Evidently AI
8.3#2 in machine learning model monitoring softwareFrom $80 a monthFree planWebAPILinuxmacOS
VisitEvidently AI vs NannyML
NannyML
7.9#4 in machine learning model monitoring softwareFrom $99 a monthFree planWebAPILinuxSelf-hosted
VisitWhat both publish
| Fact | Evidently AI | NannyML |
|---|---|---|
| Documentation depth | The documentation includes getting-started guides, metric catalogs, cookbook examples, evaluation guides, FAQs and a changelog. | Documentation includes tutorials for tabular, text and computer-vision models, custom metrics, reporting, deployment, SDK usage and API reference. |
| Integrations | Documented integration examples cover Jupyter and Colab, Streamlit, MLflow, DVCLive, Airflow, Metaflow, FastAPI, PostgreSQL, Prefect, Grafana, Prometheus and AWS SES. | NannyML Cloud is offered through both Azure Marketplace and AWS Marketplace. |
| Purpose | Evidently evaluates, tests, and monitors LLMs, RAG applications, AI agents, and machine-learning models. | NannyML monitors deployed machine-learning models and estimates model performance even when ground truth is delayed or absent. |
| Rating on G2 | 5.0 out of 5 from 1 review | No public NannyML rating; 0 reviews listed |
| Rating on Product Hunt | 5.0 out of 5 from 2 reviews | 5.0 out of 5 from 4 reviews |
Evidently AI plans
- DeveloperFree
- Open-sourceFree
- Pro$80 a month
- EnterprisePriced on request
- StartupsPriced on request
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
Pick Evidently AI if…
It suits teams evaluating or monitoring AI applications and predictive ML models, including those that want open-source tooling or a hosted platform. Its synthetic-data and red-team capabilities may also suit teams assessing adversarial inputs and risks.
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.