Cleanlab
Data-centric AI platform that automatically finds and fixes label errors and data issues in tabular, text, and vision datasets.
Our Verdict
The go-to when dataset quality — not model choice — is limiting your metrics.
Pros
- Finds label errors across text, vision, tabular
- Research-backed confident-learning algorithms
- Works with existing pipelines
Cons
- Requires labeled dataset to start with
- Value drops with already-clean datasets
- Enterprise pricing gets steep
Best for: ML teams debugging accuracy ceilings caused by label noise
Not for: Teams with already-clean data or no labeled ground truth yet
When to Use Cleanlab
Good fit if you need
- Finding label errors in training datasets before fine-tuning
- Estimating data quality scores for ML dataset audits
- Cleaning noisy text classification datasets with Datalab
- Improving model accuracy by fixing mislabeled training examples
Lock-in Assessment
Low 4/5
Lock-in Score 4/5
Pricing
Price wrong?Cleanlab Pricing
- Pricing Model
- freemium
- Free Tier
- Yes
- Entry Price
- —
- Enterprise Available
- No
- Transparency Score
- —
Beta — estimates may differ from actual pricing
1,000
1001K10K100K1M
Estimated Monthly Cost
$25
Estimated Annual Cost
$300
Estimates are approximate and may not reflect current pricing. Always check the official pricing page.
Project Health
D
Health Score
11.4k 887
Bus Factor
10
Last Commit
3 months
Release Freq
142d
Open Issues
103
Issue Response
N/A
License
Apache-2.0
Last checked: 2026-04-21
Community Discussion
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