Skip to main content
Vikrama.
Travel

Booking systems, guest intelligence, and revenue engines. Built for occupancy, not just reservations.

We build the systems that turn guest data into higher RevPAR and better experiences.

Hotels, airlines, and travel platforms run on thin margins and high expectations. We build AI-powered revenue management, guest personalization systems, and booking platforms that maximize occupancy and guest satisfaction simultaneously.

Why AI in Travel is different.

Travel runs on perishable inventory. An empty room tonight or an empty seat on today's flight is revenue that never comes back. Hotels using AI-powered revenue management see 8-15% RevPAR improvement within six months, not from raising prices, but from pricing every room, every night, against real-time demand signals instead of last year's spreadsheet.

OTAs take 15-25% commission on every booking they own. Direct booking rates are the single biggest margin lever most properties have, but their websites convert at half the OTA rate because the booking experience is worse. Meanwhile, guest personalization is still a loyalty card and a generic welcome email.

The winners in travel are not the ones with the best locations. They are the ones with the best data infrastructure: unified guest profiles, dynamic pricing engines, and operations platforms that coordinate housekeeping, maintenance, and front desk in real-time. That is a systems problem, not a hospitality problem.

The Problems That Slow You Down

01

Revenue management is last year's spreadsheet

Room pricing based on historical occupancy and competitor rates. Dynamic pricing exists in theory but not in your PMS.

02

Guest personalization is a loyalty card

Every guest gets the same room, same welcome, same upsell email. Frequent guests don't feel recognized.

03

OTA commission is eating your margin

Booking.com and Expedia take 15-25%. Direct bookings are cheaper but your website converts at half the rate.

04

Operations run on walkie-talkies and whiteboards

Housekeeping, maintenance, and front desk coordinate manually. Room status is 30 minutes behind reality.

These aren't pitch deck scenarios. Every use case maps to a system pattern we've built and deployed in production.

What We Build in Travel

Dynamic Hotel Room Pricing

VP Revenue Management
Problem

Manual rate adjustments miss real-time demand; 5-10% revenue left on table.

System

XGBoost/LSTM on booking pace, competitor rates, events, seasonality, channel data, delivering real-time recs to PMS/CRS.

7.2% revenue uplift; 17% revenue increase, 10% occupancy boost.

Autonomous Reservation Agent

Head of Reservations
Problem

Bookings from OTAs/agents/emails/docs; manual reconciliation causes 5-10% overbooking risk, 2-3 day lags.

System

Multi-agent LLM with OCR for docs/emails, availability checks, dynamic pricing, auto-confirmation/ERP sync.

70-90% bookings automated, overbooking risk cut, processing from days to minutes.

Airline Revenue Management

VP Revenue Management
Problem

Legacy RMS can't handle real-time competitor pricing; empty seats or over-discounting.

System

RL + demand forecasting on booking curves, comps, ancillaries for fare/inventory optimization and no-show models.

Boosted revenue, occupancy, profitability via real-time adjustments.

Personalized Guest Journey Engine

VP Marketing
Problem

Generic offers; 5-10% upsell conversion despite rich guest data.

System

Segmentation + LLM for journey orchestration (welcome, upgrades, spa based on prefs/behavior), A/B tested.

25% upsell/cross-sell revenue increase.

Booking Fraud Detection

Head of Fraud Prevention
Problem

Fake bookings cost 1-5% of revenue; manual reviews slow confirmations.

System

XGBoost anomaly detection on booking velocity, IP/proxy, payment patterns, device fingerprints.

Fraud losses down 50-70%, minimal false positives.

OTA Price & Parity Intelligence

Director of Distribution
Problem

Miss rate parity across 100s of OTA sites; 20-30% channel fees erode direct bookings.

System

ML scraping + anomaly detection on OTA rates for deviation alerts and parity enforcement.

Dynamic adjustments improve occupancy and revenue.

Multi-Lingual Guest Chat Agent

Director of Guest Services
Problem

Global properties handle queries in 10+ languages; staff shortages delay responses.

System

LLM agent for chat/email handling reservations, amenities, check-in, multi-lingual with escalation to humans.

24/7 coverage, faster responses, higher satisfaction.

Building the system is half the job. Growing the business around it is the other half.

How We Grow Travel Brands

AEO for Hotel PMS Software Queries

Head of Growth Marketing
Problem

Hospitality tech loses 46% of "best hotel PMS software" to ChatGPT; zero-clicks reduce trials 32%.

Build

Schema feature comparisons, ROI calcs, Perplexity tracking to demo funnels.

41% AI citation growth, 27% trial traffic in 6 months.

LinkedIn Ads for Hotel Revenue Tools

Demand Gen Director
Problem

LinkedIn CPL $60-100 for RMS; under 11% SQL rate.

Build

GM targeting, webinars, HubSpot scoring/nurture for pricing demos.

CAC 33% down to $50, pipeline 2x.

HubSpot Lead Scoring for OTA Integrations

Marketing Ops Lead
Problem

2.8K leads/quarter; 63% unqualified.

Build

HubSpot workflows (channel tests, visits), sequences (ROI tools), PMS sync.

Integration pipeline 44% growth, cycle 25% shorter.

Frequently asked questions

AI moves fast. Stay ahead.

No spam. One actionable email per week on AI systems and growth.

Empty rooms tonight are revenue you never get back. We fix that.

Start with a revenue and guest data audit. We'll identify the fastest path to higher occupancy and better guest experiences.