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DataArt & Rappi: Three Pillars of Strong Technological Partnership

DataArt introdujo una nueva arquitectura de motor de búsqueda basada en microservicios e indexación personalizada, utilizando Elasticsearch como núcleo. La solución se asemejaba a una experiencia de búsqueda en la vida real con funcionalidades de búsqueda de relevancia incomparable.

Nombre de la compañía Rappi
UbicaciónLATAM
Rappi

Client

Rappi is a multi-vertical super-app that offers food, groceries, e-commerce, pharmacy, travel, and payment services in 9 countries in Latin America.

One of Rappi’s key verticals is Rappi Travel, an online travel platform for booking trips, aggregating flight offers, and more. This vertical aims to continue to add value to the lives of Rappi users by providing multiple integrated services within the super-app ecosystem.

Challenge

Against a backdrop of increased demand for travel and constantly fluctuating travel conditions, Rappi recognized the need to improve the app’s search features and capabilities for its customers. Its Airport & City Search Engine presented an opportunity to enhance accuracy and performance while building a curated, seamless search experience.

Goals:

  • Improve user experience by returning faster and more accurate results
  • Leverage sales by delivering the proper search response to the visitor
  • Decrease maintenance costs by introducing a new microservices architecture

Solution

DataArt’s vision: Improving in-app search without the operational overhead and creating a tolerant and relevant process that offers users an out-of-the-box search tool inside the app.

DataArt introduced a new search engine architecture based on microservices and custom indexing, using Amazon OpenSearch Service at its core. The solution resembled a real-life search experience with searching functionalities of unrivaled relevance.

Rappi Team Scaling

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Highlights

  • Improved indexing and search performance by 10X
  • Increased maintainability, scalability, and reliability

Benefits

  1. Improved conversion rate for search by 5% for locations not covered by popular destinations
  2. Reduced cost-to-serve by optimizing marketing performance and costs
  3. Increased engagement and customer satisfaction with a rich search experience
  4. Decreased maintenance costs

Technology Stack

AWS
Amazon OpenSearch Service
Amazon DocumentDB

DataArt and AWS Travel & Hospitality Competency

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