Screenshot 2022-09-01 at 18.12.58

Best Practices In Collaboration & Project Management

                                                      The definitive guide for your data annotation projects

Download the whitepaper

High-quality training data is critical to delivering a successful AI-powered app.

But who says high-quality training data says... Data labeling, and likely: data labeling at scale. 

To make the various stakeholders imply work together efficiently

But getting this high-quality training data is no picnic.  Although necessary, the labeling process of raw unstructured is often perceived as a painful experience.

If any of these concerns ring a bell, this ebook on project management is for you! 

By reading the end of this step-by-step guide, you will be familiar with the best practices companies can emulate.

More and more products are powered by machine learning. That’s why it's [capital] to think about ethics and to make sure [its] impact [is] positive.“

Clément Delangue,
Co-founder & CTO
@Hugging Face

“Our Data-centric approach to AI has helped us achieve a categorization of our own categories that is accurate in more than ninety-five percents of the videos.”

Andrea Colonna,VP AI

But the real-world experience of those who put them into production shows that (...) it's often the quality of data (...) that makes your AI project succeed or fail.”

Edouard D'Archimbaud, Co-founder & CTO @Kili Technology

Screenshot 2022-09-01 at 18.12.58
Labeling Platform for High-quality Data
One tool to label, find and fix issues, simplify DataOps,
and dramatically accelerate the build of reliable AI