Defining the right data strategy

Designing a data strategy that works for your AI project can make all the difference — both by producing significantly higher quality training data, and by saving time and reducing costs. Learn step-by-step how to design and implement a customized data strategy for your organization using methods developed over 30+ years of experience in the data annotation field.

What you’ll find:

  • Six factors of data quality and how they’re impacted by the annotation process
  • Framework for AI project analysis and how to assess project requirements and limitations
  • Method for estimating the amount of training data necessary
  • Comparison of various data annotation approaches as they affect security and privacy
  • A checklist of data strategy tasks to facilitate decision making
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Defining the right data strategy

Let’s work together to build smarter AI

Whether you need help sourcing and annotating training data at scale, or you need a full-fledged annotation strategy to serve your AI training needs, we can help. Get in touch for more information or to set up your proof-of-concept.
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