Autonomous AI discovery built for travel & hospitality.
Continuous AI discovery across your reservations, channel, loyalty, and ancillary data. Every finding ships with the underlying queries, the cohort definition, and the cost of the run. The cohort-level demand questions that never make it past the weekly KPI deck, answered before your next revenue review.
Built for VPs of Revenue Management, Heads of Distribution, Chief Commercial Officers, and Heads of Analytics at hotels, airlines, cruise lines, and tour operators.
The cohort-level demand questions that never make it past the weekly KPI deck, running overnight against your data.
Your team owns the rate, the inventory, the channel mix, the loyalty program. The agent runs unattended against your reservations, channel, loyalty, and ancillary data — and ships findings into a queue your team triages. Every claim carries the underlying queries and the data-validated number, not the reservation-system-reported or BI-dashboard-reported one.
See how the agent reads segment × channel × loyaltyTotal bookings look fine. The cohort underneath is where the demand actually moved.
Three benchmarks every revenue management and commercial leader recognizes. Each points to the same gap: your data already holds the signals — channel quality drift, loyalty cohort behavior, segment mix shifts — but they only surface when somebody asks the right question. Most weeks, nobody does.
Three findings the agent surfaced, paired with the recommendation it shipped.
Three shapes the revenue team sees every quarter: a single-channel booking-quality cliff the aggregate concealed, a cross-system top-tier loyalty drift the dashboard couldn't see, and a segment-mix mirage the aggregate rate averaged into a win. Same auditable trail every time — severity, the underlying queries, the cohort definition, the cost of the run.
Point the agent at your reservations and channel data for a week. Triage what it finds Monday morning.
Five surfaces the team already owns, one continuous discovery.
Same engine, same data, five categories of work your team is already doing — or wants to do, if the queue ever clears. Pick the surface that matters this quarter.
The booking pace that looks normal, and the cohort underneath that isn't.
Booking pace, lead-time distribution, and conversion drift by segment, channel, geography, and product. The agent reads reservations, lookup events, and rate availability together — and surfaces the cohorts whose booking shape changed before the weekly pace report catches it. Pre-cancellation behavior, search-to-book friction, and lead-time compression all show up at the cohort level before the aggregate moves. The deep dive lives in how the agent decides what to investigate.
- Booking pace and lead-time distribution by segment and product
- Search-to-book conversion drift across direct and partner channels
- Pre-cancellation behavior patterns and early-warning windows
- Rate-availability mismatches that quietly lose bookings
- Geography and source-market cohort-level demand shifts
Built for travel suppliers who want a cohort analyst running overnight, not three dashboards to reconcile.
Three things every finding from DecisionBox carries. None of them changes how your team works in your reservation system, your revenue management dashboard, your loyalty platform, or whatever data tools and BI you already standardized on.
Sees what nobody had time to query for
The agent picks which cohorts, segments, distribution channels, and loyalty tiers to investigate from your reservations, channel, loyalty, and ancillary data. Findings ship into a queue your team triages in the morning. The cohort-level demand question stops sitting in the data waiting for the next QBR.
Every number you'd defend at the revenue review
The underlying queries the agent ran, the cohort definition, the data window, the cost of the run, the validation checks. Your team re-runs anything, extends anything, overrides anything. No black boxes, no reservation-system-reported or BI-dashboard-reported numbers the data can't validate, no "trust the AI."
Reads all your data, not just the reservation system and the revenue management dashboard
Reservations plus channel attribution, loyalty membership, ancillary spend, and segment classification — read together. The patterns the reservation system can't see (because it only sees bookings) and the patterns the revenue management dashboard can't see (because it only sees rate and yield) surface when your data is read end-to-end. Snowflake, BigQuery, Databricks, Redshift, PostgreSQL. Open source, AGPL v3. The agent meets you on the stack you already run.