Buyer’s Guide for
Data Annotation
and Data Labeling

Accelerate Your AI / ML Development

So, you want to start a new AI/ML initiative and are realizing that finding good data will be one of the more challenging aspects of your operation. The output of your AI/ML model is only as good as the data you use to train it – so the expertise you apply to data aggregation, annotation, and labeling is of critical importance.

Deciding how to generate, acquire, or license your training data is a question every executive will need to answer and this buyer’s guide was designed to help business leaders navigate their way through the process.

In this buyer guide you will learn:

• How to determine which types of AI data work to outsource
• Best practices to accelerate and scale high-quality AI training data
• Critical decision points in a “build vs. buy” scenario
• The three key stages of data annotation and labeling projects
• Level of vendor involvement and quality control mechanisms