Domino Model Monitor
Domino Model Monitor automates model evaluation and alerts teams when production models degrade enough to need expert review.
What Domino Model Monitor is
Domino Model Monitor automates model evaluation and alerts teams when production models degrade enough to need expert review. Its monitoring tracks data drift and model quality, with a central dashboard for model status, summaries, customized alerts, and monitoring results. Domino also provides automated prediction-data pipelines and monitoring metrics. When a model needs remediation, users can recreate its development environment, retrain with production data, and redeploy a new version. Models built with Python, R, SAS, MATLAB, TensorFlow, or DataRobot can be registered for monitoring. The Elastic Monitoring Engine is designed to scale and can ingest data from Amazon S3 and Hadoop-compatible storage, including Azure Blob Storage, Azure Data Lake, Google Cloud Storage, and HDFS. Deployment options include self-managed environments in a VPC on AWS, Azure, or GCP, as well as on-premises and secure air-gapped settings. Pricing is available on request. Domino positions the platform for large AI-driven enterprises and regulated industries doing mission-critical AI work; its stated certifications and controls include ISO, SOC 2, HIPAA, and GDPR-related capabilities.
Good
- Monitors data drift and model quality degradation
- Supports models built in six listed frameworks
- Can retrain with production data and redeploy
- Supports cloud, on-premises, and air-gapped deployment
- Offers a central dashboard with customized alerts
Watch out
- Pricing is available only on request
- Premium support has a two-business-day non-urgent SLA
- Enterprise support has a one-business-day non-urgent SLA
Who it suits
Domino Model Monitor suits large AI-driven enterprises and regulated organizations monitoring production models. It is especially relevant where teams need drift alerts, retraining workflows, or self-managed deployment options.
Verdict
Domino Model Monitor combines drift and quality monitoring with tools for model retraining and redeployment. Its enterprise deployment and support options are substantial, but pricing requires a request.
Plans and prices
From Domino Model Monitor's own pricing page, checked 1 Oct 2026.
| Plan | Price | What it gives you |
|---|---|---|
| Domino Cloud | Priced on request | 5 service accounts · 5 admin licenses · Unlimited consumer licenses · 1 deployment · Premium support (2 business days) · Continuous upgrades · Nexus Data Planes deployment included |
| Enterprise | Priced on request | 10 service accounts · 10 admin licenses · Unlimited consumer licenses · Up to 2 deployments · Up to 2 upgrades per year · Enterprise support (1 business day) · Designated customer advocate · Proactive monitoring |
| Premium | Priced on request | 5 service accounts · 5 admin licenses · Unlimited consumer licenses · Up to 2 deployments (1 prod, 1 non-prod) · Up to 2 upgrades per year · Premium support (2 business days) |
The facts
Each one read from Domino Model Monitor's own pages, with the date it was checked.
What it does
- Automated pipelines
- Domino provides simplified deployment tools, automated prediction data pipelines, and automatic generation of monitoring metrics.checked 1 Oct 2026
- Central dashboard
- Users can view model status, monitoring summaries, customized alerts, data drift, and model quality from one dashboard.checked 1 Oct 2026
- Deployment environments
- Domino supports self-managed deployment in a VPC on AWS, Azure, GCP, or on-premises, including secure air-gapped environments.checked 1 Oct 2026
- Drift monitoring
- The monitoring platform tracks data drift and model quality degradation with integrated monitoring and alerts.checked 1 Oct 2026
- Enterprise security
- Domino describes single-tenant isolation, secure development testing, vulnerability scanning, third-party penetration testing, and SIEM-integrated intrusion detection.checked 1 Oct 2026
- Framework support
- Models built in Python, R, SAS, MATLAB, TensorFlow, or DataRobot can be registered for monitoring.checked 1 Oct 2026
- Integrations
- Domino's partner ecosystem includes Anaconda, Snowflake, Palantir, RStudio, SageMaker, MathWorks, Stata, Collibra, DataRobot, H2O.ai, Okera, Teradata, Trifacta, and Pinnacle 21.checked 1 Oct 2026
- Purpose
- Domino Model Monitor automates model evaluation and alerts when production models degrade enough to require expert review.checked 1 Oct 2026
- Remediation
- Users can recreate a production model's development environment, retrain with production data, and redeploy a new version.checked 1 Oct 2026
- Scale and storage
- Domino's Elastic Monitoring Engine is designed to scale monitoring capacity and ingest data from Amazon S3 and Hadoop-compatible file systems including Azure Blob Storage, Azure Data Lake, Google Cloud Storage, and HDFS.checked 1 Oct 2026
- Security certifications
- Domino states that it is certified for ISO 27001, ISO 9001, SOC 2, HIPAA, and GDPR, and supports 21 CFR Part 11 and Annex 11 compliance.checked 1 Oct 2026
- Snowflake monitoring
- Domino can automatically configure Snowflake-deployed models for drift and model quality analysis with prediction data capture pipelines and ground-truth datasets.checked 1 Oct 2026
- 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.checked 1 Oct 2026
- Target customers
- Domino positions its platform for large AI-driven enterprises and highly regulated industries performing mission-critical AI work.checked 1 Oct 2026
The company
- Founded
- 2013checked 28 Sep 2026
- Headquarters
- San Francisco, California, United Stateschecked 28 Sep 2026
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