The Reality
Where Travel Platforms
Usually Start Breaking
Most travel platforms don't fail dramatically. They degrade. Integration reliability drops quietly. Post-booking operations grow manual. Release cycles stretch. By the time the architecture is visibly a problem, the cost of fixing it is much higher than it needed to be.
Supplier integrations that break without warning
GDS and OTA connectivity that works in staging but behaves differently at volume. When a supplier pushes a schema change, you find out from a customer complaint, not a monitor.
Booking flows that collapse under peak demand
A platform designed for 500 daily bookings doesn't scale linearly. At 5,000, queues pile up, timeouts compound, and fixes become progressively manual.
Pricing and availability that doesn't match reality
Rate parity breaks silently. A customer books a room that's already sold. A fare on screen doesn't match what the GDS confirms. These aren't UX issues - they're revenue and trust problems.
Legacy monoliths blocking every release
One change to the booking engine touches seven other components. Release cycles stretch to weeks. Engineers spend more time on archaeology than on product.
Post-booking operations that depend on people
Amendments, cancellations, voucher generation, and supplier confirmations handled through spreadsheets and manual follow-up. It scales until it doesn't.
No real visibility across third-party systems
You know a booking failed. You don't know at which integration layer, which supplier, or how often it happens. Root cause analysis takes days.
Reconciliation that never quite closes
Commission calculations, net vs gross rate mismatches, and refund tracking that requires hours of manual cross-referencing every week.
New channel onboarding takes months
Adding a new OTA or supplier means months of bespoke integration work. Each new connection is another load-bearing custom build with no shared contract.
Margin erosion from uncontrolled rate logic
Markup rules hardcoded in five different places. Net vs gross rate handling inconsistent across suppliers. Promotional overrides applied incorrectly. Revenue leaks compound quietly until finance raises a flag months later.
Content that goes stale faster than anyone tracks
Hotel names, room descriptions, policies, and cancellation terms not refreshed since integration. Customers see inaccurate content; complaints spike during high-demand periods because content management was treated as a one-off, not a platform capability.
Data that only answers yesterday's questions
Revenue sitting in booking system exports. Supplier performance metrics extracted weekly. Conversion funnel reporting that requires an analyst. When data isn't flowing automatically, business decisions lag the market by days.
Single supplier dependency with no fallback
One GDS contract or one aggregator as the only source for hotel inventory. When that supplier degrades or terminates, there's no backup. Supplier diversification isn't exciting to architect - until it's the only thing keeping your platform running.
Advisory Areas
What I Help Travel
Businesses Solve
Travel Platform Strategy & Architecture
From single booking flows to multi-supplier distribution networks - designing the right architecture for your stage, your team, and where you're going.
Booking Engine Design & Modernization
Auditing and rearchitecting booking engines that have grown brittle. Separating availability, pricing, and booking concerns properly. Improving reliability and reducing latency.
OTA, GDS & Supplier Integration Architecture
Defining how your platform connects to Amadeus, Sabre, Travelport, Expedia, Booking.com, or direct hotel/airline feeds. Integration patterns that are maintainable, observable, and resilient.
Hotel Distribution Platform Design
CRS design, channel manager connectivity, PMS integration, and rate/inventory synchronization architectures for hospitality-focused platforms.
Legacy-to-Microservices Transformation
Staged decomposition of monolithic travel stacks into services that can be deployed, scaled, and failed independently - without disrupting live bookings during the migration.
Scalability, Resilience & Observability
Designing for demand peaks, supplier timeouts, and partial failures. Ensuring your platform degrades gracefully and recovers automatically rather than requiring manual intervention.
API Strategy & Integration Governance
Internal API contracts, versioning, throttling, consumer management, and the integration governance that stops every new connection from becoming a unique snowflake.
Engineering Leadership for Travel Teams
Working with founders, CTOs, and engineering leads to build the processes, standards, and team structures that allow travel engineering to move fast without breaking distribution.
Post-Booking Automation & Ops Design
Designing amendment, cancellation, reconciliation, and voucher workflows that execute automatically - eliminating the ops burden that scales linearly with every new booking and every new supplier added to the platform.
B2B API Product Development
Building the distribution API your agents and affiliates connect to - authentication, rate limits, margin control, per-consumer usage analytics, and the governance model that prevents bespoke per-client integrations from accumulating into unmaintainable custom code.
Content & Catalog Architecture
Property content management, room type normalisation, policy extraction, and the data architecture that keeps your catalog accurate at scale without manual per-listing intervention. Particularly relevant for OTA backends and hospitality SaaS platforms managing content at volume.
Revenue & Pricing Architecture
Centralising markup, margin, and dynamic pricing logic into a single engine. Eliminating inconsistencies across channels, supplier types, and markets. Building the foundation for data-driven revenue management rather than ad hoc rate overrides.
Architecture Depth
Inside a Booking Engine
That Actually Holds Up
Most booking engine problems share the same root cause: availability, pricing, and booking confirmation are treated as a single responsibility when they have fundamentally different failure modes, latency characteristics, and data sources.
A booking engine that scales and recovers under supplier pressure looks very different from one that started as an MVP and had features bolted on for five years. Here's what the right architecture looks like at each layer.
01
Search & Availability Layer
Availability queries should never hit suppliers synchronously in a search-per-keystroke flow. Cache aggressively - hotel availability with short TTLs, flight availability with near-real-time refresh. Rate-limit supplier calls here, not in business logic. Every supplier gets its own adapter; none of them get to own your data model.
02
Rate & Pricing Engine
Pricing logic is where complexity accumulates fastest. Net vs gross rates, markup rules, contracted rates, promotional overrides, and multi-currency conversion all need a single authoritative engine. When pricing lives across five codepaths, rate parity breaks at peak and you find out from the OTA, not your own monitors.
03
Shopping Cart & Itinerary Hold
Holding a quote while the user completes booking details is a timed operation against supplier inventory. Most platforms handle this poorly - locking inventory too aggressively (supplier friction) or too loosely (double bookings). The cart layer needs explicit TTL management, soft-hold vs hard-book transitions, and multi-component trip handling.
04
Booking Confirmation Flow
Confirmation is the only step where you can't retry transparently. A payment may have processed even if the API timed out. This layer needs idempotency keys, supplier confirmation number tracking, and a reconciliation queue for confirmations that didn't return cleanly. "We'll confirm shortly" is a valid choice - but it must be backed by automation, not an ops agent.
05
Supplier Abstraction Layer
Every supplier integration should implement a shared contract - search, price, book, cancel, amend - and never expose its quirks to the booking engine. Supplier-specific normalisation, retry logic, timeout handling, and circuit breakers live inside each adapter. When Amadeus changes a field, you fix one file, not six codepaths.
06
Post-Booking State Machine
A booking isn't done at confirmation. It has states: confirmed, on-request, amended, cancelled, partially-refunded, expired. That machine needs to be explicit - transitions logged, supplier side-effects decoupled via events, finance systems updated consistently. When it lives in if/else chains, operations teams end up managing state manually.
Domain Knowledge
Travel Systems I Understand
Beyond the Surface
These aren't topics I've read about. They're systems I've had to make decisions on under delivery pressure, with real booking volumes, real supplier contracts, and real business consequences.
Booking & Distribution
Hotel Booking Engines
Flight Booking Systems
Rail & Coach Booking
Car Rental Platforms
Sightseeing & Activities
Cruise & Liveaboard Systems
B2B Agent Portals
B2C Consumer Journeys
GDS & Supplier Connectivity
GDS - Amadeus (Full Suite)
GDS - Sabre (Full Suite)
GDS - Travelport / Galileo
GDS Search, Book, Cancel, Ticketing
NDC / Airline Direct XML Feeds
Direct Hotel Connects
Aggregator Platform APIs
Supplier API Normalisation
Channel Manager & PMS Integrations
Channel Manager Integrations (SiteMinder, Staah, RateGain)
PMS - Opera (Full Integration)
PMS - Cloudbeds
PMS - IDS / HMS
CRS (Central Reservation Systems)
Rate & Inventory Synchronization
Availability Push / Pull Architecture
Multi-Property Distribution
OTA & Travel Aggregators
Booking.com API
Expedia / Hotels.com
Agoda / AirBnB Connectivity
MakeMyTrip / Goibibo
Travel Aggregator APIs (TBO, Hotelbeds, Juniper)
Bed Bank Integrations
Multi-OTA Feed Management
Parity Monitoring Architecture
Tour Operators & Own API Distribution
Tour Operator Platform Integrations
DMC (Destination Management Company) Connectivity
B2B Wholesaler API Feeds
White-Label Distribution APIs
Own API Product Development
B2B API Gateway Design
XML / REST API for Distribution
Agent Booking Portal APIs
Affiliate & Reseller API Architecture
Platform Systems
Dynamic Pricing Engines
Inventory & Rate Management
Availability Synchronization
Markup & Margin Engine
Multi-Currency / Multi-Language
Operations & Finance
Post-Booking Workflows
Amendment & Cancellation Flows
Voucher & Confirmation Systems
Reconciliation & Commission Tracking
Supplier Invoicing
Finance Integration
Industry Coverage
Travel Segments I've
Worked Inside
Not every vertical in travel has the same system complexity. Each has its own supplier contracts, availability model, post-booking workflow, and margin structure. Here's where I have direct, operational experience - not just familiarity.
Hotels & Hospitality
Hotel booking engines, channel manager connectivity (SiteMinder, Staah, RateGain), PMS integration (Opera, Cloudbeds), CRS architecture, rate/inventory sync, and multi-property distribution. Deep experience with direct connects, OTA parity management, and property-level rate structures. From boutique hotel tech to chain-scale systems.
Flights & Airlines
GDS flight search, book, cancel, ticketing, and post-ticketing workflows across Amadeus, Sabre, and Travelport full suite. NDC integration, airline direct API connectivity, baggage and seat selection handling, fare rule processing, and post-issuance operations - void, refund, exchange, and reissue.
Rail & Coach
Rail booking APIs, seat reservation systems, and dynamic pricing engines for coach and intercity travel. Integrating rail inventory into multi-modal travel platforms where the booking model, confirmation flow, and post-trip amendment rules are fundamentally different from hotel or air.
Car Rental
Car rental supplier integrations, fleet availability APIs, rate comparison, and the specific data models around rental agreements, insurance options, and drop-off location management. Integration with aggregators (Cartrawler, EasyTerra) and direct supplier connectivity for large fleet operators.
Sightseeing & Activities
Tour and activity booking platforms, attraction ticketing, experience aggregator APIs, and the operational complexity of time-slot-based inventory. Integration with suppliers like Viator, GetYourGuide, and direct operators for city tours, day trips, and destination experiences at scale.
Cruise & Liveaboard
Cruise cabin inventory, itinerary management, liveaboard booking systems, and the post-booking complexity around supplements, cabin upgrades, shore excursions, and multi-leg voyages. Direct operator integration and aggregator connectivity for dive travel and Indian Ocean liveaboard operators.
B2B Agent & Wholesale
Wholesale platforms, B2B agent portals, sub-agent commission management, credit limit enforcement, and the distribution architecture that allows resellers to access contracted inventory without exposing your full margin structure. XML/REST API feeds for B2B aggregators and wholesale distribution.
B2C Consumer Platforms
Consumer-facing booking journeys, search-to-checkout architecture, abandonment recovery, dynamic packaging, and the scaling challenges that emerge when consumer volume is orders of magnitude higher than B2B. Payment gateway integration across multiple currencies and markets - India, UAE, and international.
Modernization
Modernising Travel Platforms
Without Disrupting Revenue
The core challenge in travel platform modernization isn't the rewrite - it's migrating while continuing to process bookings. Most travel teams don't have the luxury of a clean break.
My approach starts at the boundaries. Identify which integration points are the most fragile, the most expensive to maintain, or the biggest blockers to product velocity. Decompose those first. Build the new service alongside the old one, validate, then cut over.
The goal isn't microservices for their own sake. It's a platform your team can deploy independently, monitor clearly, and extend without fear.
- Supplier integrations become independently deployable
- New channel onboarding drops from months to weeks
- Availability, pricing, and booking are properly separated
- Release cycles shorten because changes are scoped
- Incidents become faster to diagnose and isolate
- Platform handles demand spikes without manual intervention
- Engineering team spends time on product, not on archaeology
Integration Architecture
Supplier Integration Patterns
That Don't Become Technical Debt
Every travel platform eventually has the same conversation: "we need to add another supplier, but our last three integrations have become maintenance nightmares." The root cause is almost always the same - each connection was built as a custom one-off rather than an implementation of a shared contract.
Pattern 01
Supplier Abstraction Layer
Define a canonical interface - search, price, book, cancel, amend - and implement it per supplier. Your booking engine talks only to the interface. Supplier-specific quirks (different field names, async vs sync confirmation, XML vs JSON response shapes) are handled inside each adapter, never in core booking logic.
Pattern 02
Response Normalisation
Every supplier returns availability and booking data in a different schema. Normalisation converts supplier responses into your internal data model at the integration boundary. Downstream services never parse supplier-specific formats. When Amadeus changes a field name, you fix one mapper - not every service that consumes that data.
Pattern 03
Circuit Breakers & Graceful Degradation
Suppliers go down. GDS connections timeout. Direct hotel APIs return 503s during peak season. Circuit breakers prevent a single degraded supplier from cascading into total booking engine failure. When a supplier is struggling, requests fail fast rather than queuing and blocking the entire system.
Pattern 04
Asynchronous Confirmation Handling
Some suppliers - particularly PMS systems and on-request hotel inventory - don't confirm immediately. Async confirmation handling means: accept the booking, queue the confirmation request, poll or receive webhook callbacks, and update booking state automatically. No manual ops agent checking supplier extranets every 20 minutes.
Pattern 05
Rate Throttling & Quota Management
GDS systems charge per search and carry contractual rate limits. Unconstrained availability queries during high traffic burn supplier credit and trigger circuit breakers on the GDS side. Rate throttling at the integration layer, combined with availability caching, keeps costs predictable and supplier connections stable under load.
Pattern 06
Per-Supplier Observability
You can't debug supplier issues without per-supplier metrics. Track response times, error rates, timeout rates, and booking completion rates separately for each supplier. When a GDS degradation starts affecting booking completion, you want to know from a monitor - not from a customer complaint the next morning.
Connectivity Architecture
Channel Managers, OTAs, PMS
& Aggregator Integrations
Travel connectivity complexity comes from the sheer number of systems that need to stay in sync - and the fact that each one uses a different protocol, data model, and availability push mechanism. Channel managers push via XML. OTAs pull via REST. GDS systems use legacy XML over HTTPS. PMS systems often have both push and pull modes depending on the version. The architecture that scales is one that normalises at the boundary and exposes a single contract inward.
Channel Managers
SiteMinderStaahRateGainMyAllocatorCloudbeds CMeZee
Channel managers sit between the PMS and all distribution channels - pushing rates and availability outward, pulling bookings inward. SiteMinder and Staah dominate India and Southeast Asia for hotel distribution. RateGain adds revenue management on top. The integration challenge is that channel managers use their own availability model (allotment pools, stop-sell flags) which must be mapped to your CRS model without drift. Availability push is typically XML over HTTPS; booking retrieval uses REST or XML pull depending on the channel manager's API version.
PMS Systems
Opera PMSCloudbedsIDS / HMSProtelMewsLittle Hotelier
PMS integration is the deepest hotel tech integration - it's where reservations live, where check-in happens, and where rates are ultimately managed. Opera PMS (Oracle) is the enterprise standard; Cloudbeds and Mews dominate mid-market and tech-first properties. PMS API coverage varies: Opera has a mature XML API; Cloudbeds has REST. The integration must handle reservation creation, modification, cancellation, no-show, and check-out events - all of which affect your booking record and financial reconciliation.
OTAs & Distribution Channels
Booking.comExpedia / Hotels.comAgodaMakeMyTripGoibiboAirbnb
Direct OTA connectivity bypasses channel manager fees and gives more reliable rate and availability sync. Booking.com Connectivity API, Expedia Rapid API, and MakeMyTrip's seller API all have different rate models and inventory push mechanisms. The architecture challenge is managing rate parity across direct OTA connections, channel manager-mediated channels, and your own direct booking flow simultaneously - with each having slightly different processing latency and availability update frequency.
Bed Banks & Aggregators
HotelbedsTBO HolidaysJuniperGTA / KuoniTravcoW2M
Bed banks and wholesalers provide contracted hotel inventory to B2B buyers - travel agents, OTAs, and tour operators - at net rates. Hotelbeds is the global market leader; TBO dominates India's B2B market. Integration covers search, book, cancel, and voucher flows via XML or REST APIs. The key architectural decision is whether to cache aggregator inventory (for speed) or query live (for accuracy) - most platforms cache search results with a TTL and re-price at booking confirmation to balance latency and accuracy.
GDS & Airline Direct Connectivity
AmadeusSabreTravelport / GalileoNDC APIsAirline Direct XML
GDS integration covers the full booking lifecycle - search, price, book, cancel, ticketing, and post-ticketing operations including void, refund, and exchange. Each GDS uses legacy XML (SOAP/OTA/edifact) with distinct session management and rate limits. NDC (New Distribution Capability) APIs are REST-based and expose fare families, ancillary services, and seat maps that legacy GDS doesn't surface well. Direct airline connectivity (IndiGo, Air India, Emirates direct APIs) bypasses GDS fees for high-volume routes but requires separate integration and maintenance per airline.
B2B Distribution & White-Label APIs
B2B Agent PortalWhite-Label APISub-Agent NetworksXML / REST Feed
Building your own B2B distribution API allows travel agents, corporates, and affiliates to access your inventory programmatically - without going through a bed bank that takes margin. The API must handle authentication (OAuth/API key per sub-agent), rate limits, margin control (different markup rules per agent tier), and per-consumer usage analytics. The common failure mode is building bespoke integrations per B2B client rather than a single governed API that all B2B consumers implement against.
Integration Coverage
Are You Looking For
Integrations?
From bed banks and channel managers to OTAs, PMS, GDS, and supplier systems - these are the platforms and APIs with direct integration experience across connectivity architecture, booking flows, and data synchronisation.
Bed Banks & Aggregators
Hotelbeds
WebBeds
TBO Holidays
Juniper
GTA (Kuoni)
Travco
W2M
Stuba
Bedsonline
HotelsPro
DOTW
Restel
Bonotel
Tourico
Agoda B2B
Expedia Partner Solutions
MakeMyTrip B2B
Yatra B2B
Rakuten Travel
Global Hotel Exchange
HotelbedsWebBedsTBO HolidaysJuniperGTA (Kuoni)TravcoW2MStubaBedsonlineHotelsProDOTWRestelBonotelTouricoAgoda B2BExpedia Partner SolutionsMakeMyTrip B2BYatra B2BRakuten TravelGlobal Hotel Exchange
Channel Managers
SiteMinder
STAAH
RateGain
Cloudbeds CM
eZee Centrix
AxisRooms
RateTiger
MyAllocator
D-EDGE
TravelClick
Availpro
HotelRunner
Rentals United
Lodgify
SmartHotel360
Octorate
YieldPlanet
CultSwitch
BookingFactory
SiteMinderSTAAHRateGainCloudbeds CMeZee CentrixAxisRoomsRateTigerMyAllocatorD-EDGETravelClickAvailproHotelRunnerRentals UnitedLodgifySmartHotel360OctorateYieldPlanetCultSwitchBookingFactory
Online Travel Agencies (OTAs)
Booking.comExpedia
AirbnbAgodaMakeMyTrip
Goibibo
Hotels.com
Trip.comYatra
Cleartrip
EaseMyTrip
ixigo
TripAdvisor
Vrbo
Trivago
Kayak
HappyEasyGo
Paytm Travel
Thomas Cook
Cox & Kings
Booking.comExpediaAirbnbAgodaMakeMyTripGoibiboHotels.comTrip.comYatraCleartripEaseMyTripixigoTripAdvisorVrboTrivagoKayakHappyEasyGoPaytm TravelThomas CookCox & Kings
Supplier & PMS Systems
Opera Cloud (Oracle)Cloudbeds PMS
Mews
Protel Air
Little Hotelier
IDS Next
HotelogixeZee FrontDesk
RoomRaccoon
Agilysys
Guestline
Shiji
Infor HMS
StayNTouch
Maestro PMS
Clock PMS+
WebRezPro
Checkfront
Preno PMS
Sirvoy
Opera Cloud (Oracle)Cloudbeds PMSMewsProtel AirLittle HotelierIDS NextHotelogixeZee FrontDeskRoomRaccoonAgilysysGuestlineShijiInfor HMSStayNTouchMaestro PMSClock PMS+WebRezProCheckfrontPreno PMSSirvoy
GDS & Other Systems
Amadeus GDS
Sabre GDS
TravelportGalileoWorldspanApollo GDS
IATA NDC
IBS Software
Navitaire
Radixx
SilverRail
SITA
OpenJaw
Farelogix
AeroCRS
Hahn Air
Pegasus CRS
Travelsky
Trust International
Worldline Travel
Amadeus GDSSabre GDSTravelportGalileoWorldspanApollo GDSIATA NDCIBS SoftwareNavitaireRadixxSilverRailSITAOpenJawFarelogixAeroCRSHahn AirPegasus CRSTravelskyTrust InternationalWorldline Travel
Enterprise Architecture
Scaling Connectivity Across
Every System at Enterprise Level
A travel platform that connects 3 suppliers operates very differently from one that connects 30. The integration patterns that work at small scale - one adapter per supplier, synchronous responses, no rate management - fail at enterprise scale. Here's the architecture that keeps connectivity reliable when the number of suppliers, channels, and booking volumes multiply.
01
Unified Supplier Abstraction Layer
Every external system - GDS, channel manager, PMS, OTA, aggregator, or direct hotel API - connects through a supplier adapter that implements a single shared contract: search, price, book, cancel, amend. The booking engine never knows which supplier it's talking to. Schema normalisation, protocol translation (XML→JSON), and supplier-specific retry logic are inside the adapter. When a supplier changes their API, you fix one adapter, not the booking engine or any downstream service.
02
Multi-Layer Caching & Rate Management
At enterprise scale, querying suppliers live for every search is untenable. GDS charges per query. Channel managers have rate limits. PMS systems are not built for high-frequency polling. The caching strategy has multiple layers: a short-TTL availability cache (Redis) for search results, a longer-TTL content cache (property details, room types, policies) for catalog data, and session-based pre-fetching for checkout flows. Rate throttling per supplier prevents quota breaches under peak traffic.
03
Event-Driven Distribution Architecture
Rate and availability changes should propagate via events, not synchronous polling. When a channel manager pushes a rate update, an event is published to a message queue. Downstream services - OTA feeds, B2B API, direct booking engine - consume that event and update their local read models. This decouples the update latency from the query latency: search is always fast (reads local cache) and updates are eventually consistent (events propagate asynchronously without blocking the search path).
04
Multi-Channel API Gateway
A single API gateway enforces authentication, rate limits, and margin rules across all distribution channels - B2B agents, OTAs, direct consumer, and internal services. Each channel gets its own API key or OAuth client with channel-specific rate limits, markup rules, and response shaping. The gateway is also the observability chokepoint: per-channel request volumes, error rates, and latency percentiles are all measured here. Adding a new distribution channel means onboarding a new API consumer, not building a new integration.
05
Cross-System Observability & SLA Monitoring
Enterprise-scale travel connectivity requires per-supplier, per-channel, per-booking-type observability. Search response time by supplier. Booking confirmation rate by channel. NDR / failed booking rate by OTA. Reconciliation discrepancy rate by period. Each metric has a defined alert threshold. When Amadeus response times start climbing, or when Booking.com booking confirmations drop below expected rates, monitoring detects it before customers do - not after a spike in complaint volume.
06
Failover, Fallback & Graceful Degradation
Enterprise connectivity means accepting that any supplier will degrade or go offline. Circuit breakers prevent a single supplier failure from cascading. Fallback logic routes to alternative inventory sources when a primary supplier is unavailable. For GDS failures, cache-served results are displayed with freshness indicators. For channel manager outages, the last-known availability is served rather than returning zero results. The platform degrades gracefully - showing less-than-perfect results - rather than failing completely for end users.
AI Innovation & Development
Where AI Actually Helps
Travel Platforms
AI in travel has genuine applications - and a lot of hype that doesn't survive contact with real booking data. The use cases that work are grounded in the data travel platforms already have: booking history, search behaviour, supplier performance, and content at scale. Here's where I advise on AI development and implementation.
Customer Support Copilot
Handling amendment, cancellation, and itinerary queries without routing everything to a human agent. RAG-based, grounded in your own booking and policy data - not hallucinating supplier policies.
Internal Operations Assistant
Ops teams querying booking status, supplier confirmations, and reconciliation exceptions using natural language - rather than running manual reports across disconnected systems.
AI Travel Recommendation Engine
Personalised destination, hotel, and package suggestions powered by traveler profile, search context, past booking history, and real-time inventory. Moving beyond rule-based upsell logic to ML-driven recommendations that adapt to each traveler's intent signals.
AI Revenue & Yield Management
Dynamic pricing powered by demand signals, competitor rate monitoring, booking pace data, and historical sell-through patterns. Building the AI layer on top of your pricing engine that moves rates in response to real signals - not static markup rules.
Content & Catalog Enrichment
Automating hotel content normalisation, policy extraction, and destination descriptions using LLM workflows - reducing the manual cost of maintaining content at scale across hundreds of properties.
Supplier Anomaly Detection
Identifying patterns in supplier API behaviour, pricing drift, and availability discrepancies before they affect customer bookings. Useful where monitoring alone doesn't catch subtle drift in supplier data quality.
AI Travel Agent & Trip Planning
Conversational trip planning that understands traveler intent, queries live inventory, and assembles multi-component itineraries - flights, hotels, activities - grounded in real availability and pricing, not hypothetical plans.
AI Innovation & Product Development
Advisory on building AI-first travel products - from architectural decisions around GenAI integration, RAG pipeline design, and LLM evaluation frameworks, to product strategy for embedding AI into your core booking and operations platform.
Operational Depth
Post-Booking Is Where
Operations Get Expensive
Most travel platforms focus engineering effort on the search-to-book funnel. Post-booking is where operational cost quietly compounds. Amendments, cancellations, supplier re-confirmations, voucher management, and reconciliation - handled manually - consume more ops capacity than most founders expect until they're at scale.
Amendment Engine
Date changes, name corrections, room upgrades, and passenger amendments against live bookings. Each supplier has different amendment rules, charges, and API flows. An amendment engine handles these systematically - not case-by-case by an ops agent pulling up supplier extranets and manually updating records.
Cancellation Flows
Automated cancellation against supplier systems, cancellation charge calculation, refund initiation against payment gateways, and customer notification - executed as a coordinated transaction. When cancellations are manual, teams spend hours per booking on supplier extranets, particularly during disruption events when volume spikes overnight.
Voucher & Confirmation
Supplier confirmation numbers, hotel voucher generation, airline PNR management, and the full confirmation communication flow to customers. Automated reconciliation between what's confirmed in your booking system and what the supplier actually has on record - surfacing discrepancies before check-in, not at the property.
Deposit & Balance Tracking
Advance deposits, balance payment deadlines, supplier payment schedules, and auto-cancellation logic for unpaid balances. Particularly critical for tour operators and holiday packages where the payment schedule spans weeks and supplier due dates don't align with customer payment dates.
Reconciliation Engine
Commission calculations, net vs gross rate reconciliation, supplier invoicing, and matching what your system recorded against what the supplier invoiced. Manual reconciliation at any volume above a few hundred bookings per week becomes the blocker that prevents finance from closing the month on time.
Supplier Re-confirmation Polling
On-request inventory - particularly hotels in high-demand markets and tour products - requires active tracking of supplier systems until confirmation arrives. Automated confirmation tracking, timeout escalation, and fallback options need to run without an ops agent manually chasing suppliers on email or phone.
Who This Is For
The Businesses That
Reach Out to Me
Travel Founders & CEOs
Your platform works at current scale. But growth is exposing the cracks - in booking reliability, supplier stability, or post-trip operations. You need a technical perspective that understands the business constraints too.
Hotel Tech & Hospitality SaaS Companies
Distribution architecture, PMS connectivity, channel management, and the operational systems that keep occupancy and revenue data consistent. I know these systems from working inside them.
OTA / Aggregator / B2B Distribution Platforms
Complex supplier networks, high search-to-book ratios, pricing accuracy under load, and integration contracts that need to be sustainable. These are the problems I've worked through.
Teams Modernizing Legacy Travel Stacks
A platform built 8–10 years ago that's now holding back product velocity and scaling confidence. You need a plan that doesn't require stopping the business to execute.
Technology Stack
What a Modern Travel Platform
Actually Runs On
Stack decisions made at the early scaling phase - around caching, queuing, and API design - are the ones teams spend years undoing if they get them wrong. Here's the infrastructure pattern I've seen work for travel platforms at scale, with the reasoning behind each choice.
Core Infrastructure (AWS)
Lambda (Supplier Adapters)
ECS / Fargate (Booking Services)
API Gateway
SQS (Async Confirmations)
SNS (Event Broadcasting)
Step Functions (Post-Booking Workflows)
CloudFront (Search Response Caching)
Route 53 (DNS & Health Routing)
Data & Caching
ElastiCache Redis (Availability Cache)
Aurora RDS (Transactional Bookings)
DynamoDB (Supplier Session State)
Elasticsearch (Content & Property Search)
S3 (Vouchers & Documents)
TTL-Managed Search Cache
Rate & Session Store
Observability & Reliability
CloudWatch (Per-Supplier Metrics)
Datadog / New Relic
AWS X-Ray (Distributed Tracing)
PagerDuty (On-Call Alerting)
Booking Funnel Monitoring
Supplier SLA Dashboards
Reconciliation Anomaly Alerts
Integration & API Layer
REST & XML API (Supplier Side)
GraphQL (Internal BFF Layer)
Webhook Receivers
OAuth 2.0 / JWT (B2B API Auth)
API Rate Throttling
Supplier Circuit Breakers
OpenAPI Spec-First Design
Why This Matters
Operator,
Not Observer
I've built and led travel technology from the inside - not by advising from a distance. I know what it takes to maintain supplier connections that behave differently every quarter, what happens when a GDS pushes a breaking change on a Friday afternoon, and why reconciliation complexity compounds faster than most teams anticipate.
The decisions I help teams make aren't theoretical. They're about what to build now, what to defer, what to buy, and what to stop maintaining. That judgment comes from having sat with these exact trade-offs under real delivery pressure, across TravelTech, Hospitality SaaS, and distribution platforms across India, UAE, and international markets.
20+
Years in Technology Leadership
31+
Products Shipped to Production
35M+
API calls/day at peak scale
5
India, UAE, Maldives, USA & Canada
FAQ
Common Questions
What kind of travel platforms have you worked with?
Hotel tech, B2B distribution platforms, OTA/aggregator backends, hospitality SaaS, and travel management systems. Across India, UAE, and with teams building for international markets. Both greenfield builds and modernization of platforms that had been running for 5–10 years.
Can you help with a specific integration - OTA, GDS, or supplier?
Yes. If you're dealing with a specific connectivity challenge - unreliable supplier responses, rate/availability sync issues, schema drift, or building a new integration - that's a productive thing to work through together. Bring the specifics.
Do you work hands-on or purely as an advisor?
Both, depending on what's most useful. For some teams I review architecture and provide directional guidance. For others, I'm more actively involved in design decisions, technical standards, and helping engineering leads navigate the execution.
How do you approach modernization for a platform that's still live?
Staged, boundary-first. I don't recommend big-bang rewrites for live travel platforms. The approach is to identify the highest-fragility, highest-cost integration points and address those first - running new and old in parallel, validating, then cutting over.
Can you work with teams outside India?
Yes. I've worked remotely with teams across UAE, the US, and other markets. Time zones aren't a barrier for advisory work.
What's your experience with GDS integrations specifically?
Full-suite across Amadeus, Sabre, and Travelport/Galileo - search, book, cancel, ticketing, and post-ticketing operations including void, refund, and exchange. Including NDC and airline direct API connectivity. I've dealt with GDS schema changes mid-contract, rate limit renegotiations, and the operational differences between using a GDS as a primary supplier versus as a supplementary feed alongside direct hotel connects.
How do you handle channel manager and PMS integration complexity?
Channel managers (SiteMinder, Staah, RateGain) and PMS systems (Opera, Cloudbeds) each have their own data models, push/pull availability mechanisms, and rate code structures. The key is normalising at the integration boundary - your CRS or distribution layer should never need to understand each system's quirks directly. I've built this abstraction layer for multi-property hotel groups and hospitality SaaS platforms, and it's what makes adding a fourth or fifth PMS integration take days rather than months.
Post-booking operations are becoming our biggest bottleneck. Where do I start?
Map the specific manual steps first. Which operations happen more than 50 times a week and require someone to touch a supplier extranet or send a follow-up email? Prioritise by volume and risk - cancellation confirmations and amendment tracking are usually the highest-ROI automation targets. Most platforms eliminate 60–70% of ops burden from just two or three well-designed automations. The first session is usually enough to identify exactly where the ceiling is.
How long does a typical engagement run?
It depends on what you're working through. An architecture review and recommendations engagement is typically 2–4 weeks. Ongoing advisory for a platform in active modernisation or scale-up is more often structured as a 3–6 month retainer with regular working sessions. Some teams need a focused intervention on a specific integration problem - that's often 2–3 weeks. I structure it around what's actually useful, not a fixed package.
What's the best way to start?
Book a 30-minute session using the calendar. Come with the specific platform challenge or decision you're working through. No slides needed - just the problem.