Unlocking Operational Knowledge with AI

Volaris empowers its workforce with AI-driven knowledge access, streamlining operations and cutting search time by up to 90%.

Customer Overview

Volaris is Mexico's largest airline by passenger volume, operating as an ultra-low-cost carrier (ULCC) across Mexico, the United States, Central America, and parts of South America. Founded in 2005, the airline has grown into a key player in the aviation industry, serving over 70 airports and operating more than 200 routes with a fleet of 149 aircraft, a majority of which are fuel-efficient NEO models.

With a strong focus on operational efficiency, cost optimization, and scalability, Volaris serves a broad customer base including leisure, business, and VFR (visiting friends and relatives) travelers. Its fast-paced, high-volume operations demand precise, real-time access to critical information across multiple operational roles.

Challenge

Volaris faced a critical operational bottleneck: employees across different roles—pilots, flight attendants, airport staff, and operations control—struggled to quickly locate and access essential documentation stored across hundreds of folders in SharePoint.

The absence of a centralized, intelligent search mechanism resulted in time-consuming manual searches, inconsistent information retrieval, and increased risk of operational and regulatory errors. Employees often relied on inefficient workarounds, such as asking colleagues or navigating complex folder structures, leading to delays and reduced productivity.

This challenge introduced significant risks, including:

• Delays in accessing time-sensitive operational information
• Increased likelihood of errors due to outdated or incorrect documentation
• Potential regulatory non-compliance
• Reduced scalability and trust in internal systems

Without a modern solution, these inefficiencies were expected to compound over time, impacting operational performance, employee experience, and overall cost structure.

Solution

Point B designed and implemented a unified, role-aware Generative AI chatbot that provides fast, secure, and intelligent access to enterprise documentation through a conversational interface.

The solution leverages Retrieval-Augmented Generation (RAG) to deliver precise, context-aware answers grounded in Volaris's internal knowledge base, replacing manual, folder-based searches with a streamlined AI-driven experience.

At the core of the solution is a scalable, serverless AWS architecture built on Amazon Bedrock, AWS Lambda, Amazon S3, Amazon OpenSearch, and Amazon API Gateway. Documents were migrated from SharePoint to Amazon S3, where automated metadata tagging enables advanced filtering and retrieval.

Key capabilities include:

• Role-based access control to ensure users only see relevant information
• Hybrid search combining semantic understanding and metadata filtering
• Automated metadata generation (role, document type, date, aircraft, legal status)
• Intelligent query interpretation to dynamically apply filters based on user intent
• Re-ranking models to prioritize the most relevant and up-to-date results

The solution consolidates multiple legacy tools into a single, unified chatbot, reducing infrastructure complexity while improving maintainability and scalability.

Compared to traditional approaches, this architecture delivers:

• Scalability & performance: serverless services that automatically handle demand spikes
• Operational simplicity: fully managed AWS services with minimal infrastructure overhead
• Security & compliance: role-based access and controlled data exposure
• Future readiness: a flexible foundation for expanding AI-driven use cases