product
Data quality: Editorially ReviewedSoftware & technology
Workflow orchestration
Observability
Self-hosted / on-premises
MLOps & model tooling
Predictive / classical ML
Freemium
SaaS (vendor-hosted)
NannyML
Observability
Overview
NannyML is an open-source library for post-deployment machine learning monitoring that estimates model performance without access to ground truth labels. It uses confidence-based performance estimation (CBPE) and direct loss estimation (DLE) to detect silent model failures. NannyML provides drift detection, performance estimation, and alerting for production ML models.
- Pricing model
- Freemium
- Deployment
- Self-hosted / on-premises, SaaS (vendor-hosted)
- Regions served
- Global
- Categories
- Software & technology, Workflow orchestration, Observability, Self-hosted / on-premises, MLOps & model tooling, Predictive / classical ML, Freemium, SaaS (vendor-hosted)
- Last updated
- 2 October 2026
- Published
- 2 October 2026
Use cases
Workflow orchestration
Deployment options
Self-hosted / on-premises
SaaS (vendor-hosted)
Data sources & provenance
Where this information came from, how it was checked and when it was last looked at. “Last updated” records a change to the record — it does not mean the record was verified.
- Data quality
- Data quality: Editorially Reviewed
- Primary source
- nannyml.com
- Sources cited
- 2
- Last reviewed
- 28 September 2026
- Last updated
- 2 October 2026
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