Data labeling refers to the process of assigning context and meaning to the data you’re training your AI algorithm on. The machine learning algorithm relies on the labels to understand and learn from the data it is processing.
Harness high-quality human data from professionals across math, science, computing, linguistics, data science, and many other backgrounds. Our data collection service is perfect for enterprises in any sector or industry and designed to scale with you.
Our professionals are able to quickly adapt to your in-house data labeling platform, while also possessing expertise in leading open-source platforms such as Intel’s CVAT, CSAIL’s LabelMe and Stanford's CoreNLP.
Our adaptable Latin American professionals bring an average of 5+ years of experience from their chosen field, with many hand-selected from top universities. Every talent in our platform is also rigorously vetted by our in-house AI model and our senior talent team.
High-quality human data to train your LLM or other ML model.
Utilize human feedback to optimize ML models for more efficient self-learning.
We collaborate with leading US firms like Dr Squatch and Check to grow their remote LatAm teams.