IT AI Index

Index › Vendors › C3 AI · September 2026 Edition

1 category · Named, not ranked

C3 AI

4Judge labels

0First choices

1Negative labels

4 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

2 labels, too few to rank

A product needs 10 labels in a category before a share or quadrant is stated. C3 AI was named 2 times in ML platforms, where Azure Machine Learning led with 17%. 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-market79 of 99

under the label threshold

Enterprise18 of 75

under the label threshold

In ml platforms · 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 C3 AI 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
ML platforms	Data platform	0%	79 of 99	50%	2	under 10 labels · led by Azure Machine Learning at 17%

Movement

This is the first edition on this tier, so no move can be computed for C3 AI 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 C3 AI across every prompt where it was named for a mid-market B2B company. Twelve models, six prompts per category.

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

Paraphrase0 labelsNone

Comparative1 labelNone

Budget-constrained0 labelsNone

Scale-constrained0 labelsNone

Negative1 labelNone

First choiceAlternativeMentionNegative4 labels in all, every segment counted; 0 of the 0 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.

No positive label carried a quote.

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.

“Long sales cycles, complex change management; geared to large enterprises, poor fit for small orgs” DeepSeek V4 Flash · ML platforms · negative prompt · soft negative

Named alongside

The products named in the same answers as C3 AI, over the 4 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and C3 AI was named but was not.

ProductSame answerTook the first choice insteadHead to head

Amazon SageMaker4 of 40Not in the top three

Azure Machine Learning4 of 40Not in the top three

Google Vertex AI4 of 40Not in the top three

Databricks3 of 41Not in the top three

DataRobot3 of 40Not in the top three

Dataiku3 of 40Not in the top three

Palantir3 of 40Not in the top three

H2O.ai2 of 40Not in the top three

SAS2 of 40Not in the top three

Databricks Mosaic AI1 of 41Not 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 C3 AI. 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 4 answers that named C3 AI and are not a share of its labels.

Domains cited

research.oz.spotlightar.com4

dagshub.com3

g2.com3

learn.g2.com3

aiadvisorypractice.com2

checkthat.ai2

tinyctl.dev2

21998286.fs1.hubspotusercontent-na1.net1

aistrategy.guide1

arxiv.org1

Twenty-two of the twenty-two domain citations in answers naming C3 AI came from somebody else's page.

Pages cited

research.oz.spotlightar.com/reports/forrester-wave-ai-ml-platforms-q3-2024/leaders4

dagshub.com/blog/top-deep-learning-platforms3

checkthat.ai/answers/what-are-the-best-ai-ml-platforms2

g2.com/categories/data-science-and-machine-learning-platforms/enterprise2

learn.g2.com/best-data-science-ml-platforms2

learn.g2.com/best-machine-learning-tools2

tinyctl.dev/roundups/machine-learning-platforms2

seclab.illinois.edu/wp-content/uploads/2021/05/long2020understanding.pdf1

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 C3 AI'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 C3 AI, 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 c3ai.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.