Should I translate my hotel website? When and how
Translation is now the cheap part of a multilingual hotel website. The real cost is keeping every language current, findable and bookable.
What we do
One place where the numbers are true
Not a dashboard. The layer underneath the dashboards, which is the part that decides whether any of them are right.
Every source connected
Booking engine, PMS, ad platforms, analytics, email, payments. Purpose-built connectors where no export exists.
Cleaned and reconciled
Currencies, timezones, units and definitions resolved, so revenue means one thing wherever you read it.
One guest, one record
Working out that the person who booked, subscribed, paid and reviewed is the same guest. The hardest part, and the one that pays.
History that stays yours
We keep the raw layer permanently, so your data stops being something a platform deletes after fourteen months.
Checked before you see it
Assertions that stop the pipeline rather than report on it afterwards. Wrong data never reaches a report.
Ready for your AI
A governed layer your own assistants can query, with the meanings already resolved before they get there.
Technology partners
Deep experience with the systems you already run
How it works
Three layers, like a kitchen
The structure is standard. The analogy is the quickest way to see why it is built this way.
The delivery bay
Raw ingredients arrive exactly as they were sent. Nothing cleaned, nothing changed, nothing thrown away. If anything goes wrong further down the line, the original is still there.
The prep kitchen
Where it gets cleaned, sorted and matched. Duplicates removed, formats fixed, and the John Smith who booked on your site recognised as the J. Smith who left the review.
The dining room
The finished dish. Clean tables that answer real questions: how many guests came back, what a direct booker is worth against an OTA guest, who has not visited in six months.
Start simple, add later
Booking data and email first. That alone will tell you more about your guests than you have ever known. Marketing, feedback and prediction come after.
What we believe
Bad Data in a Pretty Dashboard Is Still Bad Data.
What changes
What changes when it's in one place
The questions stop being projects and start being queries.
One number, in every meeting.
History that stops vanishing after fourteen months.
The monthly report assembles itself.
Cross-system questions become a query, not a fortnight.
Your AI finally has something true to work from.
Before you ask
Questions we get asked
No. A dashboard is what you see. This is the layer underneath it, which decides whether what you see is true. Keep whatever dashboards you already like and point them at this instead.
Nothing. We connect to the systems you already run. The warehouse sits alongside your stack rather than in place of any part of it.
You do. Each client gets an isolated environment with its own permissions, and it can sit on our infrastructure or on yours.
Less than people expect. Warehousing is charged by data volume rather than by seat, so for a small or medium group the infrastructure is a modest monthly figure. The cost is in the connecting and the modelling, not the storage.
Booking data and your email platform. Not dashboards. Get the data right first, because a pretty dashboard built on bad data is still bad data, and now it is also convincing.
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