Travel & Hospitality

The inventory changed while you were checking out

Travel is a distributed systems problem wearing a consumer interface. Prices move, availability disappears mid-transaction, and a supplier times out at the worst possible moment. Almost everything else in the product is downstream of handling that well.

8+
Years building software
500+
Projects delivered
350+
Clients served
What we build for travel

Booking systems that stay correct under churn

Availability and price are stale the moment you read them, and a booking touches several systems that can each fail independently. Design for that first and the rest of the product gets much simpler.

Search and availability

Multi-supplier search that stays fast when every query fans out to a dozen upstreams. Caching with honest freshness rules, timeouts that degrade to partial results, and a price you can still honour at checkout.

Booking correctness

Taking the money is not the hard part. The state machine after it is: holds, confirmations, timeouts, and the reversal path when leg three fails after legs one and two have already confirmed.

Supplier, GDS and channel integrations

Amadeus, Sabre, Travelport, bed banks, channel managers, property and car systems, and the direct supplier whose API documentation is a spreadsheet. Normalising them into one model is most of the engagement.

Itinerary and package complexity

Multi-city, multi-passenger, multi-supplier trips with changes, cancellations and partial refunds applied correctly. The data model here decides how painful the following three years are.

Pricing, rules and seasonality

Rate plans, markups, promotions, currency, taxes and market-specific fees expressed as rules your commercial team can change without waiting for a release.

Agents for trip search and service

Natural-language search over your real inventory, plus agents handling changes, cancellations and booking status against live systems and your actual fare rules rather than a generic policy summary.

What we engineer for

The failure modes that cost you

Look-to-book that holds

Search infrastructure sized for the traffic that never books, because most of it never does. Cheap searches are what make the conversions affordable.

No orphaned bookings

Every multi-step booking either completes or unwinds cleanly, with reconciliation catching the cases where a supplier confirmed and your system never heard about it.

Seasonal peaks without permanent cost

Autoscaling and caching tuned to your own demand curve, so high season holds up and the quiet months do not bill like it.

Service load absorbed

Changes, cancellations and status questions handled by agents with real access to the booking and the fare rules, escalating anything involving a fee exception or a stranded traveller.

How we start

Model the mess before the interface

01

Map suppliers and states

Every upstream, its quirks, its timeout behaviour under load, and the full state machine a booking can pass through. Travel projects go wrong here or they mostly do not go wrong.

02

Build the spine first

Search, availability, booking and reversal, tested against supplier sandboxes and deliberately induced failures. The interface follows once the layer underneath is trustworthy.

03

Launch clear of peak

Load tested against your own seasonal high, with cutover scheduled well away from it and a rollback available. Nobody should be replatforming a booking engine three weeks before high season.

Stack

What we build with

Distribution
AmadeusSabreTravelportNDCBed banksChannel managers
Backend
Node.jsJavaPythonGoPostgreSQLElasticsearch
Scale & resilience
RedisKafkaTemporalCircuit breakersEdge caching
Product
Next.jsReactReact NativeFlutterTypeScript
Platform
AWSGCPKubernetesTerraformObservability
FAQ

Questions travel buyers ask

Usually a combination: parallel fan-out with per-supplier timeouts, returning partial results instead of waiting for the slowest upstream, caching availability against a freshness policy you have actually decided on, and pre-warming the routes and dates people search most. Adding hardware is the least effective item on that list and the one most often tried first.
Treat the booking as a durable workflow rather than a request. Each step is idempotent and recorded, failures trigger a defined compensating action, and a reconciliation process compares your records against supplier records to catch the ones that slipped through anyway. Some always do, the point is finding them before the traveller does.
Almost certainly, including the ones with thin documentation and XML from another era. Certification timelines and sandbox access are usually the schedule risk rather than the code itself, so we start those in week one rather than discovering them in month three.
You decide the policy and we implement it consistently: reprice at checkout, honour a held quote for a fixed window, or absorb small deltas within a threshold. What generates complaints is rarely the repricing itself, it is doing it inconsistently, or telling the customer too late in the flow.
Trip discovery in natural language over your own inventory, and post-booking service, changes, cancellations, status, where the agent can read the booking and the fare rules. Anything involving a fee waiver, a stranded passenger or a supplier exception should reach a human, and we build that handoff deliberately.

Booking system creaking under its suppliers?

Tell us the suppliers, the volumes and where it hurts most. We will come back with an honest read on whether it needs fixing, extending or replacing.

Talk to a travel engineer

Reviews

Clutch
5.0
Upwork
5.0
Google
5.0
Freelancer
5.0