How to improve data classification with live web data

Most AI roadmaps now include a slide called “Data Classification.” Few teams talk about what those labels are actually sitting on. Classification is how teams bring structure and governance to messy data: from product pages and reviews to transaction records. In practice, that layer often runs on partial, outdated slices of the truth: last month’s exports instead of live PDPs, a narrow slice of reviews rather than the full stream, and internal records with little context from the open web. When the underlying data is this thin or out of date, you do not just get noisy labels; you lose the trust and auditability classification was meant to create. Nimble’s 𝗪𝗲𝗯 𝗦𝗲𝗮𝗿𝗰𝗵 𝗔𝗴𝗲𝗻𝘁𝘀 are built to close that gap. They turn live web pages into structured inputs your classification layer can govern and audit with confidence. They capture full product, price, and content context across retailers, keep labels in sync with what is actually on the shelf and on the page, and keep your AI and governance workflows fed with continuously refreshed external data. 📍If you are heading to Databricks Data + AI World Tour in Chicago on November 19 and working on data classification, governance, or external data pipelines, come find our own Josh Farber. He will be there to show how real-time web data turns classification from a static checklist into a live control layer. 📌 If you will not be there but want to run this on your own classification or governance stack, you can reach us on Slack: https://lnkd.in/dDkv3fSP 👋 See you there