Neptune.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 2.6 for Neptune.ai, and ranks ahead in 0% of the answers that name both.

Choose Neptune.ai if…

You need a self-hosted or on-premises option
You prefer a larger, established vendor (51–200 employees)
Collaboration-first dashboard for tracking experiments
Lightweight metadata store built for experiment tracking

Choose ZenML if…

You want the brand AI engines rank higher (6 vs 2.6)
You need more native integrations (66+ vs 25+)
AI answers describe it more positively (55% vs 25% positive)
You need SOC 2 Type II or ISO 27001 coverage

AI visibility side by side

Latest weekly run · Nov 2

Metric	Neptune.ai	ZenML
Visibility score	2.6%	6%
Change vs last week	New	New
Rank in MLOps Platforms	#24	#14
Share of voice	0.6%	1.5%
Mentions this run	4	11
Positive in AI answers	25%	55%

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

Visibility score trend

Weekly runs over the last 60 days

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

Engine by engine

ZenML leads on 2 of 3 engines

ChatGPT

0.9%

11.7%

AI Mode

6.8%

6.3%

Perplexity

Neptune.aiZenML

Head to head in AI answers

1 engine answers name both brands

1Neptune.ai ranked higher

0ZenML ranked higher

Prompt	Engine	Neptune.ai	ZenML
Official website of the top MLOps platform vendors	ChatGPT	#16	#17

Features, pricing & fit

Dimension	Neptune.ai	ZenML
Pricing model	—	Flat tiers
Entry price	—	Free; paid from $39 / mo
Free plan	—	Yes
Deployment	Hosted service by default, with a self-hosted option on-premises or on AWS, Google Cloud or Azure as a Kubernetes cluster, deployed as microservices via a Helm chart.	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	25+	66+
Compliance	—	SOC 2 Type II, ISO 27001
Support	—	Community Slack, Email, Dedicated support with SLA on Enterprise, Workshops and architecture reviews on Enterprise
Founded	2017	2021
Headquarters	Palo Alto, California, United States	Munich, Germany
Employees	51–200	11–50
Funding	Series A · $18M raised	Seed extension · $6M raised
Best for	Teams training foundation models and other large-scale machine learning models that need to monitor GPT-scale training runs.	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.