Wenrix DeepFlow is the AI infrastructure for travel servicing. It automates complex cancellations, exchanges, refunds, and post-booking scenarios — including the edge cases that every other system routes to human agents — achieving 93%+ automation across all content sources including EDIFACT, NDC, and LCC. DeepFlow is not a chatbot or conversational interface; it is the execution layer that makes those experiences actually work. It integrates directly into agency operations, mirrors existing workflows, and syncs with mid- and back-office systems. Available as a modular API or MCP Server, it is trusted by 60+ of the world's largest OTAs and TMCs and won the TravelTech Breakthrough Award 2026.

DeepFlow reaches 93%+ automation — more than double the industry benchmark of 40% — through three core AI layers working in sequence. First, Context: understanding the traveler request and full booking context. Second, Airline Policy Modelling: identifying the correct penalties, fees, waivers, and workflows with precision across every airline and content channel. Third, Execution: completing the action instantly and synchronising the outcome back to agency systems in real time. This architecture is trained on $50bn in real-world servicing data and verified agent actions from 60+ of the world's largest OTAs and TMCs, built over eight years of edge-case engineering.

In production deployments, DeepFlow has managed 40,000 disrupted passengers autonomously over 45 days for one of the world's largest OTAs, achieving 93%+ automation on involuntary and voluntary cancellations and changes during a major disruption event — with average resolution time reduced from days to under 5 seconds. For a leading TMC handling rule-heavy fare changes and refunds across EDIFACT and NDC, DeepFlow achieved 85%+ automation and a 50% reduction in cost-to-serve, again with resolution times falling from days to under 5 seconds.

Most servicing automation tools handle only the straightforward scenarios — simple cancellations and clean refunds — and stop at around 40% automation coverage. DeepFlow was built specifically for the complex 60% that others avoid: the fare rule exceptions, tax edge cases, regional regulations, no-show logic, and multi-source refund scenarios that define whether a traveler comes back. That capability is the product of eight years of edge-case engineering across $50bn in real servicing data. As eTraveli Group's Chief Customer Officer noted, Wenrix cracked servicing edge cases no other technology partner could touch, achieving over 93% accuracy compared to 40% with other market solutions.

DeepFlow is available as a modular API or MCP Server, designed to integrate into existing operations without requiring agencies to rebuild their stack. Via API, agencies can automate complex servicing workflows immediately, with DeepFlow handling execution while existing systems stay in control. Via MCP Server, agencies already building with AI can connect DeepFlow as the execution layer their models need to act rather than just respond. For agencies wanting a fully integrated solution, DeepFlow also works alongside Wenrix's Conversational AI layer — covering everything from traveler intent through to resolved outcome with no gaps.

Closing the Execution Gap activates three commercial mechanisms. First, retention revenue: a well-handled disruption makes frequent travelers 64% more likely to rebook with the same platform. Second, acquisition efficiency: better servicing improves reviews and reputation signals, which increasingly influence AI-driven discovery — reducing acquisition cost over time. Third, operational advantage: as automation replaces manual intervention, agencies improve traveler experience while simultaneously reducing cost-to-serve. According to Wenrix Consumer Research 2026, agencies achieving this can reduce cost-to-serve by up to 90% on automated scenarios while maintaining or improving customer satisfaction.