H2O.ai vs ZenML

Which one do AI engines recommend, and how do they differ on price, fit and features?

The short answer

ZenML is the stronger AI pick in MLOps Platforms: it has a visibility score of 6 versus 2.2 for H2O.ai, and ranks ahead in 0% of the answers that name both.

Choose H2O.ai if…

You need HIPAA or FedRAMP High coverage
You prefer a larger, established vendor (201–500 employees)
Explainable, open-source-driven predictive and agentic tooling
Go-to platform for automated machine learning (AutoML)

Choose ZenML if…

You want the brand AI engines rank higher (6 vs 2.2)
AI answers describe it more positively (55% vs 29% positive)
You need ISO 27001 coverage
Free and fully transparent open-source option

AI visibility side by side

Latest weekly run · Nov 2

Metric	H2O.ai	ZenML
Visibility score	2.2%	6%
Change vs last week	New	New
Rank in MLOps Platforms	#27	#14
Share of voice	1%	1.5%
Mentions this run	7	11
Positive in AI answers	29%	55%

The stronger value in each row is marked with a ✓.

Visibility score trend

Weekly runs over the last 60 days

H2O.ai 0pp · ZenML 0pp over 0 weekly runs.

Engine by engine

ZenML leads on 2 of 3 engines

ChatGPT

2.8%

11.7%

AI Mode

1.9%

6.3%

Perplexity

1.9%

H2O.aiZenML

Head to head in AI answers

1 engine answers name both brands

1H2O.ai ranked higher

0ZenML ranked higher

Prompt	Engine	H2O.ai	ZenML
Official website of the top MLOps platform vendors	ChatGPT	#11	#17

Features, pricing & fit

Dimension	H2O.ai	ZenML
Pricing model	—	Flat tiers
Entry price	—	Free; paid from $39 / mo
Free plan	—	Yes
Deployment	On-premises, fully air-gapped, private cloud, or public cloud	Self-hosted open source, or ZenML's cloud. Enterprise runs on-prem or air-gapped in the customer's cloud, with data and compute staying in the customer's VPC.
Integrations	—	66+
Compliance	SOC 2 Type II, HIPAA, FedRAMP High	SOC 2 Type II, ISO 27001
Support	Forward Deployed Engineers embedded on-site	Community Slack, Email, Dedicated support with SLA on Enterprise, Workshops and architecture reviews on Enterprise
Founded	2012	2021
Headquarters	Mountain View, California, United States	Munich, Germany
Employees	201–500	11–50
Funding	Series E · $250M raised	Seed extension · $6M raised
Best for	Regulated enterprises and public-sector agencies that need predictive, generative and agentic AI on their own infrastructure, including air-gapped deployments.	Data science and ML engineering teams that want pipelines and AI agents run on their own infrastructure, and agent teams that want to find the evals they are missing.