Amazon unveils Q, an AI-powered chatbot for businesses

Amazon unveils Q, an AI-powered chatbot for businesses

Amazon is launching an AI-powered chatbot for AWS customers called Q.

Announced during a keynote at Amazon’s re:Invent conference today, Q can answer questions like “how do I build a web application with AWS.” Trained on 17 years’ worth of AWS knowledge, it’ll offer a list of potential solutions along with reasons why you might consider each of these proposals.

“You can easily chat, generate content and take actions,” AWS CEO Adam Selipsky said onstage. “It’s all informed by an understanding of your systems, your data repositories and your operations.”

AWS customer configure Q by connecting it to — and customizing it with — organization-specific apps and software, like Salesforce and Amazon S3 storage instances. Q indexes data and content, “learning” and indexing aspects about a business — including core concepts, product names and organization structure.

From a web app, users can ask Q to analyze, for example, which product features customers are struggling with and possible ways to improve them, or upload a file (a Word doc, PDF, spreadsheet and the like) and ask questions about that file. Q then draws on its connections and data, including business-specific data, to come up with a response along with citations.

Q then uses all of the business context available to find relevant data, information and documents and picks the best ones before combining everything together into a response all in just a fraction of a second using the power of generative AI.

Q goes beyond simply answering questions. The assistant can take actions on a user’s behalf through a set of configurable plugins, like automatically creating service tickets, notifying particular teams in Slack and updating dashboards in ServiceNow. To prevent mistakes, Q has users inspect any actions it’s about to take before they run and link to the results for verification.

Integrated in the AWS Management Console as well as existing chat and business apps like Slack, Q can understand the nuances of app workloads, suggesting AWS solutions and products for apps that only run for a few seconds, for instance, or very infrequently access storage.

Onstage, Selipsky gave the example of an app that need high performance for video encoding and transcoding. Asked about the best EC2 instance for the app in question, Q would present a list taking into account performance and cost considerations, Selipsky said. 

Q can also troubleshoot things like network connectivity issues, analyzing network configurations to provide remediation steps.

And Q ties in with CodeWhisperer, Amazon’s service that can generate and interpret code. Within a supported IDE (e.g. Amazon’s own CodeCatalyst), Q can generate tests to benchmark software — drawing on knowledge of a customer’s code. Amazon Q can create also create a draft plan for implementing new features in software, or transforming code and upgrading code packages, repositories and frameworks — plans that can be refined and even executed using natural language.

Selipsky says that Amazon used Q internally to upgrade around 1,000 apps from Java 8 to Java 17 — and test those apps — in just two days.

Amazon is also building Q into first-party products like QuickSight, the company’s business analytics service. Q can provide visualization options for business reports, automatically reformatting them. Or it can answer questions about data in a report.

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