Introducing Humanloop Programmatic

Jordan Burgess

We’re delighted to offer early access to Humanloop Programmatic. A new kind of annotation tool that’s the fastest way to get annotated data for NLP.


Save time and cost by replacing manual labeling with rapid, programmatic labeling using Programmatic.

In working with hundreds of NLP teams over the last year, we've seen that getting annotated data is often the biggest bottleneck. Manual annotation is slow and expensive, and getting time from subject-matter experts can be difficult. As part of our mission is to solve this, we are making programmatic labeling accessible and practical.

With Programmatic, data scientists and machine learning engineers can label millions of datapoints in the time it would take to manually annotate hundreds.

It runs locally, keeping your data private.  You can explore your data with powerful search. And you can rapidly iterate on labeling functions to take best advantage of subject-matter expertise.

You can export your labeled data to your machine learning pipeline or you can export to Humanloop to train a model and improve your dataset with active learning.

Here’s how Programmatic works


Here’s what users are saying about Programmatic:

To understand more about how Weak Labeling can be so powerful read why I changed my mind about weak labeling for ML.

Programmatic is now in early access and you can sign up for immediate access for FREE using the following form.

Frequently asked questions
What is Programmatic?
Where can I find documentation for Programmatic?
What is weak supervision?

About the author

Jordan Burgess
Cofounder and Chief Product Officer
Jordan Burgess is a co-founder and Chief Product Officer of Humanloop. He is inspired to build AI systems that transform how we interact with computers. He helped build the AI systems powering Alexa at Amazon, and was an early ML Engineer at Bloomsbury AI (acq. by Facebook). Jordan has an MPhil in Machine Learning from Cambridge and studied Engineering and Computer Science at MIT.
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