Amazon Q enterprise AI chatbot is now generally available
According to early stats, Amazon Q has the potential to help enterprise users become more than 80% more productive at their jobs. …
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Amazon Q, the work-centric generative AI assistant from Amazon Web Services (AWS), has become generally available, as enterprises race to leverage large language models (LLMs) in their workflows to power different use cases, including knowledge retrieval, conversation, software development and more.
Amazon describes it as the “most capable gen-AI-powered assistant for software development and navigating companies’ internal data” on its YouTube account and posted a video showing some of the tasks it can accomplish, but it has yet to release benchmarks showing its performance compared to other leading LLMs.
This can span from assisting across software development efforts to querying internal data for analysis, building reports and much more.
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Swami Sivasubramanian, the VP of AI and Data at AWS, described it as “the most capable generative AI-powered assistant” that can drive productivity for both developer and business users with its accuracy, advanced agent capabilities, and best-in-class security. Q will even help teams create new generative AI apps for various needs.
What does Amazon Q bring to the table?
In all, three key aspects of Amazon Q are hitting general availability today: Amazon Q Developer, Amazon Q Business and Amazon Q Apps.
The first product, as the name suggests, is the developer-centric version of the assistant that sits in the development environment and generates code in response to natural language commands. AWS says it comes with multi-step planning and reasoning capabilities to string together multiple requests and can also handle other tedious coding tasks, including testing, upgrading application code, troubleshooting and debugging coding conflicts, performing security scanning and fixes and optimizing AWS resources. All the user has to do is ask Amazon Q to perform the required task, and it will handle the rest.
According to Andy Jassy, the president and CEO at Amazon, repetitive coding tasks take approximately 70% of the developers’ time, keeping them from handling other more critical functions in their role. With Q, however, they get that much-needed headroom back. He said Q can already save months when moving from older versions of Java to newer ones and will also be able to execute .net transformations in the future.
Amazon Q Developer is priced on a software-as-a-service (SaaS) subscription model with a free tier (limited to 50 interactions per month) and a more full featured and less limited pro tier at $19 per month.
The other two products hitting GA today – Amazon Q Business and Amazon Q Apps – focus on the business side of things, specifically driving value from the massive trove of information stored across enterprise documents, apps and systems.
Amazon Q Business collates and analyzes information from all distributed sources within an enterprise and uses that data to provide answers to business users in plain natural language. AWS says enterprise users can ask questions about anything related to the day-to-day operations of their company, be it internal policies, product updates, or specific business results.
Q will simply take the query, search for the data, summarize and analyze it and subsequently provide the answer in the conversation. It can even assist with time-consuming tasks like writing reports and preparing presentations, the company added.
Q Business is priced at $3 per user per month for a “lite” tier that offers a text-based chatbot and $20 per user per month for the Pro tier, which includes content generation capabilities and many other integrations, features, and Q Apps.
Meanwhile, Q Apps is an extension of Q Business that enables users to create dedicated generative AI apps with natural language prompts.
These custom apps, unlike Q Developer and Business, will focus on a specific use case and use only the data repository pointed out by the user. This will eventually give every team the power to build gen AI apps to automate and accelerate different aspects of their workflows.
Q assistant already driving efficiencies
While Amazon Q has just become generally available, Jassy says early customers and partners across all industries are already using the assistant to transform how their employees work.
Some notable beta testers include Brightcove, British Telecom, Datadog, GitLab, GoDaddy, National Australia Bank, NCS, Netsmart, Slalom, Smartsheet, Sun Life, Tata Consultancy Services and Toyota.
“Early indications signal Amazon Q could help our customers’ employees become more than 80% more productive at their jobs; and with the new features we’re planning on introducing in the future, we think this will only continue to grow,” Sivasubramanian noted.
With the widespread availability and new capabilities in the pipeline, it will be interesting to see how Amazon Q fares against Microsoft, which has been going all in with its Copilot offering – focusing on both enterprises and consumers. The company already offers Copilot for Azure to simplify how teams design, operate, optimize, and troubleshoot apps and infrastructure from cloud to edge. Back in February, it even launched Copilot for Finance, an AI-powered assistant designed specifically for finance professionals.
Google, on its part, is also racing to push generative AI front and center across its products, including the Google Cloud Platform.
