Business Challenge

This online travel agency processes high-volume flight bookings through multiple suppliers for the same airline inventory, so supplier reliability directly affects revenue and customer experience. When suppliers encounter technical timeouts, provider-side error codes, or inventory unavailability at confirmation, bookings fail at search, pricing, or payment stages, creating disruption, customer dissatisfaction, and “hundreds of thousands of dollars per hour” in potential revenue loss. Automated switching to healthier suppliers is critical, but the legacy monitoring setup and manual workflows were too slow and fragmented to detect patterns quickly and trigger routing changes in time.

• Technical timeouts and provider errors caused failed booking attempts during peak demand windows.
• Inventory unavailability surfaced flights as bookable but failed at confirmation, frustrating customers at checkout.
• Authentication and integration issues broke booking flows, especially on mobile channels.
• Manual monitoring and supplier switching created long gaps between issue onset, detection, and action.
• Multiple suppliers per carrier required intelligent, automated failover to maintain bookability without losing inventory coverage.

Solution and Implementation

Bicycle AI’s agentic analytics platform replaced manual checks with an autonomous supplier circuit breaker that continuously tracks bookability and takes action the moment performance drops.

• Monitors booking success and failure rates at a granular supplier–carrier–pseudo city level, recalculated every 10 minutes.
• Uses tier-based thresholds: around 90% bookability for top carriers, and 30–60% thresholds for lower-volume carriers, modeled from historical performance.
• Ingests streaming booking events, provider error types/codes, revenue signals, and geographic context into a single analytics layer.
• Triggers an automated circuit breaker via webhook calls to temporarily remove underperforming suppliers from the routing workflow as soon as thresholds are breached.
• Sends Slack alerts to flight commercial and operations teams with context such as affected carrier, route, and provider error category, while the backend has already shifted traffic.
• Uses unique rejection tracking to filter out repeat customer retries so failure and bookability metrics reflect true unique attempts.

By integrating Bicycle AI, the OTA transformed supplier performance monitoring from manual and reactive to fully automated and proactive.

Business Impact 

The supplier circuit breaker moved the OTA from reactive supplier monitoring to proactive, automated protection of key flight routes.

• Limited the duration and impact of supplier-side degradation that previously led to “hundreds of thousands of dollars per hour” in potential losses.
• Maintained high bookability for top-tier carriers by quickly routing traffic to healthier suppliers when issues occurred.
• Reduced dependency on data and engineering teams, allowing commercial teams to act directly on rich, contextual alerts.
• Improved supplier accountability with consistent, granular performance views at supplier–carrier–pseudo city level.
• Reduced failed booking attempts and preserved a smooth search-to-confirmation journey, especially during peaks.