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Title
Eurowings Delivers Real-Time Travel Insights with Databricks
…emo Login Contact Us Try Databricks Customer Stories / Eurowings CUSTOMER STORY Eurowings delivers real-time travel insights with Databricks 109% lift In search relevance achieved by replacing keyword-based search with s…
Description
Eurowings, a Lufthansa Group subsidiary, migrated to a unified data platform called Minerva, built on Databricks with a medallion architecture, to replace siloed data systems. It implemented semantic search on eurowings.com using Databricks AI Search and Model Serving, replacing keyword-based search. The change delivered a 109% lift in search relevance, improved recall from 50% to over 75%, and cut search latency from six seconds to under two seconds. MLflow is used to manage the model lifecycle, with Model Serving acting as a single endpoint for testing different embedding models.
…t ROI has Eurowings seen from its Databricks Data + AI Platform implementation? Eurowings achieved a 109% lift in search relevance and improved recall from 50% to over 75% after implementing Databricks Vector Search. Search latency dropped from six seconds to under two seconds — a reduction of m…
Company
Eurowings
…r two seconds, cutting response time by more than 60% for live traveler queries Eurowings, a subsidiary of Lufthansa Group and a leader in the travel industry, aims to be the ultimate travel companion by providing seamless digital experie…
Problem
Before unifying its data strategy, Eurowings faced significant challenges with siloed data across disparate systems. The previous environment lacked the connectivity required to implement advanced AI use cases, leaving the data and AI team unable to provide integrated experiences.
…from 50% to more than 75%. Breaking down data silos to power travel innovation Before unifying its data strategy, Eurowings faced significant challenges with siloed data across disparate systems. The previous environment lacked the connectivity required to implement advanced AI use cases, leaving the data and AI team unable to provide integrated experiences. Technical barriers in vector storage also slowed development, as the team had t…
Solution
Eurowings migrated to a new platform, Minerva, built on Databricks, creating a unified data lake using a medallion architecture. To power semantic search, the company implemented AI Search and Model Serving to handle real-time inference, using MLflow to manage the model lifecycle and Model Serving as a single endpoint that connects to its applications, providing flexibility to test different embedding models.
…livering real-time value to our users.” Powering semantic search with AI Search Eurowings migrated to a new platform, Minerva, built on Databricks. This move enabled the team to create a unified data lake using a medallion architecture, in which raw data is refined through the Bronze-to-Gold layers for production readiness. To power its new semantic search, the company implemented AI Search and Model S…
Business value
Eurowings achieved a 109% lift in search relevance, improved recall from 50% to over 75%, and reduced search latency from six seconds to under two seconds, cutting response time by more than 60% for live traveler queries.
…t ROI has Eurowings seen from its Databricks Data + AI Platform implementation? Eurowings achieved a 109% lift in search relevance and improved recall from 50% to over 75% after implementing Databricks Vector Search. Search latency dropped from six seconds to under two seconds — a reduction of more than 60% — delivering a faster, more accurate experience for travelers on eurowings.com. The solution also surfaced content quality issues across multiple web pages, en…
Industry
Travel & Hospitality
…silos that previously blocked advanced implementations. Share this post Details Industry : Travel and Hospitality Use Case : Artificial Intelligence , Data + AI Platform , Data Sharing and Coll…
Technology
Databricks Vector Search, Model Serving, MLflow
…Eurowings use with the Databricks Data + AI Platform for its search experience? Eurowings uses Databricks Vector Search for semantic search, Model Serving as a unified inference endpoint connecting to customer-facing applications and MLflow for model lifecycle management. This stack replaced a fragmented, manual approach to vector storage and hybrid…
AI capabilities
Natural Language Processing
…cycle and Model Serving as a single endpoint that connects to our applications. This setup provides the flexibility to test different embedding models and identify which ones provide the best answers for our customers.” Driving 109% lift in search relevance and performance The shift to Databricks…
Deployment options
cloud
…: Artificial Intelligence , Data + AI Platform , Data Sharing and Collaboration Cloud : Azure Product : Agent Bricks Ready to get started? Try Databricks for free Talk to an…
