Arize vs DagsHub

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

The short answer

DagsHub is the stronger AI pick in MLOps Platforms: it has a visibility score of 3.5 versus 1.5 for Arize, and ranks ahead in 100% of the answers that name both.

Choose Arize if…

You want a lower entry price ($50 vs $119)
You need a self-hosted or on-premises option
You need SOC 2 Type II or ISO 27001 or PCI DSS or HIPAA or GDPR coverage
You prefer a larger, established vendor (51–200 employees)

Choose DagsHub if…

You want the brand AI engines rank higher (3.5 vs 1.5)
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

AI visibility side by side

Latest weekly run · Nov 2

Metric	Arize	DagsHub
Visibility score	1.5%	3.5%
Change vs last week	New	New
Rank in MLOps Platforms	#34	#23
Share of voice	0.7%	0.6%
Mentions this run	5	4
Positive in AI answers	20%	—

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

Visibility score trend

Weekly runs over the last 60 days

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

Engine by engine

DagsHub leads on 3 of 3 engines

ChatGPT

2.8%

3.1%

AI Mode

0.9%

3.1%

Perplexity

0.9%

4.3%

ArizeDagsHub

Head to head in AI answers

1 engine answers name both brands

0Arize ranked higher

1DagsHub ranked higher

Prompt	Engine	Arize	DagsHub
Alternatives to the most popular MLOps platform	Perplexity	#20	#5

Features, pricing & fit

Dimension	Arize	DagsHub
Pricing model	Flat tiers	Per seat
Entry price	Free; paid from $50 / mo	Free; paid from $119 per seat / mo
Free plan	Yes	Yes
Deployment	SaaS, with self-hosted deployment on the Enterprise plan; Phoenix runs locally or self-hosted.	Cloud hosting, with on-premise, VPC, and air-gapped installation on the Enterprise plan.
Integrations	40+	—
Compliance	SOC 2 Type II, ISO 27001, PCI DSS, HIPAA, GDPR	—
Support	Community, Email, Dedicated support on Enterprise	Community chat and email, Priority support on the Team plan, Enterprise SLA and support
Founded	2020	2019
Headquarters	—	San Francisco, California, United States
Employees	51–200	11–50
Funding	Series B-1 extension · $131M raised	Accelerator/incubator deal
Best for	AI engineering teams building and running production AI agents and LLM applications who need observability and evaluations.	Data science and AI teams that manage multimodal datasets, experiments, and models, from individuals building small applications to enterprises running high-scale workloads.