CloudBees vs Codefresh

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

The short answer

Codefresh is the stronger AI pick in CI/CD: it has a visibility score of 3.6 versus 2.8 for CloudBees, and ranks ahead in 0% of the answers that name both.

Choose CloudBees if…

You prefer a larger, established vendor (501–1,000 employees)
Enterprise scaling, governance, and support for Jenkins
Deep enterprise Jenkins foundation with advanced software delivery management
Broad plugin ecosystem via Jenkins

Choose Codefresh if…

You want the brand AI engines rank higher (3.6 vs 2.8)
You need ISO 27001 or SOC 2 coverage

AI visibility side by side

Latest weekly run · Nov 3

Metric	CloudBees	Codefresh
Visibility score	2.8%	3.6%
Change vs last week	New	New
Rank in CI/CD	#20	#19
Share of voice	1%	1.2%
Mentions this run	6	7
Positive in AI answers	33%	—

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

Visibility score trend

Weekly runs over the last 60 days

CloudBees 0pp · Codefresh 0pp over 0 weekly runs.

Engine by engine

Codefresh leads on 1 of 3 engines

ChatGPT

2.2%

0.9%

AI Mode

4.6%

0.9%

Perplexity

1.7%

9.1%

CloudBeesCodefresh

Head to head in AI answers

1 engine answers name both brands

1CloudBees ranked higher

0Codefresh ranked higher

Prompt	Engine	CloudBees	Codefresh
Official website of the top CI/CD tool vendors	AI Mode	#9	#11

Features, pricing & fit

Dimension	CloudBees	Codefresh
Deployment	Hybrid and multi-cloud environments	—
Compliance	—	ISO 27001, SOC 2
Support	Support team	Community support (Free), 8/5 support, 9–5pm weekdays (Professional), 24/7 support (Enterprise), Premium support (add-on)
Founded	2010	2012
Headquarters	San Jose, CA, United States	South Brisbane, Queensland, Australia
Employees	501–1,000	201–500
Funding	Series F, with Goldman Sachs Asset Management private credit clients leading	Reported raise (headline only, unverified) · $204M raised
Best for	Large enterprises that need to govern CI/CD and agentic coding across mixed toolchains	Enterprise teams deploying frequently across many environments, applications, customers or Kubernetes clusters