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DatologyAI automates data curation for AI model training, helping teams train better models with less compute.
Raised $58M across disclosed rounds.[12][11][1]
Series A closed May 2024, led by Felicis Ventures.[1][11][3]
post-money valuation is not publicly disclosed.
Named investors include Felicis Ventures, Amplify Partners, Radical Ventures, M12 (Microsoft), Amazon Alexa Fund, Elad Gil, Conviction Capital, Outset Capital, Quiet Capital.[1][2][4][11]
Ari Morcos, CEO and Co-Founder[8][9][10]
Matthew Leavitt, Chief Science Officer and Co-Founder[8][9][10]
Bogdan Gaza, CTO and Co-Founder[8][9][10]
Ari Morcos, CEO and Co-Founder[8][9][10]
Matthew Leavitt, Chief Science Officer and Co-Founder[8][9][10]
Bogdan Gaza, CTO and Co-Founder[8][9][10]
Jun 2026 · siliconangle.com
reported
Jun 2026 · techcrunch.com
reported
Jun 2026 · felicis.com
reported
Jun 2026 · siliconangle.com
reported
DatologyAI automates data curation for AI model training, helping teams train better models with less compute.
CleanLab · cleanlab.ai · Same buyer (AI teams) and same workflow (data curation for model training), but CleanLab focuses on label quality and data error detection rather than petabyte-scale pretraining data selection.[2]
Labelbox · labelbox.com · Same buyer (AI teams) and adjacent workflow (data preparation), but Labelbox is primarily a human-in-the-loop labeling platform, not automated petabyte-scale curation.[2]
Galileo · rungalileo.io · Same buyer (AI teams) but different workflow: Galileo focuses on model evaluation and observability rather than pretraining data curation.[2]
YData · ydata.ai · Same buyer (AI teams) and adjacent workflow (data quality), but YData focuses on synthetic data generation rather than selecting from existing petabyte-scale datasets.[2]
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Jun 2026 · outsetcapital.com
reported