01 / Customer question
The commercial context
A new booking channel needs a clear commercial case.
AI can influence destination choice, itinerary planning and booking. It can also introduce another intermediary between the traveller and the brand. A useful channel needs accurate offers and a clear view of distribution costs, loyalty and the customer relationship.
Hotels, airlines and travel intermediaries have different inventory and fulfilment systems. We assess property, route and condition accuracy alongside the dependencies for a suitable booking integration. Post-booking service, changes and refunds are part of the journey, not an afterthought.
Customer journeys
Follow planning, comparison and booking decisions.
We build the assessment around specific questions, audiences and markets. These examples show the kinds of journeys we can examine; the final scope follows your priorities.
02 / Customer question
Does an itinerary or fare comparison preserve baggage, conditions and current availability?
03 / Customer question
Can a booking route recognise the correct offer, loyalty/account permissions and change/refund rules?
How SWLR can help
Connect travel information with distribution readiness.
01
Journey and offer evaluation
We evaluate planning and comparison questions against property, route and offer references. The findings identify missing amenities, inaccurate fare conditions and other material information gaps across the selected channels.
You receive: Discovery and offer-accuracy baseline.
02
Data and distribution planning
We reconcile relevant travel information and assess hotel distribution or airline offer dependencies. NDC and Offers and Orders are considered where applicable, rather than applying a product-shopping integration to every travel business.
You receive: Data priorities and booking-integration options.
03
Booking and commercial pilots
We scope booking permissions, loyalty recognition, changes and refunds with distribution and service teams. A pilot measures completion and net channel value, with cancellation and distribution costs included.
You receive: Evaluated booking pilot and net-channel-value measurement.
Internal AI readiness
Prepare guest and passenger workflows for reliable service.
Guest and passenger teams need applicable reservation and service knowledge. We assess approved disruption information, account permissions, system dependencies and the hand-off process for questions requiring a person.
An assistant's ability to explain conditions is distinct from permission to change a booking or issue a refund. The workflow plan names owners and evaluation criteria. Customer-service use is also separated from safety-critical aviation or other operational decisions.
A practical first engagement
Travel AI Discovery & Booking Assessment
We choose brands, properties or routes, markets, audiences, offer conditions and distribution channels. You receive discovery and data findings, channel-economics questions, booking and service dependencies, and a roadmap with suitable integration or knowledge-assistance pilot options.
01
Agree the scope
We define the business questions, references, AI surfaces and teams involved. Access requirements and dependencies are agreed before the assessment begins.
02
Review the evidence together
Findings distinguish observed answer behaviour from the underlying content, data or workflow issue. Your teams help establish which changes are material and feasible.
03
Choose the next action
The roadmap sets out priorities, owners, dependencies and validation. Where a pilot makes sense, we scope the implementation and evaluation work with the relevant teams.
Evaluation
Measure the changes that matter.
We agree the criteria before making changes. Answer samples are recorded with their questions, market, surface and date. Repeat checks help show patterns within that scope; commercial outcomes and internal workflow gains need their own evaluation with your teams.
Property and fare accuracy
Availability freshness
Booking and service task completion
Net channel revenue
Part of Ayima
Technical search expertise. Practical enterprise thinking.
SWLR brings an AI visibility and readiness remit to Ayima's enterprise search background. We connect the business question to the content, data, access and technical work behind it, then help teams prioritise the next steps.
Common questions
Before we begin.
Will AI increase direct bookings?
That is a commercial question to test. We assess discovery and booking routes, then measure channel contribution after distribution costs, cancellations and refunds. An AI recommendation alone does not establish incremental direct revenue.
How is airline readiness different from hotel readiness?
Airlines have route, fare-family, ancillary and offer/order dependencies. Hotels have property, room, rate-plan and reservation/distribution information. The assessment and integration options follow those systems and actual service conditions.
Can agents change or refund bookings?
Only within an explicitly authorised scope. Applicable conditions, customer/account permissions, records and review must be defined. We assess a controlled task and its failure or escalation paths before recommending wider use.
Signal → Evidence → Action
Start with the questions that matter.
Discuss your properties, routes, markets and the distribution or service journeys that matter.