Domino Model Monitor vs Evidently AI
Domino Model Monitor
domino.ai
Evidently AI
evidentlyai.comSide by side
| Figure | Domino Model Monitor | Evidently AI |
|---|---|---|
| Price from | — | $80/mo |
| Free plan | — | Yes |
| Free trial | — | Yes |
| Open source | — | Yes |
| Web | Yes | Yes |
| Windows | — | Yes |
| macOS | — | Yes |
| Linux | — | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 3 | 5 |
| Spec score · Machine Learning Model Monitoring Software | 7.5 (#11) | 9.2 (#1) |
| Integrations | Domino's partner ecosystem includes Anaconda, Snowflake, Palantir, RStudio, SageMaker, MathWorks, Stata, Collibra, DataRobot, H2O.ai, Okera, Teradata, Trifacta, and Pinnacle 21. | Documented integration examples cover Jupyter and Colab, Streamlit, MLflow, DVCLive, Airflow, Metaflow, FastAPI, PostgreSQL, Prefect, Grafana, Prometheus and AWS SES. |
| Purpose | Domino Model Monitor automates model evaluation and alerts when production models degrade enough to require expert review. | Evidently evaluates, tests, and monitors LLMs, RAG applications, AI agents, and machine-learning models. |
| Support | The Cloud and Premium plans include premium support with a two-business-day non-urgent SLA, while Enterprise includes one-business-day non-urgent support. | Community support is provided through Discord, GitHub issue reporting, documentation, courses and direct email contact. |
Plans
Domino Model Monitor
- Domino CloudPriced on request
- EnterprisePriced on request
- PremiumPriced on request
Evidently AI
- DeveloperFree
- Open-sourceFree
- Pro$80 a month
- EnterprisePriced on request
- StartupsPriced on request
In their own words
Domino Model Monitor
Domino Model Monitor evaluates production machine-learning models and alerts when degradation warrants expert review. It monitors data drift and model quality from a central dashboard showing status, summaries, customized alerts, and monitoring results. Automated prediction-data pipelines and metric generation support ongoing checks. When remediation is needed, teams can recreate a model’s development environment, retrain with production data, and redeploy a version. Models built in Python, R, SAS, MATLAB, TensorFlow, or DataRobot can be registered. The Elastic Monitoring Engine is designed to scale and ingest data from Amazon S3 and Hadoop-compatible storage, including Azure Blob Storage, Azure Data Lake, Google Cloud Storage, and HDFS. Domino supports API, web, and self-hosted use, including cloud VPCs, on-premises systems, and air-gapped environments. Pricing is on request, with Premium, Domino Cloud, and Enterprise plans listed.
Evidently AI
Evidently AI evaluates, tests, and monitors LLMs, RAG applications, AI agents, and machine-learning models. Its open-source Python framework is licensed under Apache 2.0 and provides more than 100 evaluation metrics. Automated evaluations measure output quality, safety, and reliability, can run in pipelines, and produce visual reports. The platform includes tracing, storage for application data and evaluation runs, test-dataset management, and dashboards. Teams can generate realistic, edge-case, or adversarial inputs tailored to a use case. Live monitoring tracks quality checks and can surface drift, regressions, and emerging risks. Red-team testing targets jailbreaks, prompt injections, data leaks, harmful content, and prompt leakage. Predictive ML workflows include performance, drift, and data-quality metrics. Evidently Cloud can send alerts to Slack, Discord, and email. Open-source support is through Discord and documentation; Pro includes email support. The Developer plan is free and limited to 10,000 rows per month, 1GB of snapshots, 3 projects, and 2 seats. Pro costs $80 a month, with additional rows and storage charged separately.