Buyer’s Guide for
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