Collibra AI Governance vs Domino Data Lab

Both compete in Enterprise Incumbents. Collibra AI Governance positions itself as “AI governance layered on Collibra's data catalog and lineage for trusted, compliant AI”, while Domino Data Lableads with “Enterprise MLOps and governance platform for building and running AI in regulated industries”. The table below compares what each publishes.

Where Collibra AI Governance pulls ahead

Publishes support for NIST AI RMF, which Domino Data Lab does not. Data-mature enterprises already using Collibra for data governance that want AI oversight anchored to catalog, metadata and lineage across many model platforms.

Where Domino Data Lab pulls ahead

Publishes support for GDPR, SOC 2, HIPAA, which Collibra AI Governance does not. Large regulated enterprises (pharma, financial services, government) needing rigorous model governance, reproducibility, and audit trails across hybrid or on-prem infrastructure

Both map to EU AI Act, so framework coverage alone will not separate them — the decision usually comes down to who operates the tool and how it fits your existing stack.

	Collibra AI Governance	Domino Data Lab
Positioning	AI governance layered on Collibra's data catalog and lineage for trusted, compliant AI	Enterprise MLOps and governance platform for building and running AI in regulated industries
Category	Enterprise Incumbents	Enterprise Incumbents
Frameworks	EU AI Act, NIST AI RMF	EU AI Act, GDPR, SOC 2, HIPAA
Deployment	SaaS, Cloud	SaaS, Cloud, On-prem
Built for	Data Science / ML, GRC, Compliance, Risk	Data Science / ML, GRC, Compliance, Risk, Security
Founded	2008	2013
Headquarters	Brussels, Belgium and New York, New York, USA	San Francisco, California, USA
Ownership	Independent (private, VC-backed)	Private, independent, venture-backed as of mid-2026; not acquired. Backed by Sequoia Capital, Coatue, NVIDIA, Snowflake, and UBS; raised a Series F round in August 2025.
Funding	~$640M raised; ~$5.25B valuation (2021)	Approximately $224M+ raised across multiple rounds (through Series F, August 2025); investors include Sequoia Capital, Coatue Management, NVIDIA, Snowflake, and UBS
Pricing	Custom / enterprise	Enterprise subscription / commercial license (custom quote; no public self-serve pricing)
Key capabilities	Model and agent registries with lifecycle stages EU AI Act and NIST AI RMF assessment templates End-to-end data-to-model lineage Metadata capture and documentation Agentic AI compliance assessments Broad AI platform integration	Visual drag-and-drop Policy Builder with reusable templates Central model registry with lineage and version tracking Automated model cards, evidence notebooks, and tamper-evident audit trails Governs models built inside or outside Domino Reproducible, collaborative data-science workspaces Model monitoring and drift detection
Integrations	AWS Bedrock, AWS SageMaker, Azure AI Foundry, Azure ML, Databricks Unity Catalog, Google Vertex AI, MLflow, SAP AI Core	NVIDIA, Snowflake, AWS, Git / GitHub, GitHub Copilot, Claude Code, OpenAI Codex, Common ML frameworks and IDEs
Notable customers	None published	Bristol Myers Squibb, Lockheed Martin
Best for	Data-mature enterprises already using Collibra for data governance that want AI oversight anchored to catalog, metadata and lineage across many model platforms.	Large regulated enterprises (pharma, financial services, government) needing rigorous model governance, reproducibility, and audit trails across hybrid or on-prem infrastructure
Limitations	Strongest for organizations invested in Collibra's data governance suite; it emphasizes cataloging and assessment over runtime enforcement and real-time model monitoring.	Heavyweight, enterprise-priced platform with no public self-serve tier; governance strength is oriented toward classic ML/model-risk workflows and regulated industries, and it is a broad MLOps suite rather than a focused, lightweight LLM-observability tool, which can mean higher implementation overhead for smaller teams.

Which should you shortlist?

Choose Collibra AI Governance if data-mature enterprises already using Collibra for data governance that want AI oversight anchored to catalog, metadata and lineage across many model platforms.

Choose Domino Data Lab if large regulated enterprises (pharma, financial services, government) needing rigorous model governance, reproducibility, and audit trails across hybrid or on-prem infrastructure

Neither is a substitute for a governance program. Whichever you pick, you still need people who can define the policies the tool enforces.

Full Collibra AI Governance profile →Full Domino Data Lab profile →

AI Governance Tool Selection Kit

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