Cleanlab Raises $25M Series A Funding to Enhance Data Curation Solutions


Cleanlab, the innovators behind an automated data curation solution vital for enhancing the value of data points in enterprise artificial intelligence (AI), large language models (LLM), and analytics solutions, have successfully secured $25 million in Series A funding. Co-led by Menlo Ventures and TQ Ventures, with participation from existing investor Bain Capital Ventures (BCV) and new investor Databricks Ventures, this funding round brings Cleanlab’s total funding to $30 million.

Cleanlab’s solution significantly boosts profitability by improving the quality of data, a crucial factor for data-driven analytics and generative AI solutions. Bad data incurs significant costs, with over $3 trillion lost in the U.S. alone, and 80% of enterprise time spent manually enhancing data quality. Cleanlab is the first enterprise solution that automatically adds smart metadata, transforming messy, real-world data into valuable inputs for various models.

Their technology identifies issues, increases reliability, and boosts profit margins by avoiding costly data quality and annotation processes for most data.

Developed by Cleanlab’s founders, who hold PhDs in Computer Science from MIT and are published researchers, the company’s proprietary automated data curation platform, Cleanlab Studio, is used by over 10% of Fortune 500 companies and innovative startups. Cleanlab Studio has introduced new features addressing unreliable LLM outputs and launched its Trustworthy Language Model (TLM), which enhances the reliability of LLM outputs and generated content.

Cleanlab’s CEO, Curtis Northcutt, emphasized the significance of data curation: “It’s the culmination of over a decade of work to introduce Cleanlab Studio, which reimagines what AI and analytics can do for people and enterprises now that we can automate data curation and reliability.”

The investment will enable Cleanlab to expand its offerings and continue pioneering data-centric AI solutions.

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