Datasaur, a startup that provides a platform for data scientists to label and train natural language processing (NLP) models, has announced that it has raised $4 million in a seed funding round led by Initialized Capital, a venture capital firm that invests in early-stage software companies.

The round also included HNVR, Gold House Ventures, and TenOneTen, bringing Datasaur’s total funding to date to $7.9 million.

Datasaur, which was founded in 2019 by CEO Ivan Lee, a former Google executive, provides an NLP comprehensive and automated data labeling solution to financial, legal, and healthcare companies to turn raw unstructured data into valuable machine learning datasets.

The company, which graduated from the Stanford StartX (F19) and YCombinator (W20) accelerators1, has also launched a new feature, Datasaur Dinamic, which allows users to train custom NLP models with a click of a single button.

Datasaur plans to use the new capital to advance its NLP data labeling and model-building process efficiency for data scientists. The company also aims to democratize access to the latest advancements in NLP and large language models (LLM) technology, which enable machines to understand and generate natural language.

Ivan Lee, founder and CEO of Datasaur, said: “We are thrilled to have the support of Initialized Capital and our existing investors to accelerate our vision of building the future of NLP. We believe that data labeling and model training are the key steps in the NLP development cycle, and we are excited to bring our platform to more customers and industries.”

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