AI Infrastructure & MLOps Freemium

Cleanlab

Data quality and reliability tools for machine learning systems

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PricingFreemium
Starting priceContact sales
Free planYes
Free trialYes
APIYes
Open sourceYes
DeploymentHybrid
Last verifiedAugust 3, 2026
Overview

Tool overview

Cleanlab is listed under AI Infrastructure & MLOps AI tools.

Summary

What is Cleanlab?

Cleanlab provides open-source data quality algorithms and commercial controls for identifying label issues, unreliable examples, and risky AI outputs. Teams use it to find data errors, prioritize examples for review, improve training sets, and add quality controls around AI applications and agents.

Best fit

Best for

Data and AI teams improving quality, monitoring, governance, or evaluation

Audience

Who is it for?

Data scientistsML engineersData teamsAI governance teams
Recommendation

Decision note

Accepted for Preview after independent V411 official-source verification. Apply only after failures = 0, warnings = 0, unmapped = 0, Arabic v2 parity is valid, the logo result is reviewed, and all controlled fields, explicit clears, outreach evidence, affiliate evidence, rebrand status, and source notes are visually confirmed.

Capabilities

Key features

Label issue detection algorithms

Data quality scoring and ranking

Active learning and review prioritization

Support for classification and other modalities

Quality controls for AI application outputs

Open-source Python library and Studio

Workflows

Use cases

Cleaning training datasets

Finding mislabeled examples

Prioritizing human review

Improving model evaluation data

Reducing unreliable AI responses

Strengths

Pros

  • Established data-centric methodology
  • Open-source library for technical teams
  • Useful across several data modalities
  • Commercial platform for scaled workflows
Considerations

Limitations

Cleanlab can identify suspicious data and outputs, but domain experts must confirm errors, define acceptable quality, and evaluate downstream model impact. Human review and environment-specific validation remain necessary before production use.

Cost

Pricing details

Pricing modelFreemium
Starting priceContact sales
Free planYes
Free trialYes
Pricing context

Billing options

Free open-source libraryCustom commercial contract
Pricing context

Pricing note

The current cleanlab Python package is free under Apache-2.0. Cleanlab Studio and Trustworthy Language Model are commercial offerings whose public pages route buyers to the company rather than publishing a reliable base price. No distinct commercial free trial was confirmed.

View official pricing
Compatibility

Supported languages

  • English
Connectivity

Integrations

Python SDK

REST API

Specs

Technical details

PlatformsWeb, API
Multilingual supportUnknown
Login requiredYes
Open sourceYes
LicenseApache-2.0
DeploymentHybrid
CompanyCleanlab Inc.
Current version2.9.0
Models / versionscleanlab 2.9.0
Editions / planscleanlab open-source library Cleanlab Studio Trustworthy Language Model
Data confidenceHigh
Last verifiedAugust 3, 2026
Documentation → Source code → Release notes → Data source →
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Answers

Frequently asked questions

Cleanlab provides open-source data quality algorithms and commercial controls for identifying label issues, unreliable examples, and risky AI outputs. Teams use it to find data errors, prioritize examples for review, improve training sets, and add quality controls around AI applications and agents.
Data and AI teams improving quality, monitoring, governance, or evaluation
The listed pricing model for Cleanlab is Freemium. Pricing can change, so users should verify the latest plan details on the official website.
Yes. The current profile indicates that a free trial is available.
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