Evidently AI vs Valohai

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

The short answer

Evidently AI is the stronger AI pick in MLOps Platforms: it has a visibility score of 2.4 versus 1.9 for Valohai, and ranks ahead in 0% of the answers that name both.

Choose Evidently AI if…

You want the brand AI engines rank higher (2.4 vs 1.9)
AI answers describe it more positively (50% vs 20% positive)
Listed as a monitoring option in vendor-neutral ML stacks
Named alongside Prometheus and Grafana in monitoring setups

Choose Valohai if…

You need a self-hosted or on-premises option
You need SOC 2 Type II coverage
You prefer a larger, established vendor (11–50 employees)
14-day free trial

AI visibility side by side

Latest weekly run · Nov 2

Metric	Evidently AI	Valohai
Visibility score	2.4%	1.9%
Change vs last week	New	New
Rank in MLOps Platforms	#25	#30
Share of voice	0.9%	0.7%
Mentions this run	7	5
Positive in AI answers	50%	20%

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

Visibility score trend

Weekly runs over the last 60 days

Evidently AI 0pp · Valohai 0pp over 0 weekly runs.

Engine by engine

Evidently AI leads on 1 of 3 engines

ChatGPT

5.4%

2.2%

AI Mode

Perplexity

1.9%

3.5%

Evidently AIValohai

Head to head in AI answers

1 engine answers name both brands

0Evidently AI ranked higher

1Valohai ranked higher

Prompt	Engine	Evidently AI	Valohai
Alternatives to the most popular MLOps platform	Perplexity	#19	#13

Features, pricing & fit

Dimension	Evidently AI	Valohai
Pricing model	—	Per seat
Entry price	—	Contact sales
Free plan	—	No · 14-day trial
Deployment	The open-source version runs on the customer's own infrastructure; Evidently Cloud runs on managed infrastructure.	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	2020	2016
Headquarters	San Francisco, CA, United States	San Francisco, California, US
Employees	1–10	11–50
Funding	Seed · $1M raised	Seed · $2M raised
Best for	AI and ML teams that want open-source evaluation, testing and monitoring for LLM applications and predictive models.	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