The long-term success of an AI-based product relies on having the infrastructure for scalable, flexible, and cost-effective data labeling for its learning.

In this post, we'll look at five commonly used computer vision
annotation tools for item identification.

Here are a handful of recent case studies that show the power of data labeling in action.

Gartner identifies data labeling as one of the key factors responsible for the ongoing evolution of AI technology and rapid AI-powered product development. 

Get smarter at making your corporation effective by improving the accuracy of AI systems. Using data-centric approaches elevate machine learning models.

Data labeling and annotation is one of the biggest challenges businesses face in developing AI solutions. Here are the top 5 Data labeling mistakes.

Five underutilized ways you can leverage ML observability to make your production workflow more efficient: retraining workflows, deprecation, versioning...

'Innovate with Confidence: Expert Guidance in Advanced LLM Development' explores the strategies and insights for making the most of Language Learning Models.