Domino Model Monitor
domino.ai
What it is
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.
Spec sheet
- Purpose
- Domino Model Monitor automates model evaluation and alerts when production models degrade enough to require expert review.Read 1 Oct 2026 · domino.ai
- Integrations
- Domino's partner ecosystem includes Anaconda, Snowflake, Palantir, RStudio, SageMaker, MathWorks, Stata, Collibra, DataRobot, H2O.ai, Okera, Teradata, Trifacta, and Pinnacle 21.Read 1 Oct 2026 · domino.ai
- 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.Read 1 Oct 2026 · domino.ai
- Headquarters
- San Francisco, California, United StatesRead 28 Sep 2026 · domino.ai
- Founded
- 2013Read 28 Sep 2026 · domino.ai
- Automated pipelines
- Domino provides simplified deployment tools, automated prediction data pipelines, and automatic generation of monitoring metrics.Read 1 Oct 2026 · domino.ai
- Central dashboard
- Users can view model status, monitoring summaries, customized alerts, data drift, and model quality from one dashboard.Read 1 Oct 2026 · domino.ai
- Deployment environments
- Domino supports self-managed deployment in a VPC on AWS, Azure, GCP, or on-premises, including secure air-gapped environments.Read 1 Oct 2026 · domino.ai
- Drift monitoring
- The monitoring platform tracks data drift and model quality degradation with integrated monitoring and alerts.Read 1 Oct 2026 · domino.ai
- Enterprise security
- Domino describes single-tenant isolation, secure development testing, vulnerability scanning, third-party penetration testing, and SIEM-integrated intrusion detection.Read 1 Oct 2026 · domino.ai
- Framework support
- Models built in Python, R, SAS, MATLAB, TensorFlow, or DataRobot can be registered for monitoring.Read 1 Oct 2026 · domino.ai
- Remediation
- Users can recreate a production model's development environment, retrain with production data, and redeploy a new version.Read 1 Oct 2026 · domino.ai
- 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.Read 1 Oct 2026 · domino.ai
- 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.Read 1 Oct 2026 · domino.ai
- Snowflake monitoring
- Domino can automatically configure Snowflake-deployed models for drift and model quality analysis with prediction data capture pipelines and ground-truth datasets.Read 1 Oct 2026 · domino.ai
- Target customers
- Domino positions its platform for large AI-driven enterprises and highly regulated industries performing mission-critical AI work.Read 1 Oct 2026 · domino.ai
Plans and prices
Strong points and limits
Strong points
- Tracks data drift and model quality
- Central dashboard with customized alerts
- Supports multiple model frameworks
- Self-managed and air-gapped deployment options
- Includes registry and experiment tracking
Limits
- Pricing is available only on request
- Enterprise-oriented deployment and licensing
- Support response varies by plan
Who it suits
Domino positions this platform for large AI-driven enterprises and regulated industries running mission-critical AI. It fits teams needing monitored production models and managed remediation workflows.
Verdict
Domino Model Monitor combines drift detection, quality monitoring, alerting, and retraining workflows across cloud, self-hosted, and air-gapped deployments. Its plan structure and support terms are aimed at larger organizations.
Where Specifiction places it
- Machine Learning Model Monitoring Software#11 of 207.5
- Model registries#25 of 387.3