AWS Announces Amazon Q to Reimagine the Future of Work
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New type of generative AI-powered assistant, built with security and privacy in mind, empowers employees to get answers to questions, solve problems, generate content, and take actions using the data and expertise found at their company
Accenture, BMW Group, Gilead, Mission Cloud, Orbit Irrigation, and Wunderkind among the customers and partners excited to use Amazon Q
“Generative AI has the potential to spur a technological shift that will reshape how people do everything from searching for information and exploring new ideas to writing and building applications,” said Dr. Swami Sivasubramanian, vice president of Data and Artificial Intelligence. “AWS is helping customers harness generative AI with solutions at all three layers of the stack, including purpose-built infrastructure, tools, and applications. Amazon Q builds on AWS’s history of taking complex, expensive technologies and making them accessible to customers of all sizes and technical abilities, with a data-first approach and enterprise-grade security and privacy built-in from the start. By bringing generative AI to where our customers work—whether they are building on AWS, working with internal data and systems, or using a range of data and business applications—Amazon Q is a powerful addition to the application layer of our generative AI stack that opens up new possibilities for every organization.”
Generative AI chat applications have captured the public’s imagination and helped people understand what is possible, but there are still barriers that prevent people from using these solutions at work. Specifically, these chat applications do not know an organization’s business, data, customers, operations, or employees—the work they do, who they interact with, what information they use, and what they can access. Additionally, these solutions were not initially built with the security and privacy features that organizations need for employees to safely use them in their day-to-day work. This has led to companies adding these features to their assistants after they were built, which does not work as well as incorporating security into the assistant’s fundamental design. That is why AWS created Amazon Q, helping customers unlock the full benefit of generative AI for every employee.
Amazon Q is an expert for customers building, deploying, and operating applications and workloads on AWS
Today, developers and information technology (IT) professionals are expected to keep up with the latest technological developments, design and deliver new features quickly, manage the end-to-end lifecycle of applications and workloads, and balance competing priorities when it comes to building net-new capabilities and maintaining existing offerings. All of this requires significant work for developers and IT professionals that distracts them from their core focus. Whether they are trying to answer a straightforward question, like how a specific feature works, or a nuanced one, like finding the best Amazon Elastic Compute Cloud (Amazon EC2) instance for a given workload, customers spend a significant portion of their time learning how things work through documentation, public forums, and conversations with colleagues. Once the application is up and running, customers need to dedicate additional time and resources to maintain it. For example, troubleshooting a network connectivity issue may require a customer to work quickly to diagnose the problem, ensure there is proper connectivity between resources, and review network configuration details, sometimes in the absence of additional guidance or support from teammates. In their integrated development environment (IDE), a developer that takes over a project from a colleague may have to spend time studying previously written code to understand its underlying programming logic. Regardless of the project they are working on, they also have to continuously debug, test, and optimize their code, taking time away from building new features. Throughout all of these steps, developers and IT professionals are moving between the AWS Management Console and documentation, the IDE, and chatrooms with colleagues, and there is not a unified source to help answer questions across every step of the process from planning to maintaining applications.
Trained on 17 years of AWS knowledge and experience, Amazon Q transforms the way developers and IT professionals build, deploy, and operate applications and workloads on AWS. Customers can access Amazon Q through a conversational interface from the AWS Management Console, documentation pages, their IDE, and over Slack or other third-party chat apps. Amazon Q is an expert on patterns in the AWS Well-Architected Framework, best practices, documentation, and solution implementations, making it easier for customers to explore new services and capabilities, get started faster, learn unfamiliar technologies, architect solutions, troubleshoot, upgrade applications, and more. Customers can get crisp answers and guidance by asking questions to learn about AWS capabilities (e.g., “Tell me about Agents for Amazon Bedrock?”), research how an AWS service works (e.g., “What are the scaling limits on a DynamoDB table?”), figure out the best way to architect a solution (e.g., “What are the best practices for building event-driven architectures?”), or identify the best service for their use case (e.g., “What are the ways to build a web app on AWS?”). Based on the question, Amazon Q will give succinct answers that include citations and links to its sources, and customers can ask any number of follow up questions to get more details, find the best option for their workload, and receive an outline of the basic steps to get started. Customers can also use Amazon Q to select the best EC2 instance for their workload by asking questions like, “Help me find the right EC2 instance to deploy a video encoding workload for my gaming app with the highest performance,” and Amazon Q will provide a list of instance families with the reasons to use each of them. To troubleshoot an issue like an EC2 or Amazon Simple Storage Service (Amazon S3) configuration error, customers simply press the “Troubleshoot with Amazon Q” button while in the AWS Management Console to have Amazon Q research the error and suggest a fix. Customers can also troubleshoot network issues by asking questions like, “Why can I not connect to my EC2 instance from my laptop?” and Amazon Q will analyze a customer’s end-to-end network configuration and provide a diagnosis (e.g., “This instance appears to be in a private subnet, so public accessibility may need to be established.”).
When accessed in the IDE via Amazon CodeWhisperer, Amazon Q combines its expertise for building software with an understanding of a customer’s code. Developers can use Amazon Q to explain specific programming logic by asking questions (e.g., “Provide me with a description of what this application does and how it works.”), and Amazon Q will give details like which services the code uses and what different functions do (e.g., “This application is building a basic support ticketing system using Python Flask and AWS Lambda.”), along with a description of the application’s core capabilities, how they are implemented, and more. Amazon Q can also help developers debug, test, and optimize their code. A developer just needs to ask Amazon Q for help (e.g., “Optimize my selected DynamoDB query), and Amazon Q provides a natural language description of its suggestions along with the accompanying code a developer can implement in one click.
Additionally, Amazon Q gives developers access to powerful capabilities to solve common challenges, further simplifying application development and maintenance, including:
- Develop features faster: If a developer wants to add a new feature to an application today, they need to go through the time-consuming process of mapping out a plan, thinking through the programming logic, writing the code and tests, and integrating it into the codebase, making small changes across potentially thousands of lines of code. With the feature development capability, developers can get guided assistance and automate much of the end-to-end process. From Amazon CodeCatalyst, AWS’s unified software development service for teams, a developer assigns Amazon Q a backlog task from their issues list, and Amazon Q then drafts a step-by-step plan, writes the code, and presents a developer with the suggested changes to implement the feature—a developer only needs to review the suggestions, make any necessary adjustments, approve the update, and deploy it.
- Amazon Q Code Transformation: Many developers today spend hours on application maintenance and upgrades, leaving less time for writing code or building new applications. While these upgrades can be important for application security and performance improvement, they often require months or years for developers to go through every line of code making updates. With Amazon Q Code Transformation, developers can remove a lot of the heavy lifting of this process, reducing the time required from days to minutes. A developer just opens the code they want to transform in their IDE and asks Amazon Q to “/transform” it. Amazon Q then analyzes the codebase, identifies and updates its dependencies, generates the new code language, incorporates the latest security and performance enhancements, and tests to validate the application will run. Recently, a small team of five Amazon developers used Amazon Q Code Transformation to upgrade 1,000 production applications from Java 8 to Java 17 in just two days. The average time per application was less than 10 minutes. Amazon Q Code Transformation currently supports language upgrades from Java 8 to Java 17, and .NET Framework to cross-platform .NET upgrades coming soon, with even more transformations to follow in the future.
Amazon Q is an expert on a customer’s business
Organizations are sitting on vast amounts of information spread across multiple documents, systems, and applications. From finance and human resources to marketing and sales, employees across every organization collectively spend hours every week searching internal sources for information, piecing together analyses, writing reports, building presentations, or adapting content for different customers or audiences. Generative AI can help solve these challenges, but the general-purpose solutions available today are not connected to internal resources and do not understand a company’s existing identities, roles, and permissions to determine which resources an employee should have access to for their work. Publicly available solutions may also use data inputs and outputs for training, opening companies up to security and privacy risks, which has led to some organizations banning these offerings. While there are some generative AI solutions designed to work with a specific set of productivity tools, they only work within those tools and do not extend across all of an organization’s systems and applications. Because of these barriers, employees have been unable to tap into the full potential of generative AI.
Customers can connect Amazon Q to their business data, information, and systems, so it can synthesize everything and provide tailored assistance to help employees solve problems, generate content, and take actions relevant to their business. With more than 40 built-in connectors for popular data sources, including Amazon S3, Dropbox, Confluence, Google Drive, Microsoft 365, Salesforce, ServiceNow, and Zendesk, as well as the option to build custom connectors for internal intranets, wikis, run books, and more, Amazon Q makes it fast and easy for customers to get started. Once Amazon Q synthesizes all the information it’s connected to and a customer is ready to deploy their own assistant, Amazon Q generates a web application that employees can access using a customer’s existing authentication system. Amazon Q uses the authentication system to understand a user, their role, and what systems they are permitted to access, so employees can ask detailed, nuanced questions and get tailored results that only include information that the user has access to view. Employees can ask Amazon Q about anything they would have to historically search for across different data sources (e.g., “What are the latest guidelines for logo usage?”), and Amazon Q will synthesize the relevant content, sharing answers and links to sources. Amazon Q can also streamline day-to-day communications, helping employees with tasks like generating a blog post, summarizing documents, drafting emails, and creating meeting agendas. Employees can also use Amazon Q to complete tasks in popular systems like Jira, Salesforce, ServiceNow, and Zendesk. For example, an employee could ask Amazon Q to open a ticket in Jira or create a case in Salesforce.
Amazon Q provides answers and insights that are accurate and faithful to the source material and knowledge a customer provides it, and customers can use additional administrative controls to block entire topics and filter both questions and finalized answers using keywords. Administrators can also limit certain responses to specific employees or data sources. For example, Amazon Q can be set to only respond to security-related questions from the security team or pull answers to people-related questions from a company’s internal directory.
Amazon Q provides generative AI-powered assistance across Amazon QuickSight, Amazon Connect, and AWS Supply Chain
While many use cases and industries will benefit from the transformative potential of generative AI, the solutions available today are often generic and do not have the specific context needed to carry out domain-specific tasks. To unlock the full benefit of generative AI, customers need access to purpose-built solutions adapted to the nuances of their use case or industry. That is why AWS is bringing Amazon Q to multiple services and applications, including:
- Amazon Q is in Amazon QuickSight (preview): Amazon QuickSight is a unified BI service built for the cloud that offers interactive dashboards, paginated reports, and embedded analytics, plus natural-language querying capabilities. With Amazon Q in QuickSight, customers can access generative AI-powered capabilities to build dashboards and more easily use existing dashboards to simplify decision making using data stories, inform business stakeholders of changes, and distill key insights. With the new story generation feature, users can ask Amazon Q to “build a story about how the business has changed over the last month for a business review with leadership.” In seconds, Amazon Q creates a data-driven, visually compelling story based on the available data in QuickSight that users can further customize and share throughout their organization. Additionally, with new executive summaries on dashboards and reports, Amazon Q creates at-a-glance summaries that highlight what is important to pay attention to in a dashboard. Business users can also use a new, streamlined question-and-answering experience where they can ask exploratory questions and generate relevant answers not limited to the visuals in their dashboards and reports. For example, a user could ask, “Why did the number of orders increase last month?” and Amazon Q would summarize the details in a dashboard created on the fly with supporting visuals.
- Amazon Q is in Amazon Connect (generally available): Amazon Connect is the cloud contact center that enables organizations of all sizes to deliver superior customer experiences at lower cost. Contact center agents play a critical role in helping organizations build customer trust and loyalty by guiding customers through complex decisions, but it is challenging to onboard, train, and coach employees to become high performers and ensure they have the information they need to respond to customers quickly and accurately. Amazon Q in Connect detects customer issues based on the real-time conversation between the customer and agent, and automatically provides the agent responses, suggested actions, and links to relevant articles. By empowering agents to address customer needs across a broad range of topics without assistance from supervisors, Amazon Q in Connect increases customer satisfaction while reducing agent training, resolution time, and cost. For example, Amazon Q could detect a customer is contacting a rental car company to change their reservation. Amazon Q would then generate a response the agent could send detailing the company’s change policies and guide the agent through the step-by-step process of updating the reservation. To learn more about Amazon Q in Connect, see the Amazon Connect press release.
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Amazon Q is in AWS Supply Chain (coming soon): AWS Supply Chain is a cloud-based application that gives customers insights into their supply chain by combining Amazon’s nearly 30 years of supply chain experience with the resilience, security, and business continuity of AWS. Many customers are looking for a more intuitive way to understand how inventory changes upstream and downstream could impact their future operations. With Amazon Q in AWS Supply Chain, customers will be able to ask “what,” “why,” and “what if” questions about their supply chain data, visualize outcomes of complex scenarios, and ask follow-up questions to understand the tradeoffs between different decisions. For example, a customer could ask “What is causing the delay in my shipments and how can I speed things up?” and Amazon Q could provide an analysis of a customer’s supply chain that notes most of the orders were on the East Coast, a storm caused a delay, and they could expedite their deliveries and reduce costs by shipping to
New York instead ofMiami . To learn more about Amazon Q in AWS Supply Chain, see the AWS Supply Chain press release.
Accenture, an AWS Premier Tier Services Partner, is a leading global professional services company with resources focused on accelerating end-to-end adoption of AWS and maximizing enterprise-wide transformation, securely, at speed and scale. “Amazon Q will be transformational for Accenture as we continue to work closely alongside AWS to accelerate the adoption and deployment of generative AI technologies amongst our own engineers and with organizations around the world,” said Karthik Narain, group chief executive at Accenture. “Our latest research shows nearly all C-suite executives expect generative AI to be transformative for their company and their industry, so we are investing now to get ahead of the curve by enabling up to 50,000 of our software developers and IT professionals with Amazon CodeWhisperer and Amazon Q over the next two years. With Amazon CodeWhisperer, we have already seen a
BMW Group is a German multinational manufacturer of luxury vehicles and motorcycles. “BMW teams need to ingest and interpret new data quickly to deliver the precision experiences our customers expect,” said Christoph Albrecht, data engineering and analytics consultant at BMW Group. “New Amazon Q capabilities in QuickSight help our analysts build dashboards in hours when it used to take days. We are seeing an even greater impact with our business users, where Amazon Q in QuickSight is accelerating critical business decisions at the highest levels of our organization by enabling on-the-fly answers to time-critical questions. The stories feature also enables us to present a clear picture of the business for board meetings, building insightful, professionally formatted stories fast. Amazon Q in QuickSight is the high-performance fuel our demanding teams consume to get precision answers fast."
Gilead Sciences, Inc. is a biopharmaceutical company that has pursued and achieved breakthroughs in medicine for more than three decades, with the goal of creating a healthier world for all people. “Gilead's use of generative AI on AWS has led to faster innovation and productivity gains,” said Kevin Cox, chief cloud architect at Gilead. “By leveraging Amazon Q, we can generate insights and accelerate analysis of large amounts of data across our enterprise. Overall, Amazon Q provides a faster way to create generative AI solutions by streamlining connections to our data sources, automating complex tasks, such as managing vector stores, and quickly surfacing relevant insights on demand. For life sciences organizations like Gilead, the productivity benefits unlocked by generative AI solutions on AWS like Amazon Q are exciting.”
Mission Cloud is an AWS Premier Services Partner that empowers businesses to invent a greater future in the cloud by leveraging the leading cloud platform. “Our team of cloud experts regularly works with the breadth and depth of AWS technologies to help customers manage, modernize, and optimize their cloud environments or build entirely new applications,” said Jonathan LaCour, CTO at Mission Cloud. “While AWS gives us the infrastructure, tools, and services we need to delight our clients, there is still a lot of undifferentiated work in the software development process outside of working with AWS services. With capabilities to automate new feature development, remediate errors, and even upgrade applications, Amazon Q will give our developers time to focus on adding even more value to the work we do with clients. Long-term projects to upgrade applications will likely shrink to days, and we can accelerate shipping new features when managing legacy applications, despite starting with no prior documentation or guides. Amazon Q will help us more efficiently build, deploy, and operate workloads on AWS for our customers.”
Orbit Irrigation is a manufacturer and supplier of home and commercial irrigation systems. “In order to resolve customers’ questions, our agents spend 2-3 minutes per interaction searching through several different sources of knowledge, including Orbit product pages, customer account pages, and internal knowledge forums,” said Brian Dick, senior manager of Customer Care at Orbit Irrigation. “This multistep process adds time to the interactions for agents and customers. The new responses automatically generated at each turn of the customer conversation by Amazon Q in Connect are tailored based on our own knowledge base articles. Amazon Q in Connect will create
Wunderkind is a leading digital marketing platform that delivers performance marketing and advertising solutions to brands, publishers, and advertisers. “We have an unbelievable amount of proprietary data, but it is difficult looking across our multiple data silos to find the right answer and distill the information into quick, actionable insights,” said Richard Jones, chief revenue officer at Wunderkind. “Adding Amazon Q as a topline layer over our various content and data repositories brings a whole new level of efficiency to our customer success and marketing teams. Based on initial estimates, we expect the time spent on content discovery alone to be reduced by over
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