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AWS Solutions Library

Guidance for Building Travel Assistants Using Amazon Bedrock Agents

Overview

This Guidance demonstrates how organizations in the travel and hospitality (T&H) industry can build an intelligent virtual assistant that uses generative AI to streamline every aspect of travel planning. Through a personalized chat interface, the virtual concierge curates tailored travel itineraries, handles all bookings, and provides recommendations for flights, accommodations, activities, and local experiences based on individual preferences, budgets, and travel styles. Once bookings are made, the virtual concierge supports travelers with any questions or changes for a stress-free and flexible travel experience.

How it works

These technical details feature an architecture diagram to illustrate how to effectively use this solution. The architecture diagram shows the key components and their interactions, providing an overview of the architecture's structure and functionality step-by-step.

Download the architecture diagram

Well-Architected Pillars

The architecture diagram above is an example of a Solution created with Well-Architected best practices in mind. To be fully Well-Architected, you should follow as many Well-Architected best practices as possible.

AWS Cloud Development Kit (AWS CDK) allows you to define AWS resources using traditional programming languages. By defining all AWS resources with AWS CDK, you can replicate deployments and safely deploy changes and updates to workloads. Amazon CloudWatch proactively monitors applications and infrastructure, helping identify anomalies, troubleshoot issues, and ensure peak efficiency.

Read the Operational Excellence whitepaper 

Amazon Cognito securely manages user identities and access for web and mobile applications, minimizing custom identity management code while enhancing security through multi-factor authentication. Amazon Bedrock provides data privacy and security through encryption at rest and in transit, access controls, and support for regulatory standards. Amazon Bedrock Guardrails implement safeguards for generative AI applications, filtering undesirable content and protecting against data leaks.

Read the Security whitepaper 

Amazon Bedrock offers provisioned throughput, enabling application performance scaling to meet user base demands. This capability helps ensure reliable service delivery, handling fluctuations in demand.

Read the Reliability whitepaper 

Amazon Bedrock provides a wide range of foundation models, allowing selection of the most appropriate model for specific use cases and requirements. Additionally, Amazon Bedrock Knowledge Bases offers various vector database options, optimizing for factors like cost, operational overhead, and data location.

Read the Performance Efficiency whitepaper 

The S3 Intelligent-Tiering storage class automatically moves data to the most cost-effective access tier, reducing storage costs without impacting performance. This helps ensure that the raw knowledgebase files that you upload to your S3 bucket are correctly handled and moved to cheaper storage classes when they are no longer frequently accessed.

Read the Cost Optimization whitepaper 

Lambda runs code without provisioning or managing servers, automatically scaling to meet demand, reusing execution environments, and optimizing resource utilization. This serverless approach contributes to a more sustainable architecture and minimizes energy consumption.

Read the Sustainability whitepaper 

Disclaimer

The sample code; software libraries; command line tools; proofs of concept; templates; or other related technology (including any of the foregoing that are provided by our personnel) is provided to you as AWS Content under the AWS Customer Agreement, or the relevant written agreement between you and AWS (whichever applies). You should not use this AWS Content in your production accounts, or on production or other critical data. You are responsible for testing, securing, and optimizing the AWS Content, such as sample code, as appropriate for production grade use based on your specific quality control practices and standards. Deploying AWS Content may incur AWS charges for creating or using AWS chargeable resources, such as running Amazon EC2 instances or using Amazon S3 storage.

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