AI case study

RappiProduct search

Legacy keyword search failed on typos and vague queries. Now, semantic AI interprets natural language and images to find exact items.

Published|1 month ago

Key results

Conversion Rate Increase
25%
Response Time Reduction
40%

Result highlights

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The story

Context

Latin America's fastest-growing on-demand delivery app operates across more than 300 cities, connecting users with extensive retail and restaurant catalogs.

Challenge

The legacy keyword-based search engine struggled to process vague queries, misspelled words, or low-interaction keywords that lacked semantic...

Solution
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Quotes

The company

Multi-vertical super-app for on-demand delivery, fintech, and travel services.

IndustryTransportation & Logistics
LocationBogotá, Colombia
Employees5K-10K
Founded2015

The implementation partner

Marvik logo

Marvik

marvik.ai
Role in this case study

Worked with Rappi to migrate its on-demand delivery platform to Oracle AI solutions.

IndustryTechnology
LocationMontevideo, Uruguay
Employees51-250
Founded2016

The vendor

Enterprise database software and cloud infrastructure services.

IndustrySoftware & Platforms
LocationAustin, TX, USA
Employees100K+
Founded1977

Use case

Rappi's Product search is part of this use case:

Specialized Search
28 case studies(+111% YoY)
Proven impact?
LowModerateVery Strong
5.2Strong
3.9Moderatewithin Product Engineering

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