DagsHub vs Valohai

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 1.9 for Valohai, and ranks ahead in 100% of the answers that name both.

Choose DagsHub if…

You want the brand AI engines rank higher (3.5 vs 1.9)
You want a free plan to start
Structured annual pricing with yearly billing options on team tiers
Recommended as a starting option for MLOps lifecycle coverage

Choose Valohai if…

You need a self-hosted or on-premises option
You need SOC 2 Type II coverage
14-day free trial

AI visibility side by side

Latest weekly run · Nov 2

Metric	DagsHub	Valohai
Visibility score	3.5%	1.9%
Change vs last week	New	New
Rank in MLOps Platforms	#23	#30
Share of voice	0.6%	0.7%
Mentions this run	4	5
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

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

Engine by engine

DagsHub leads on 3 of 3 engines

ChatGPT

3.1%

2.2%

AI Mode

3.1%

Perplexity

4.3%

3.5%

DagsHubValohai

Head to head in AI answers

1 engine answers name both brands

1DagsHub ranked higher

0Valohai ranked higher

Prompt	Engine	DagsHub	Valohai
Alternatives to the most popular MLOps platform	Perplexity	#5	#13

Features, pricing & fit

Dimension	DagsHub	Valohai
Pricing model	Per seat	Per seat
Entry price	Free; paid from $119 per seat / mo	Contact sales
Free plan	Yes	No · 14-day trial
Deployment	Cloud hosting, with on-premise, VPC, and air-gapped installation on the Enterprise plan.	Managed cloud, on-premises, private cloud or air-gapped environments, on the customer's own cloud infrastructure
Compliance	—	SOC 2 Type II
Support	Community chat and email, Priority support on the Team plan, Enterprise SLA and support	Technical support from the Customer Engineering team, Valohai Training academy, Training and onboarding resources
Founded	2019	2016
Headquarters	San Francisco, California, United States	San Francisco, California, US
Employees	11–50	11–50
Funding	Accelerator/incubator deal	Seed · $2M 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.	AI product and ML teams that combine LLMs with specialized models and need to run the work on their own cloud or on-premises infrastructure