DVC vs Valohai

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

The short answer

DVC is the stronger AI pick in MLOps Platforms: it has a visibility score of 3.7 versus 1.9 for Valohai, and ranks ahead in 100% of the answers that name both.

Choose DVC if…

You want the brand AI engines rank higher (3.7 vs 1.9)
AI answers describe it more positively (56% vs 20% positive)
Git-like versioning of data and experiments that integrates with code repositories
Versions massive datasets and models alongside code

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	DVC	Valohai
Visibility score	3.7%	1.9%
Change vs last week	New	New
Rank in MLOps Platforms	#21	#30
Share of voice	1.4%	0.7%
Mentions this run	9	5
Positive in AI answers	56%	20%

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

Visibility score trend

Weekly runs over the last 60 days

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

Engine by engine

DVC leads on 3 of 3 engines

ChatGPT

2.2%

AI Mode

4.3%

Perplexity

3.9%

3.5%

DVCValohai

Head to head in AI answers

1 engine answers name both brands

1DVC ranked higher

0Valohai ranked higher

Prompt	Engine	DVC	Valohai
Alternatives to the most popular MLOps platform	Perplexity	#6	#13

Features, pricing & fit

Dimension	DVC	Valohai
Pricing model	—	Per seat
Entry price	—	Contact sales
Free plan	—	No · 14-day trial
Deployment	Runs locally on the user's machine alongside Git, with data kept in the customer's own cloud storage (S3, Azure, Google Cloud).	Managed cloud, on-premises, private cloud or air-gapped environments, on the customer's own cloud infrastructure
Compliance	—	SOC 2 Type II
Support	—	Technical support from the Customer Engineering team, Valohai Training academy, Training and onboarding resources
Founded	2017	2016
Headquarters	—	San Francisco, California, US
Employees	—	11–50
Funding	—	Seed · $2M raised
Best for	Individual data scientists and small data science projects that want data version control with minimal overhead.	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

Plans side by side

DVC

Pricing not available.

Valohai

ProCustomuser / month

EnterpriseCustomuser / month

Valohai pricing

Pros and cons

Themes from the AI answers that mention each brand

DVC

Git-like versioning of data and experiments that integrates with code repositories
Versions massive datasets and models alongside code
Free, open-source tool often paired with MLflow