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Domino Model Monitor

Domino Model Monitor automates model evaluation and alerts teams when production models degrade enough to need expert review.

Domino Model Monitor's website

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.

All about pricing
PlanPriceWhat it gives you
Domino CloudPriced on request5 service accounts · 5 admin licenses · Unlimited consumer licenses · 1 deployment · Premium support (2 business days) · Continuous upgrades · Nexus Data Planes deployment included
EnterprisePriced on request10 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
PremiumPriced on request5 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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