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Build a ChatGPT-Like App on AWS: A Comprehensive Guide to Conversational AI Development

Vikas Singh
Vikas Singh
January 4, 2024
Clock icon13 mins read
Calendar iconLast updated January 4, 2024
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Quick Summary:- This article talks about Amazon Q, a powerful tool for developing custom models with large language models, and your own company, explaining how it can benefit businesses. Additionally, it provides a guide on creating a ChatGPT-like generative AI tool on AWS.

In this AI era, businesses are actively adopting generative AI tools to automate various tasks, including customer service interactions and content creation. These tools can achieve the work of multiple human analysts with significantly greater speed and precision.

A prime example is ChatGPT, an OpenAI product that has shaken the industry with its ability to generate human-quality text, code, and marketing materials. From crafting engaging social media posts to streamlining customer inquiries, these AI tools offer a multitude of benefits for marketers, content creators, coders, and businesses as a whole.

Since the emergence of generative AI tools, businesses have been putting their efforts into transforming their businesses by integrating AI tools to improve their services and increase productivity.

The race to adopt AI-driven businesses is not just giving an edge over competitors; it’s become imperative in today’s data-driven world.  With the exponential growth of data, AI tools can act as powerful allies, bridging the gap between your business and users.  They can assist your customers, streamline your operations, and ultimately boost productivity.

For companies within the AWS ecosystem, leveraging this power is even easier with Amazon Q. This AI-powered assistant helps businesses harness the potential of generative AI.

Don't let your competitors gain an edge with AI. Hire an AWS expert and integrate Amazon Q into your cloud apps. Contact us today to transform your workflows.

What is Amazon Q?

Amazon Q is an enterprise chat assistant service from Amazon Web Services (AWS) that lets you deploy conversational AI applications. To build a generative chatbot for your organization's end users, you can utilize either enterprise data alone or combine it with the knowledge of specific large language models, depending on your desired level of personalization and context.

It is a fully managed service, meaning Amazon takes care of the underlying infrastructure, including servers, storage, and networking. This eliminates the need for you to provision, configure, and maintain your own ML infrastructure.


Features of Amazon Q

  1. Summarizing long documents, generating drafts of emails or articles, conducting research on topics, or performing comparative analysis
  2. It understands existing identities, roles, and permissions and uses this information to personalize its interactions.
  3. It can help you brainstorm solutions and identify relevant information.
  4. Do you need reports, summaries, or even creative text formats? It can handle it, saving you time and effort.
  5. Based on its insights, it can suggest and even automate specific actions to address issues or capitalize on opportunities.
  6. Amazon Q takes care of the tricky stuff, like building and managing AI for your chatbot so that you can build it faster—no need to mess with complex machine learning yourself.
  7. Amazon Q can scan all your documents, emails, code, and other internal info to give you the most relevant answers and even provide you an option to choose what sources should be used to respond to user queries.
  8. It supports access control for your data, allowing administrators to set permissions for access. It will respond to questions based on each end user's specific permissions and access levels.
  9. Unlike other tools, it provides sources for its information, eliminating the need for manual cross-checking.

How Amazon Can Help Your Business?

By deploying it in your organization, you can help your employees by supporting them in key tasks such as answering questions, writing emails and messages, discovering knowledge, summarizing text quickly, drafting document outlines, and brainstorming ideas. It can perform various tasks, including conversations with end users. q-dev-rev-sq1-rai.

It comes with pre-built connectors to over 40 supported data sources, including Amazon Simple Storage Service (Amazon S3), Microsoft SharePoint, Salesforce, and Atlassian Confluence to let you easily synchronize data from multiple content repositories.  It also includes a built-in semantic document retriever and a ready-to-deploy chat interface for end users, enabling easy deployment.

It further includes built-in plugins to communicate with popular third-party applications, such as JIRA, ServiceNow, Salesforce, and Zendesk.


Amazon Q integrates with services such as Amazon Kendra and other supported data sources such as Amazon S3, Microsoft SharePoint, and Salesforce.

By integrating with these various services and data sources, Amazon Q becomes a more powerful and versatile question-answering tool. It can access a wider range of information and provide more accurate and relevant answers to user questions.

Building a Generative AI Chatbot with Amazon Q: A Developer's Guide

As a business owner, you strive for efficiency and employee empowerment. Amazon Q can be your key ally in achieving this, unlocking valuable insights and empowering your team to make informed decisions with ease. This guide breaks down the process of setting up and integrating Amazon Q into your business app,

Set up Amazon Q with AWS IAM Identity Center

Step 1: Follow the provided instructions on this page to configure Amazon Q with AWS IAM Identity Center as your SAML 2.0-compliant identity provider (IdP).

Setting up Amazon Q with AWS IAM Identity Center as your SAML 2.0-compliant identity provider (IdP)

Step 2: In the IAM Identity Center metadata section, click on "Download" to obtain the IAM Identity Center SAML metadata file.


Step 3: On the details page, click on Actions, then select Edit attribute mapping, and map the Subject to the email attribute, using a syntax like ${user:email}.

Create Amazon Q Application

Step 1: Navigate to the AWS Q in the Console and initiate the process to create an Amazon Q application.
Specify the application name, choose an authentication method for Amazon Q (e.g., using an existing service role), and provide a name for the service role.


Step 3: Choose a retriever – a retriever pulls real-time data from the index during a conversation. Options include using the Amazon Q native retriever or an existing Amazon Kendra retriever.


Step 4: Connect data sources – Amazon Q offers built-in connectors for popular data sources and enterprise systems. For this demonstration, select Amazon S3.


Step 5: Add plugins – Optionally add plugins or skip this step based on your requirements.

Deploy Amazon Q

Step 1: Within the Applications section, select your "Deploy web experience."

Step 2: Within the Service access category, name the service role. You may choose an existing role or create a new role.  Service access role assumed by end users when they sign in to your web experience that grants them permission to start and manage conversations Amazon Q.

Step 3: Enter the ACS URL and  Audience URI (SP Entity ID) in the relevant field.

Step 4: Under "Provide metadata from your IdP," upload the metadata generated by your IdP as an XML file utilizing the "Import from XML" option.

Step 5: Configure user and group mapping, refer to this page for more information on this.

Step 6: To complete the deployment of your web experience, click on "Deploy."

For Administrators:

1. Creating an Application: You kick things off by building an Amazon Q application within the AWS Management Console. This involves defining its purpose, access permissions, and desired capabilities.

2. Choosing a Retriever: Select the AI model responsible for retrieving relevant information from your data sources. Options include pre-trained models or custom models tailored to your specific needs.

3. Connecting Data Sources: Integrate Amazon Q with your internal repositories, codebases, and enterprise systems. Popular integrations include Google Drive, Salesforce, and Slack.

4. Preview & Testing: Before deploying your application, thoroughly test it to ensure it functions as expected. You can chat with the assistant, ask questions, and refine its responses based on your feedback.

For End Users:

1. Accessing the Web Experience: You can explore Amazon Q by navigating to your organization's designated URL and using your credentials to log in. This will provide you access to the Amazon Q interface.

2. Asking Questions: You can converse with Amazon Q. For example, ask it questions related to your work, seek insights from your data, or request specific tasks. It uses natural language for a seamless experience.

3. Information Retrieval: Amazon Q will prioritize information from your internal data sources. If the answer wasn't found there, it may resort to its own model knowledge (if enabled by your admin) or indicate the question is beyond its current scope.

4. Taking Action: You can execute follow-up tasks such as raising tickets, generating reports, or scheduling meetings directly within Amazon Q if your admin has configured it for your organization.

Pricing and availability

Amazon Q is still in early access. You can visit the pricing page for details on current preview costs and the Supported Regions page for a list of available locations.  If it is available, you can access Amazon Q through the AWS Management Console.

Alternatively, you can incorporate Amazon Q functionality into your own software or application through Amazon Q API.

Additionally, you can access it through the AWS command line interface. Also, AWS provides  SDK to interact with AWS services from within your preferred programming language.

Additionally, you can access it through the AWS Command Line Interface (CLI). AWS SDKs provide language APIs for AWS services to use programmatically.


In this article, we've discussed Amazon Q and provided a guide on how to build your own ChatGPT. We hope you found this article helpful and informative.

Amazon Q is a powerful tool that can dramatically transform your business by providing tailored solutions to your unique needs and helping them in various ways to become more predictive and efficient. 

If you want to reduce your AWS cost and improve your existing applicaiton's performance with a free consultation from our exeprt AWS develoeprs. Contact us today to get started. 

Brilworks is a top-rated AWS development company that provides cutting-edge and innovative cloud solutions for businesses of all sizes.


1. What is Amazon Q, and how can it benefit my business?

Amazon Q is an AI-powered assistant that empowers businesses to create custom chatbots tailored to their specific needs. It leverages large language models (or organizations can choose only a specific set of data) to answer questions, generate reports, and summarize documents. By tapping into your company's own data and insights, Amazon Q can provide personalized and relevant responses, helping to boost employee productivity, increase productivity, and streamline workflows.

2. What sets Amazon Q apart from other AI tools?

Amazon Q stands out in several key areas. It prioritizes information from your own internal sources, ensuring highly customized responses. It's also designed for ease of use, with pre-built connectors and a user-friendly interface that allows even non-technical users to build and deploy chatbots effectively. Additionally, Amazon Q takes data security seriously, providing robust protection for your sensitive information.

3. How much does Amazon Q cost, and how can I get started?

Currently in early access,  It will be available in two easy-to-understand pricing plans: Business and Builder. To get started, sign up for the early access program to create your own chatbot through the AWS Management Console or integrate Amazon Q's functionality into your existing software using its API.

Vikas Singh

Vikas Singh

Vikas, the visionary CTO at Brilworks, is passionate about sharing tech insights, trends, and innovations. He helps businesses—big and small—improve with smart, data-driven ideas.

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