What Domino Data Lab does

Domino Data Lab is a privately held enterprise AI platform company founded in 2013 and headquartered in San Francisco. The company provides a unified platform that supports the full machine learning and AI lifecycle — model development, MLOps, deployment, and governance — for regulated enterprises. Its product architecture is organized around three pillars: a Model Factory that supports any coding assistant, any language, and any framework including agentic AI systems; an App Hub that scales governed AI-powered applications to thousands of users without rewrites; and a Governance Center that defines policies once and enforces them across the lifecycle with auditability, quality control, and cost visibility. The platform is differentiated by deep interoperability with AI coding assistants (GitHub Copilot, Claude Code, OpenAI Codex) through a proprietary Domino Skills framework, support for SAS, R, and Python within a 21 CFR Part 11-compliant Statistical Computing Environment (SCE), and a broad certification footprint including FedRAMP, DoD Impact Level 5, HIPAA, ISO 9001:2015, ISO 27001, and SOC 2 Type II. The company has extended into agentic AI observability, multi-modal document intelligence with RAG, self-hosted LLM inference via vLLM, and a multi-provider AI Gateway with audit logging.

The company sells primarily through enterprise field sales to large organizations in financial services (Moody's, UBS), life sciences (GSK, Bayer), and the public sector (U.S. Navy), with cloud marketplace distribution through AWS and strategic partnerships with NVIDIA, Snowflake, NetApp, and Chainguard. Named customers span more than 20% of the Fortune 100, and recent customer wins and expansions include Moody's 50%+ reduction in model deployment time, GSK's rollout to 2,000+ biostatistics users, UBS's RiskLab platform, and the U.S. Navy's Project AMMO. Revenue is generated primarily through quote-based enterprise platform subscriptions (typically annual), supplemented by professional services for MLOps assessments, model migrations, AI RMF implementations, and residency programs.

Domino is venture-backed and operates with approximately 250 employees as of 2026. Funding history includes a $100M Series F in October 2021 led by Great Hill Partners with NVIDIA, Coatue, Sequoia, Empede Capital, and Highland Capital participating, a Snowflake strategic investment in June 2022, and a corporate equity investment by UBS in August 2025 that included a board observer seat. The company has no announced acquisition, IPO, or private equity transaction.

Name

Domino Data Lab

Legal name

Domino Data Lab, Inc.

Website

https://domino.ai

Company type

Private

Founded year

2013

Operating status

Operating

Headcount range

251–500 employees

Short description

Domino Data Lab provides an enterprise AI platform for building, deploying, and governing AI/ML applications. It serves regulated enterprises across financial services, life sciences, and government, with 20%+ of the Fortune 100 as customers.

Ownership category

akta.pro rank

Product category

Enterprise AI Platform / MLOps

NAICS

Software Publishers (51321), Computer Systems Design and Related Services (54151), Computing Infrastructure Providers, Data Processing, Web Hosting, and Related Services (51821)

SIC

Services-Prepackaged Software (7372), Services-Computer Programming Services (7371), Services-Computer Integrated Systems Design (7373)

akta.pro primary industry

End-to-End Enterprise AI Platforms (MLOps & Model Lifecycle Management) (HDAEANAA)

akta.pro secondary industries

Model Deployment, Serving & Inference Platforms (HDAAABAF), AI Integration & Orchestration Platforms (Connectors, Workflow, iPaaS for AI) (HDAEANAI), AI Governance, Risk & Compliance (GRC) Platforms (HDAAAMAA), AI/ML Solution Integration & MLOps Enablement (BPAEAAAJ)

Keywords

• Enterprise AI platform
• MLOps platform
• Model lifecycle management
• AI governance software
• Statistical computing environment

Headquarters

HQ city

San Francisco

HQ country

United States

HQ region

North America

Offices1 record

Markets served

GTM type

B2B

Offering type

Software

Cost components

Personnel, Technology or R&D, Marketing or Sales, Infrastructure, Operations

Revenue model

1. Enterprise Platform Subscription: Domino operates on a subscription model providing access to its Enterprise AI Platform including model development, MLOps, and governance capabilities. Pricing is typically enterprise-level with quotes based on usage, users, and deployment scale.
2. Professional Services: Implementation, training, and consulting services including MLOps assessments, model migrations, AI RMF implementations, and residency programs.

Pricing tiers

Go-to-market motion1 record

Distribution channels3 records

Marketing channels6 records

Core offering

Domino Data Lab provides an enterprise AI platform that unifies model development, MLOps, collaboration, and governance into a single system. The platform supports the full AI lifecycle from development through production deployment, including statistical computing, generative AI, and agentic AI capabilities, for regulated industries such as life sciences, financial services, and government.

Product overview

Domino Data Lab offers a unified Enterprise AI Platform architecture combining a core Model Factory, App Hub, and Governance Center. The platform provides integrated modules for AI infrastructure, data management, AI workbench, MLOps, AI governance, and FinOps. Specialized offerings include Domino Statistical Computing Environment (SCE) for life sciences regulatory compliance, Domino Governance for enterprise AI policy enforcement, and an Agentic AI Platform for autonomous AI systems. The platform integrates coding assistants (GitHub Copilot, Claude Code, Codex) and supports LLM hosting with vLLM for self-hosted generative AI. Domino serves regulated industries including life sciences, financial services, and public sector with professional services, training (Domino University), and technical documentation (Domino Blueprints).

Differentiator

Problem solved

Functional benefit

Products and services

• Domino Enterprise AI Platform The unified enterprise AI platform providing integrated model development, MLOps, collaboration, and governance capabilities for building, scaling, and governing AI-powered applications across regulated industries including life sciences, financial services, and government.
• Domino Cloud Cloud-hosted deployment option for Domino's platform with autoscaling, spot instance support, and managed data planes for cost-effective AI workload management. Available on AWS with additional cloud providers planned.
• Domino Statistical Computing Environment (SCE) Enterprise standard statistical computing environment for life sciences that unifies SAS, R, and modern languages with full traceability and audit-ready documentation in a 21 CFR Part 11-compliant environment supporting regulatory submissions.
• Domino Governance AI governance solution that embeds policy management and enforcement into the end-to-end AI lifecycle, automating compliance documentation and reducing governed model lifecycle by 70%.
• Agentic AI Platform First fully governed platform for agentic AI systems providing secure LLM hosting, deep observability, structured evaluations, and production-grade monitoring for autonomous AI agents.
• Professional Services Expert consulting services including MLOps assessment, AI RMF configuration, model migrations, solution architecture residency, and training for enterprise AI implementation.
• Domino University Online learning platform providing training paths and certification exams for data science practitioners, administrators, and partners on Domino platform usage.
• Document Intelligence Mission-ready document intelligence solution transforming policies, case files, intelligence reports, and technical diagrams into auditable operational knowledge using multi-modal AI and retrieval-augmented generation.

Quantifiable outcome

• 50% reduction in end-to-end model lifecycle time
• +9 more outcomes

Named customers6 records

Segments5 records

Ideal customer profiles4 records

Technology focussed Yes

API detail

Has API

Yes

API docs

API detail

Core technology

AI maturity

App detail

Integration34 records

AI capability12 records

Feature9 records

Partnerships

Five partnerships are on record, tiered core and minor.

• AppsiloncoreTechnology or Integration · 25 June 2026Partnership to help life sciences companies move open-source AI from R&D development into validated production environments. Appsilon's Axon.R package validation tool is the first partner-built extension on Domino's platform, supporting SAS-to-open-source migration.
• Pharmaverse CouncilminorStrategic or Co-development Partner · 25 June 2026Collaboration with Pharmaverse Council on Axon.R package validation tool developed with the council and built on R Validation Hub's risk-based methodology for pharmaceutical regulatory compliance.
• Amazon Web Services (AWS)coreTechnology or Integration · 16 September 2025Domino platform integrated with AWS including GovCloud (US) DoD IL5 environment, support for AWS Inferentia and Trainium AI chips, and availability through AWS Marketplace. U.S. Navy deployments run on AWS GovCloud.
• NetAppcoreTechnology or Integration · 26 September 2024Strategic collaboration to enhance AI and data management using NetApp's hybrid file storage technology integrated within Domino's platform. Partnership includes Domino Volumes for NetApp ONTAP (DVNO) product that can reduce cost and processing times by up to 50%.
• NVIDIAcoreTechnology or Integration · 5 October 2021Expanded partnership with NVIDIA to further integrate AI and data analytics products into Domino's enterprise ML platform. NVIDIA participates in Domino's funding rounds and provides GPU-accelerated compute infrastructure including DGX systems for AI training and inference workloads.

Scale indicators11 records

Recent moves6 records

Expansion highlights6 records

Direct peers

• DataRobot: Enterprise AI/ML platform focused on model development, deployment, and governance for regulated industries (banking, healthcare, public sector) — the same regulated-enterprise wedge where Domino concentrates its GTM and where the two products most directly compete.
• Weights & Biases (W&B): ML experiment tracking, model registry, and MLOps platform used by enterprise data science teams; offers overlapping capabilities to Domino's MLOps, model registry, and deployment stack and is frequently evaluated against Domino by enterprise buyers.
• Palantir Foundry: Enterprise data and AI operating system with deep penetration in regulated, defense, and financial services customers; competes with Domino for the same model-driven enterprise buyer that needs auditable, governed AI in production.
• Databricks: Provides a unified data and AI platform (Lakehouse + MLflow + Mosaic AI) that directly competes with Domino's enterprise model development, MLOps, and governance capabilities for the same enterprise data science buyer.

Emerging players

• H2O.ai: Provides an enterprise AI cloud and open-source ML platform (H2O, Driverless AI) for building, deploying, and governing models; competes in the same regulated-enterprise ML platform category as Domino with a more open-source-leaning GTM.
• Snowflake Cortex AI: Snowflake is both a strategic investor in Domino and a competitor via Snowpark and Cortex AI for in-warehouse model development and ML serving; the two companies co-sell on some accounts and overlap on enterprise data science workloads.

Broad incumbents

• Azure Machine Learning: Microsoft's enterprise ML platform offering model training, deployment, and MLOps within the Azure cloud; overlaps with Domino on enterprise ML lifecycle and is the dominant competitor among Microsoft-centric regulated buyers.
• IBM watsonx: IBM's enterprise AI and data platform targeting regulated industries (financial services, healthcare, public sector) with model lifecycle, governance, and AI governance tooling — directly comparable to Domino's regulated-industry wedge.
• Google Vertex AI: Google Cloud's unified AI platform for training, deploying, and customizing ML and generative AI models, with overlapping capabilities to Domino's MLOps and agentic AI features and competitive overlap on cloud-native enterprise AI buyers.
• Amazon SageMaker: AWS's integrated ML development, training, and deployment service; competes with Domino for enterprise ML workloads and is offered at hyperscaler scale with bundled cloud pricing, although it lacks Domino's depth in regulated-industry compliance.

Market position

Strengths5 records

Weaknesses5 records

Competitive moat6 records

Key risks6 records

Key highlights7 records

Customer concentration

• Xx.com/dominodatalab
• GitHubgithub.com/dominodatalab
• LinkedInlinkedin.com/company/domino-data-lab
• Facebookfacebook.com/dominodatalab

Compliance8 records

Revenue estimate

Valuation estimate

Number of profiles

Profiles14 records

Funding overview

Funding rounds10 records

Investors16 records

Funding detail is available on the Subscription and Enterprise plan.Contact sales →

M&A

Investments

M&A and investment is available on the Subscription and Enterprise plan.Contact sales →

Frequently asked questions about Domino Data Lab