Tool overview
NannyML is listed under AI Infrastructure & MLOps AI tools.
What is NannyML?
NannyML provides an Apache-2.0 Python library and commercial monitoring platform for estimating model performance without immediate labels, detecting drift and data-quality problems, ranking issues, and triggering corrective workflows.
Best for
ML teams monitoring production models with delayed ground truth
Who is it for?
Decision note
Rebuilt from the original export under the complete V412/V411 factual-source-verification workflow. Preview only. Apply remains blocked until Failures = 0, Warnings = 0, Unmapped = 0, Missing = 0; explicit clears are reviewed; image import is disabled; a representative WordPress edit screen is compared with the export and proposed row; and a post-Apply zero-change Preview succeeds.
Key features
Performance estimation without immediate targets
Concept, prediction, target, and feature drift detection
Data-quality monitoring and root-cause analysis
Cloud, customer-cloud, and open-source deployment choices
Use cases
Monitor tabular machine-learning models
Detect silent model degradation
Prioritize retraining and investigation
Track business value and data-quality issues
Pros
- Apache-2.0 open-source library
- Thirty-day trials for commercial plans
- Managed and customer-cloud options
Limitations
Performance estimation is statistical and must be validated for each production use case.
Image, text, and video capabilities vary by commercial plan and configuration.
Pricing details
Billing options
Pricing note
The open-source library is free. Starter SaaS is $399/month for two models and 10 million predictions. Scale is $999/month for six models in the customer cloud. Both advertise 30-day trials; Enterprise is custom.
Supported languages
- English
Integrations
Python
Docker
Slack
Webhooks
Databases
Data pipelines
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