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Cleanlab

Data quality tools for finding and fixing errors in ML datasets

AI InfrastructureFounded 2021#36 of 54 in AI Infrastructure

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Company research

Current company data

No company research card is published for Cleanlab yet. The current company data below lists package and repository metrics AI-Buzz can inspect today; AI-Buzz publishes a card when recent public metrics show a measured change with dated evidence and cited sources.

Package downloads (30d)

77.5K/30d

Dependent projects

18

dependents · latest

GitHub stars

11.6K

Public importing repos

19

repos · latest

Note: Public metrics are incomplete, and current data alone does not prove a trend; they do not show private usage, paid use, customer count, or product quality.

Company profile

What is Cleanlab?

Cleanlab develops data-centric AI tools, including a no-code platform and an open-source Python library, to automatically find and fix errors in machine learning datasets. Their technology helps improve the reliability and performance of AI models by ensuring high-quality training data, addressing a critical challenge in the AI development lifecycle.

Latest company data

Metric dates vary by source

Metric dates
PyPI downloads
PyPI dependents
GitHub stars
Public GitHub repos using company packages

Key metric

Package downloads (30d)

77.5K/30d

Tracked package: PyPI cleanlab

▲ +3%

Additional metrics

3 metrics

Metric

Dependent projects

18

Projects depending on tracked package: PyPI cleanlab

Metric

GitHub stars

11.6K

Main repository stars

Metric

Public importing repos

19

Public GitHub dependency data for tracked company packages

Repository health

Maintenance data from the main open-source repository.

OpenSSF Scorecard
3.7
Releases (30d)
0

Repository usage

Public repositories and source files importing packages tied to Cleanlab.

Repos importing
190%

About Cleanlab

Cleanlab develops data-centric AI tools, including a no-code platform and an open-source Python library, to automatically find and fix errors in machine learning datasets. Their technology helps improve the reliability and performance of AI models by ensuring high-quality training data, addressing a critical challenge in the AI development lifecycle.

FoundersCurtis Northcutt, Jonas Mueller, Anish Athalye

Disclosed funding

Disclosed $30M · 2 rounds

Disclosed funding records total $30M. Category position #36 of 54 in AI Infrastructure.

Series A2023

Menlo Ventures, TQ Ventures

$25M
Seed2022

TQ Ventures

$5M

Investors

Menlo VenturesTQ Ventures

Tracked packages (1)

1 PyPI

cleanlab

PyPIMain PyPI package

cleanlab

Data quality tools for finding and fixing errors in ML datasets