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Brief
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Domino Data Lab

Domino accelerates data science work by providing an integrated platform for collaboration, experimentation, deployment, and monitoring of machine learning models, enabling enterprises to scale their AI initiatives with proper governance and reproducibility.

San Francisco, California, United StatesFounded 2013

Last updated May 11, 2026 by ATDb automated enrichment

Business Model
SaaS
Target Market
Enterprise
Employee Count
201-500
Funding
$350M+
API Available
Yes
Market Position

Leading enterprise MLOps platform provider focused on data science collaboration and model lifecycle management

Overview

Domino Data Lab is an enterprise AI and machine learning operations (MLOps) platform company founded in 2013. The company provides a comprehensive platform that helps data science teams collaborate, build, deploy, and monitor machine learning models in production environments. Domino's platform addresses the challenges of scaling data science work across organizations by providing tools for experiment tracking, model deployment, reproducibility, and governance. While not strictly an AdTech company, Domino Data Lab serves various industries including financial services, healthcare, pharmaceuticals, manufacturing, and technology companies. Some of its customers may use the platform for marketing analytics, customer segmentation, and predictive modeling that supports advertising and marketing operations. The company has raised significant venture capital funding and serves major enterprise customers including Bristol Myers Squibb, Lockheed Martin, and Red Hat. Domino Data Lab competes in the rapidly growing MLOps and data science platform market, positioning itself as an enterprise-grade solution that emphasizes collaboration, reproducibility, and governance. The platform supports multiple programming languages, frameworks, and deployment options, making it flexible for diverse data science workflows.

Products & Features

Domino Enterprise MLOps Platform

Comprehensive platform for managing the end-to-end machine learning lifecycle including development, deployment, and monitoring

Domino Workspaces

Interactive development environments for data scientists with support for multiple tools and frameworks

Domino Jobs

Automated execution and scheduling of data science workloads

Domino Model APIs

Tools for deploying and serving machine learning models as APIs

Domino Launchpad

Self-service interface for business users to interact with data science models

Key Features
Experiment tracking and reproducibilityCollaborative workspacesModel deployment and monitoringMulti-language and framework supportScalable compute infrastructureModel governance and complianceVersion control integrationAutomated model retraining
Use Cases
Predictive modeling and forecastingCustomer segmentation and personalizationRisk modeling and fraud detectionDrug discovery and clinical trial optimizationSupply chain optimizationRecommendation systemsNatural language processing applicationsComputer vision applications
Customer Segments
Financial ServicesHealthcare and Life SciencesManufacturingTechnology CompaniesInsuranceRetail

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