AI for travel agencies
AI workflows for travel agencies
A travel agency carries a long chain of small, repeatable tasks between the first enquiry and the trip itself. We set up tested workflows around that chain, give your team practical lessons to use them and keep people in charge of what goes out.
The repetitive work a travel agency carries
Tasks like these come back every week. They are good candidates for a tested workflow with a person checking the result.
Building itineraries
Turning dates and destinations into a day-by-day itinerary in the agency’s own journey spreadsheet.
Partner requests and follow-ups
Writing availability requests to accommodation, transfer and activity partners, then following up the ones that have gone quiet.
Rates and budgets
Looking up partner rates and checking the priced journey against the guest’s stated budget.
Proposals and pre-departure messages
Preparing the guest proposal, the details needed to raise the invoice and the messages that go out before departure.
What we set up
A workspace for your business
Your context, your trusted sources and instructions for repeatable tasks, organised in one place your team can edit.
Starter workflows
Two agreed workflows to begin with, such as partner availability requests and a budget check against the guest’s stated budget.
Self-guided lessons
Practical lessons inside the workspace, so your team can practise on real tasks, check the output and learn when to ask for help.
Human approval
Each workflow has a named person who checks the result before anything is sent or acted on.
Where we’ve done this
Client example · Travel agency
Journey workflows, with the team sending everything
A travel agency that plans multi-stop journeys for its guests wanted help with the work between enquiry and departure. We set up a workspace around its journey process. It covers building itineraries, looking up partner rates, checking a journey against the guest’s budget, drafting partner availability requests and follow-ups, and preparing proposals and pre-departure messages.
Emails are created as drafts. The team reads, edits and sends them. Some steps in the journey are still done by hand.
We have also built a reporting dashboard for a travel business. It is one of the examples on the home page.
This describes what was built, not measured results.
How it works
A defined scope makes the result easier to assess and the handover easier to run.
- Map. Choose the workflow, authoritative inputs, responsible people and desired outcome.
- Define. Agree systems, access, approval points, exclusions and acceptance criteria.
- Build & check. Tailor the workspace and test normal work, missing information and the agreed failure cases.
- Hand over & adopt. Give a brief orientation, leave practical lessons and record acceptance. Adoption support stays within the agreed scope.
Setup options
Choose one option. Fees are confirmed after your discovery call, and your proposal confirms one total for the agreed package.
Foundation
Your first repository, set up and connected, with two agreed workflows operated by your team, practical lessons and a tested handover.
Connected
Four agreed workflows in total, connected to the supported systems, with input and output checks and approval steps.
Operations
Six agreed workflows in total, with scheduling, queues and human approvals where feasible. Feasibility is assessed first.
Questions
Will the workflows email guests or partners by themselves?
Can AI get supplier details or rates wrong?
Does this work with our email and spreadsheets?
How is guest information handled?
Start with the work.
Email Don with a repeatable task that slows your agency down. We’ll discuss a useful first workflow and a scope you can assess before you commit.