Evidently AI vs Hopsworks

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 0.3 for Hopsworks, 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 0.3)
AI answers describe it more positively (50% vs 0% positive)
Listed as a monitoring option in vendor-neutral ML stacks
Named alongside Prometheus and Grafana in monitoring setups

Choose Hopsworks if…

You need a self-hosted or on-premises option
You need ISO 27001 or SOC 2 Type II or GDPR or HIPAA coverage
You prefer a larger, established vendor (11–50 employees)

AI visibility side by side

Latest weekly run · Nov 2

Metric	Evidently AI	Hopsworks
Visibility score	2.4%	0.3%
Change vs last week	New	New
Rank in MLOps Platforms	#25	#52
Share of voice	0.9%	0.1%
Mentions this run	7	1
Positive in AI answers	50%	0%

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

Visibility score trend

Weekly runs over the last 60 days

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

Engine by engine

Evidently AI leads on 2 of 3 engines

ChatGPT

5.4%

0.9%

AI Mode

Perplexity

1.9%

Evidently AIHopsworks

Head to head in AI answers

1 engine answers name both brands

0Evidently AI ranked higher

1Hopsworks ranked higher

Prompt	Engine	Evidently AI	Hopsworks
What should an MLOps platform integrate with?	ChatGPT	#19	#10

Features, pricing & fit

Dimension	Evidently AI	Hopsworks
Pricing model	—	Usage-based
Entry price	—	Contact sales
Free plan	—	Yes
Deployment	The open-source version runs on the customer's own infrastructure; Evidently Cloud runs on managed infrastructure.	Fully managed SaaS, self-hosted on Kubernetes, on-premises, air-gapped and hybrid
Compliance	—	ISO 27001, SOC 2 Type II, GDPR, HIPAA
Support	—	Community support, Dedicated support team and custom integrations on Enterprise plan, Platform SLA on Enterprise plan
Founded	2020	2017
Headquarters	San Francisco, CA, United States	Stockholm, Sweden
Employees	1–10	11–50
Funding	Seed · $1M raised	Series B
Best for	AI and ML teams that want open-source evaluation, testing and monitoring for LLM applications and predictive models.	Teams building production ML systems that need real-time feature serving and reuse of features across models