IT AI Index

Index › Vendors › MuleSoft · September 2026 Edition

1 category · Named, not ranked

MuleSoft

6Judge labels

1First choices

2Negative labels

5 of 12Models named it

1Category

September 2026 Edition. Every number here is derived from the raw labels under vendor table vv2026-09.2, every buyer segment counted.

Standing

3 labels, too few to rank

A product needs 10 labels in a category before a share or quadrant is stated. MuleSoft was named 3 times in ETL, where Airbyte led with 32%. The labels and the evidence are below, counted exactly.

By buyer segmentRead the same way at every buyer size.

Small businessnot named

No model named it for this buyer.

Mid-market9 of 66

under the label threshold

Enterprise40 of 67

under the label threshold

In etl · each standing computed within its segment · bars are 0 to 100 · the accent bar is the product's own best reading

Standing by category

Every category where a model named MuleSoft for a mid-market B2B company. Share is first choices across the direct, paraphrase, budget and scale prompts; rank is within every product named in that category.

Category	Function	Share	Rank	Negative rate	Labels	Quadrant
ETL and ELT	Data platform	2%	9 of 66	33%	3	under 10 labels · led by Airbyte at 32%

Movement

This is the first edition on this tier, so no move can be computed for MuleSoft yet. From the next edition this section shows, per buyer segment, whether its share moved by more than the measured noise floor.

By model

How each model treated MuleSoft across every prompt where it was named for a mid-market B2B company. Twelve models, six prompts per category.

Model	First choice	Mention	Negative	Labels
Claude Haiku 4.5	1	0	0	1
GPT-5.4 mini	0	0	0	0
Gemini 3.5 Flash	0	0	0	0
Perplexity Sonar	0	0	0	0
Grok 4.1 Fast	0	0	0	0
Mistral Small	0	0	0	0
DeepSeek V4 Flash	0	1	0	1
Llama 4 Maverick	0	0	0	0
Qwen 3.7 Flash	0	0	1	1
Kimi K2	0	0	0	0
GLM 4.7 FlashX	0	0	0	0
MiniMax M2.5	0	0	0	0

By framing

Which of the six questions produced the naming. By model says how often; this says asked what. The first-choice count on the right carries the marks of the models that produced it.

FramingLabels by classFirst choices

Direct2 labels1

Paraphrase0 labelsNone

Comparative2 labelsNone

Budget-constrained0 labelsNone

Scale-constrained1 labelNone

Negative1 labelNone

First choiceAlternativeMentionNegative6 labels in all, every segment counted; 1 of the 1 first choices count toward share, since the comparative and negative framings do not. The bar is one segment per label class, to scale within the framing.

What the models said for it

Verbatim evidence the judge attached to positive labels.

“Talend or MuleSoft if you need a balance of power and usability with vendor support” Claude Haiku 4.5 · ETL · direct prompt · first choice

And against it

Verbatim evidence attached to negative labels. A warning on a product with few labels is a warning; on a product with many, it is one voice among them.

“Cons: Overkill for simple data pipeline needs; expensive.” Qwen 3.7 Flash · ETL · comparative prompt · soft negative

Named alongside

The products named in the same answers as MuleSoft, over the 6 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and MuleSoft was named but was not.

ProductSame answerTook the first choice insteadHead to head

Airbyte4 of 61Not in the top three

Fivetran4 of 61Not in the top three

Matillion4 of 60Not in the top three

Talend4 of 60Not in the top three

AWS Glue3 of 60Not in the top three

Apache Airflow3 of 60Not in the top three

Azure Data Factory3 of 60Not in the top three

Informatica3 of 60Not in the top three

Stitch3 of 60Not in the top three

Google Cloud Dataflow2 of 60Not in the top three

A head-to-head page exists where both products are in a category's top three. The other rows are the same fact without a page behind them, so they link to the product instead.

What carried it into the answer

The sites and pages cited by the answers that named MuleSoft. A fact about retrieval, not a lever on the model.

Citations exist only for the models that return a source list, four of the twelve in this edition, so these counts come from 4 of the 6 answers that named MuleSoft and are not a share of its labels.

Domains cited

hevodata.com3

integrate.io3

domo.com2

techrepublic.com2

bestdevops.com1

checkthat.ai1

corp.kaltura.com1

cotocus.com1

coworker.ai1

dacast.com1

Sixteen of the sixteen domain citations in answers naming MuleSoft came from somebody else's page.

Pages cited

integrate.io/blog/top-7-etl-tools3

domo.com/learn/article/etl-tools2

techrepublic.com/article/etl-tools2

bestdevops.com/top-10-event-streaming-platforms-tools-in-2025-features-pros-cons-compariso1

checkthat.ai/answers/what-are-the-best-enterprise-data-integration-tools1

corp.kaltura.com/blog/live-streaming-platforms1

cotocus.com/blog/top-10-event-streaming-platforms-features-pros-cons-comparison1

coworker.ai/blog/best-enterprise-data-integration-platforms1

Pages are listed as the models cited them.

Is this your product?

Claim this page

Claiming is free and changes nothing in the data. A claimed page shows a verified contact who is told when each edition publishes and when MuleSoft's standing changes by more than the noise floor; the right to propose corrections to the vendor table, meaning names the judge wrote that should or should not read as MuleSoft, applied by version and listed in the change log; and a one-line description supplied by the vendor and marked as such.

It does not get any change to labels, shares or verdicts, any preview, or any say over which quotes appear. A verification link goes to your work email; an address at mulesoft.com is approved on the spot, any other address is reviewed by hand.

Your name and company appear on the claimed page, or the company alone if you ask below. A title and a LinkedIn address appear there too if you give them, and are left off if you do not. Your email address is never published.