NannyML
7.9#4 in machine learning model monitoring softwareFrom $99 a monthFree planWebAPILinuxSelf-hosted
VisitNannyML vs STAMM
What both publish
| Fact | NannyML | STAMM |
|---|---|---|
| Installation | The open-source library can be installed with pip, Conda, Docker or directly from the Git repository. | The reference deployment uses Docker Compose and lists Linux, macOS, or Windows with Docker 24 or later and Docker Compose as requirements. |
| Integrations | NannyML Cloud is offered through both Azure Marketplace and AWS Marketplace. | The workflow orchestrator calls the model registry over REST, and the project describes data ingestion through equipment REST hooks, MQTT applications, or frameworks such as LEAF. |
| Purpose | NannyML monitors deployed machine-learning models and estimates model performance even when ground truth is delayed or absent. | STAMM is an open-source MLOps framework for deploying, monitoring, and maintaining machine-learning soft sensors in industrial processes. |
NannyML plans
- Open SourceFree
- Starter (beta)$99 a month
- Starter$399 a month
- Scale$999 a month
- Pro (beta)$3,800 a month
- EnterprisePriced on request
STAMM plans
No prices published.
Pick NannyML if…
NannyML suits teams that need to monitor deployed models when ground truth is delayed or absent, and connect model performance with business outcomes. It can also suit teams looking for self-managed open-source installation or Cloud deployment.
Pick STAMM if…
STAMM is intended for process modelers, ML engineers, operators, and project or production managers working with industrial soft sensors. It may suit teams that want drift monitoring and model tracking in live systems.