Amazon Web Services launched Amazon Quick Suite, which combines Amazon Q Business features with Amazon Quick Sight as well as new capabilities for automation and research in a move to bolster business user and AI agent collaboration.
The platform is designed to bridge the gap between AI proof-of-concepts and production deployments. In many ways, Amazon Quick Suite reflects the current playbook for AWS. AWS has been combining building blocks into suites and unified platforms that are easier to consume.
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Amazon Quick Suite includes these primary functions and features:
- Information gathering from multiple enterprise unstructured data stores with connectors to Amazon S3, SharePoint, Exchange, Google Drive and others. Data is shared via APIs and Model Context Protocol (MCP). Amazon Quick Suite also leverages structured data from CRM, ticketing systems and other enterprise systems.
- Hypothesis testing with specialized data sets.
- Decision automation via repeatable workflows, or what AWS calls Flows, which is aimed at business users to automate routine tasks. Amazon Quick Suite also includes Quick Automate, which enables technical teams to handle complex, multi-agent, mission-critical processes.
- A user interface agent to help business users stitch together agents and orchestrate them. UI Agent is a part of Quick Automate and Flows and can be used to interact across websites and business apps.
- A built-in research agent that can produce comprehensive reports with verified sources and analytics on business strategy, pricing and market analysis across any industry.
- All of the business intelligence capabilities of Quick Sight including dashboards and reports that can be created and queried with natural language.
- Monitoring, logging and observability so admins have visibility into workflows and AI agents.
- The ability to use multiple models via Amazon Bedrock. For default tools like built-in agent and chat agent, AWS steers users to models based on high quality responses. Model flexibility is available in Flows, where users can adjust settings for speed, comprehensive responses and deep reasoning. In Quick Automate, customers have full control and can set up their own Bedrock connector and select any model. API connectors can connect to non-Bedrock models and agents on and off AWS with MCP servers.
In a demo, Amazon Quick Suite was able to pull insights and recommend workflows across five to six enterprise systems in about 5 minutes. That output generally saved 30 minutes to 45 minutes to complete without Amazon Quick Suite or manual operations.
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According to AWS, Amazon Quick Suite is designed specifically for business users with the ability to create workflows with natural language, pre-built integrations and a browser extension to meet customers where they work. Amazon Quick Suite is a horizontal approach to AI agents as AWS leverages its hyperscale cloud footprint to work across various enterprise applications and data stores.
"At a high level, we're empowering every business user regardless of technical skill and experience with generative AI to make better decisions faster," said John Brock, Head of Product, Apps and Automation AWS Agentic AI. "We also want to enable them to take action directly where they are working without having to switch between different tools."
Some of the prebuilt integrations include:
- Atlassian.
- Asana.
- SAP.
- ServiceNow.
- Salesforce.
- Microsoft Outlook, Teams.
- HubSpot.
- Marketo.
- Microsoft SharePoint, OneDrive, Google Drive and Amazon S3 storage and collaboration.
- OpenAI Specification.
- Amazon Athena, Redshift and DynamoDB.
- Slack and email.
Amazon Quick Suite supports API actions, MCP connectors, integration with existing enterprise systems and connections to agents.
With pricing of $20 per business user a month at professional scale, Amazon Quick Suite is priced on par with plans for large language model chat tools and brings together structured and unstructured data with context. Amazon Quick Suite will run $40 per user per month for a power user who would conduct a lot of research volume and build complex dashboards and technical automations.
