A Crowd Sourced Data Capture and Labeling Platform for Machine Learning Applications


Overview:NetLabeler is a platform for crowd sourced data capture and Machine Learning labeling. And if that didn't make any sense to you, you should really read our FAQ. We're sorry but the world of Machine Learning is kinda complex these days...


Status: NetLabeler is currently at beta state. Right now we are not accepting any further customers as all our efforts are being devoted to crowd sourcing data for the current COVID-19 crisis. You should see our web site. Please feel free to sign up for our launch mailing list.

NetLabeler can be used in two ways:


  • To capture data via crowd sourcing right down to embeddable forms that you can put into your external web application (think MailChimp™) but for data capture whether your crowd is an internal team or a large Internet scale crowd)
  • To label data for Machine Learning using all the standard approaches -- image labeling, attribute labeling, etc


Using NetLabeler, you can queue a set of web pages, view them, and extract and label information from the page. When all the pages are extracted, download the data through our API or in a CSV and use it to train your Machine Learning model.


Get help from employees or friends to build your data set. You can cross-check by having people extract links more than once. You can even use cats to label your data, although we don't recommend it.


© 2022 Cartazzi