A Human-in-the-Loop
There’s No Substitute for Human Judgment
Integrating human judgment in the data preparation process is the key to building AI that serves people better. We embed human-in-the-loop practices into critical moments in the data preparation process to reduce bias and improve data quality.
Curated Teams
Each project demands a specific set of expertise and skills. We curate your annotation team based on the exact needs of your project, from linguists to trained medical specialists.
Project managers
Annotation workforce
Guideline definition
Our project managers apply their understanding and experience working with annotator teams to define labeling guidelines that are well-explained, and easy for annotators to follow. These guidelines provide an excellent basis for high-quality annotation.
Need deeper support for creating guidelines that suit your model? See our strategy offering.
Continuous Feedback and Quality Assessment
Your project manager continuously monitors the quality of annotation according to the guidelines, gives annotators feedback, and refines the guidelines and procedures during the running process. This makes it possible to identify snags earlier and make improvements faster.
Model Evaluation
As a final human-in-the-loop check, we review the algorithmic output of the model and evaluate whether training data might be contributing to errors in the result. Depending on the findings, we can adapt guidelines or even revise parts of the annotation.
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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.