AI Concierge + Operations Stack for a Tour Company
The Bottleneck
A regional tour and experiences company was still running its entire booking operation on a decades-old MS Access database and manual email. Every itinerary question, availability check, and follow-up went through a small front-desk team typing responses by hand, often after hours when travelers were actually browsing and booking. Corporate and group inquiries — the highest-value bookings — got the same generic reply as a single traveler asking about departure times, so promising group leads sat in the same queue as routine questions. The Access database lived on a single desktop machine, was not accessible remotely, and had no real backup strategy.
The Custom Architecture
We rebuilt the operator's front-of-house and back-office systems as one connected stack instead of patching the old one.
A conversational agent trained on the company's actual tours, packages, and policies answers itinerary and booking questions directly on the website, day or night, and hands off to a human the moment a question falls outside its scope.
Every inquiry that doesn't convert immediately now enters a scheduled follow-up sequence instead of falling out of an inbox, so leads get a second and third touch without anyone having to remember to send them.
We migrated the operator's entire booking history and tour catalog out of MS Access into a managed PostgreSQL database on Supabase, giving the team a single, remotely accessible source of truth with real backups for the first time.
A dedicated intake flow asks group and corporate inquiries the questions that actually matter — group size, dates, budget — and routes qualified leads straight to the sales team instead of the general inbox.
The Operational Impact
The operator now has round-the-clock coverage for the questions that used to wait until business hours, a booking database that no longer lives on one machine, and a group-sales pipeline that surfaces its best leads instead of burying them in general inquiries. The team is still tracking exactly how many admin hours the new stack is saving week to week — we'll update this case study with the confirmed number once we have a full reporting cycle behind it.
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