The Retrieval Problem: Why Travel Data Demands More Than Generative AI

The travel industry harbors vast knowledge in unstructured forms—airline databases, PDF rule books, legacy systems—that users struggle to access naturally. Large language models alone cannot be trusted in this domain; they confidently provide false information about visa rules, fares, and baggage allowances. RAG architectures solve this by grounding AI responses in actual data, but the true technical challenge lies in building robust retrieval layers over heterogeneous travel data sources, a data engineering problem often overshadowed by the generation component.