony Glory
ι«δ»£θ£Co-founder & CEO
π Dallas
Eric GrΓ©ly
ιι³εCo-founder & CTO
π Paris
FrΓ©dΓ©ric Ollier
Advisor
π RomeWe aim to become the passenger standard for human-centered seat allocation.
Roadmap
What exists, and what comes next
- Seating engine: hard rules, groups, accessibility, requests, non-respondents
- Operator console and the traveler demo, offline-ready
- Reproducible benchmark on 1,000 synthetic coaches
assign_seats: a structured interface, as a local prototype
- Now: commercial conversations with tour operators
- Months 1β3: first pilot departures
- Months 3β9: satisfaction measured against a control group
- Months 9β12: integrations, privacy review, first paid contract
- Then: booking platforms, AI travel agents, international
Let's pilot it together.
We run SeatUp on a few of your departures and compare them with departures seated the usual way: answer rate, satisfaction with seatmates, seat-change requests and preparation time.
Prefer email? antoine@seatup.info Β· eric@seatup.info