Amazon Quick
AI-powered workspace for data analysis, dashboards, automation, and research, evolved from Amazon QuickSight
Amazon Quick is a workspace where you ask for things in plain English and AI agents do them: analyze your data, build dashboards, automate busywork, run research, even build small web apps. Picture a new hire who reads all your company data on day one and never sleeps. You type what you want, like show me last quarter's sales by region, and Quick queries the connected databases and draws the chart. Need a report on a competitor? It reads the web and your documents and hands back a cited summary. Repetitive task? Describe it once and Quick Automate handles it. The dashboarding part, called Quick Sight, is the piece AWS built first: it connects to Redshift, Athena, RDS, and S3, caches data in memory for fast charts, and scales to thousands of viewers. You can start free on the web with just an email, no AWS account, or run it inside your company's AWS billing.
Quick runs through a chat interface where AI agents act on connected data. Its six features: Quick Sight for dashboards, Quick Flows for AI workflows, Quick Automate for business-process automation, Quick Index for grounding answers in your documents, Quick Research for cited reports across the web and your data, and Apps for building web applications from plain-language descriptions. Connections use knowledge bases, action connectors, and structured data links; open standards like MCP and OpenAPI reach internal systems. Two access paths: a self-serve plan at aws.com/quick with free and paid tiers requiring no AWS account, or console provisioning with IAM Identity Center and per-user AWS billing. Quick is reachable from web, desktop, Chrome, Slack, Teams, and M365.
Key Capabilities
- Natural-language chat drives AI agents that analyze connected data, automate tasks, build web apps, and run cited research
- Quick Sight business intelligence: interactive dashboards on S3, Athena, RDS, Redshift, and third-party sources, with SPICE in-memory caching and row-level security
- Quick Flows and Quick Automate handle repetitive work with AI-powered workflows and business-process agents that act across connected applications
- Quick Index grounds AI responses in your organization's documents and data sources
- Apps in Quick: describe a web application in plain language and Quick builds a working interactive app
- Works from web, desktop, Chrome, Slack, Teams, and Microsoft 365; start self-serve with just an email or provision through AWS with IAM Identity Center
Gotchas & Constraints
Gotcha #1: the dashboard engine under Quick Sight is still SPICE, which caches datasets up to 2TB or 2 billion rows; larger or second-fresh data needs direct query and slower dashboards. Gotcha #2: self-serve and AWS-provisioned accounts are separate; dashboards and billing do not move between them. Constraints: QuickSight APIs and SDKs keep working unchanged, and agents act only with each connector's granted permissions.
A retail company needs executive dashboards plus a weekly competitor report. They provision Amazon Quick through the AWS console and connect Redshift (sales), Athena (clickstream), and RDS (inventory). Analysts build sales-by-region maps, product rankings, and trend lines in Quick Sight, with row-level security so each store manager sees only their region. Quick Index ingests the merchandising wiki, so executives ask plain-language questions like why did Pacific Northwest sales dip and get answers grounded in both the dashboards and the wiki. Every Monday, a Quick Research run compiles a cited competitor summary, replacing four analyst-hours of manual clipping. They embed the dashboards in their supplier portal; 100 executives view read-only, 10 analysts build analyses.
The Result
dashboards live in 2 weeks instead of months, the Monday report is fully automated, and Quick serves thousands of viewers on the same datasets without a data warehouse to manage.