Amazon Q AI, the latest innovation from AWS, has been unveiled by AWS CEO Adam Selipsky at AWS re:Invent. This revolutionary chat tool empowers businesses to seek tailored answers to their specific queries. Serving as an AI assistant, Amazon Q AI allows users to tap into their data for insights.
For instance, employees can leverage Amazon Q AI to inquire about the latest brand logo guidelines or decipher a fellow engineer’s code for app maintenance. Instead of laboriously sifting through numerous documents, Q AI efficiently surfaces the required information.
Is Amazon Q AI available now?
Accessing Amazon Q AI is a breeze, as users can utilize it via the AWS Management Console, their company’s documentation pages, developer environments such as Slack, and various third-party applications. Selipsky made it clear that the questions posed on Amazon Q AI “will not be used to train any foundation models.”
Amazon Q AI seamlessly integrates with any of the models available on Amazon Bedrock, AWS’s repository of AI models, which encompasses Meta’s Llama 2 and Anthropic’s Claude 2, among others. Customers who frequently utilize Q AI have the flexibility to select the model that aligns best with their needs. They can establish a connection to the Bedrock API for the chosen model, utilize it to gain insights into their data, policies, and workflow, and subsequently deploy Amazon Q AI.
AWS has underlined that Amazon Q AI draws upon 17 years’ worth of AWS knowledge, making it a valuable resource for addressing AWS-specific queries. It excels in recommending the optimal AWS services for various projects.
Presently, Amazon Q AI is exclusively accessible to Amazon Connect users, AWS’s service tailored for contact centers. However, the company has plans to extend its availability to other services, such as Amazon Supply Chain, designed to facilitate supply chain management tracking, and Amazon QuickSight, a platform dedicated to business intelligence. Notably, Amazon Q AI for supply chain and business intelligence is currently available in preview.
In an interview with The Verge, Dilip Kumar, Vice President for AWS Applications, explained that each instance of Amazon Q AI on AWS services will exhibit unique characteristics. For instance, on Amazon Connect, Q AI operates in real-time and actively listens to customer calls, extracting essential information like account details. It then provides contact center agents with pertinent answers to inquiries, eliminating the need for agents to search for information themselves.
“We wanted to pair the technology with the services that make the most sense first, and for contact centers, supply chain, and business intelligence, AI is a natural fit,” Kumar stated.
Amazon Q AI offers a compelling solution for businesses seeking efficient and tailored responses to their queries. AWS CEO Adam Selipsky’s announcement at AWS re:Invent has shed light on the promising capabilities of Amazon Q AI. This chat tool, which integrates seamlessly with models on Amazon Bedrock, empowers users to harness the power of AI to gain insights into their data, policies, and workflows. It represents a significant leap forward in the quest for streamlined information retrieval, sparing employees from the arduous task of manual document searching.
Amazon Q AI’s deep knowledge, drawn from 17 years of AWS expertise, positions it as a valuable resource for addressing AWS-specific inquiries and recommending optimal AWS services. While currently exclusive to Amazon Connect, AWS’s contact center service, it is slated for expansion to other services like Amazon Supply Chain and Amazon QuickSight.
In terms of pricing, Amazon Q AI in Connect is competitively priced at a starting rate of $40 per agent per month, and users have the opportunity to try it “for no charge until March 1, 2024,” according to AWS’s Connect website. Selipsky has emphasized that Amazon Q AI prioritizes security, respecting the parameters set by customers to ensure that unauthorized personnel cannot access sensitive information.
It’s worth noting that other companies have also ventured into similar territory with products like Microsoft’s Copilot, Dropbox’s Dash, and Notion’s AI-powered notes search feature.
As an additional announcement, AWS will offer Bedrock users the capability to implement guardrails around the models they use to build AI-powered applications. Currently in preview, these guardrails enable companies to enforce data privacy and responsible AI standards, a critical consideration for highly regulated industries like finance and healthcare. Furthermore, AWS plans to include the ability to redact personally identifiable information from customers’ end users as part of these guardrails, although this feature is not immediately available.
