Bookings, documents, conversations and settlement were scattered across channels. We built mid- to long-term housing operations into a single platform, and on top of it the system reads conversations every day to find bookings whose real arrival date differs from the registered one. A person still applies them.
The registered check-in date was derived from the school term — it was not the real arrival date. The real arrival information lived only inside chats held in several languages, so a manager had to read every conversation, every day. Contracts, proof-of-residence letters and receipts were produced by hand, and bookings arriving through outside platforms — along with pre-existing customers — sat outside the system entirely.
* A real engagement, anonymized with client consent. We don't publish figures about a client's operating scale.
The domain was housing, but the prescription is domain-agnostic. If your operations are scattered across chats, sheets and paper — with 'nowhere for AI to enter' —
| Common situation in your company | What this case prescribes |
|---|---|
| Orders, bookings and support scattered across chat, calls and sheets | Operationalize into one platform first — machine-readable |
| When a key person leaves, the knowledge leaves with them | Accrue pricing, norms and history as the company's work language → the company owns it |
| Revenue only grows if headcount grows | Machine handles what it can, people only the rest — a non-linear shift |
| You 'adopted AI' but there's no data for it to enter | Make operations readable first, then put it on top |
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