# Serve live, governed data in AI-built apps with Amazon Quick

> **Publication**: aitalky (Independent AI Journalism)
> **Canonical Citation URL**: https://aitalky.vercel.app/news/serve-live-governed-data-in-ai-built-apps-with-amazon-quick
> **Original Source**: [AWS ML Blog](https://aws.amazon.com/blogs/machine-learning/serve-live-governed-data-in-ai-built-apps-with-amazon-quick/)
> **Author**: Wei Kuo (undefined)
> **Published Date**: Thursday, October 1, 2026
> **Category**: RESEARCH
> **Tags**: AI, AWS ML Blog, research

## Executive Summary
With Live Data in Apps in Amazon Quick, AI-built apps query your governed Quick Sight datasets in real time instead of static, build-time snapshots. Each query runs as the person viewing the app, so row-level and column-level security apply per reader.



## Full Coverage
Quick Apps could already bring live data into an app from connectors and content sources: action connectors (services like Jira, Slack, and Google Drive), Spaces documents, web search, and AI inference all run at view time, not build time. The solution introduces live structured data from your data lakes, databases, and other analytics data stores

Your governed Amazon Quick Sight datasets, the SPICE and Direct Query tables that hold your business metrics, couldn't be queried live from an app. Any dataset numbers an app showed were baked in when the agent built it. A snapshot frozen at publish time

That was fine for a static report, but it broke down the moment you wanted an app whose metrics reflected what your data says today, and that respected who is allowed to see which rows

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