DagsHub 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 3.5 for DagsHub, and ranks ahead in 0% of the answers that name both.

Choose DagsHub if…

Per seat pricing suits your budget better than flat tiers
Structured annual pricing with yearly billing options on team tiers
Recommended as a starting option for MLOps lifecycle coverage

Choose ZenML if…

You want the brand AI engines rank higher (6 vs 3.5)
You want a lower entry price ($39 vs $119)
You need SOC 2 Type II or ISO 27001 coverage
Flat tiers pricing suits your budget better than per seat

AI visibility side by side

Latest weekly run · Nov 2

Metric	DagsHub	ZenML
Visibility score	3.5%	6%
Change vs last week	New	New
Rank in MLOps Platforms	#23	#14
Share of voice	0.6%	1.5%
Mentions this run	4	11
Positive in AI answers	—	55%

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

Visibility score trend

Weekly runs over the last 60 days

DagsHub 0pp · ZenML 0pp over 0 weekly runs.

Engine by engine

ZenML leads on 2 of 3 engines

ChatGPT

3.1%

11.7%

AI Mode

3.1%

6.3%

Perplexity

4.3%

DagsHubZenML

Head to head in AI answers

1 engine answers name both brands

1DagsHub ranked higher

0ZenML ranked higher

Prompt	Engine	DagsHub	ZenML
Is there a free MLOps platform for small teams?	ChatGPT	#2	#3

Features, pricing & fit

Dimension	DagsHub	ZenML
Pricing model	Per seat	Flat tiers
Entry price	Free; paid from $119 per seat / mo	Free; paid from $39 / mo
Free plan	Yes	Yes
Deployment	Cloud hosting, with on-premise, VPC, and air-gapped installation on the Enterprise plan.	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, ISO 27001
Support	Community chat and email, Priority support on the Team plan, Enterprise SLA and support	Community Slack, Email, Dedicated support with SLA on Enterprise, Workshops and architecture reviews on Enterprise
Founded	2019	2021
Headquarters	San Francisco, California, United States	Munich, Germany
Employees	11–50	11–50
Funding	Accelerator/incubator deal	Seed extension · $6M raised
Best for	Data science and AI teams that manage multimodal datasets, experiments, and models, from individuals building small applications to enterprises running high-scale workloads.	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.