GTM AI Index

Index › Vendors › Glean · September 2026 Edition

1 category · Named, not ranked

Glean

13Judge labels

0First choices

3Negative labels

7 of 12Models named it

1Category

September 2026 Edition. Every number here is derived from the raw labels under vendor table v2026-09-16.3, 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. Glean was named 3 times in Knowledge base, where Notion led with 18%. The labels and the evidence are below, counted exactly.

By buyer segmentRead the same way at every buyer size.

Small business71 of 82

under the label threshold

Mid-market33 of 96

under the label threshold

Enterprise16 of 94

under the label threshold

In knowledge base · 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 Glean 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
Knowledge base and self-service	Customer	0%	33 of 96	0%	3	under 10 labels · led by Notion at 18%

Movement

This is the first edition on this tier, so no move can be computed for Glean yet. The next is due October 1, 2026. 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 Glean across every prompt where it was named for a mid-market B2B company. Twelve models, six prompts per category.

Model	Alternative	Mention	Labels
Claude Haiku 4.5	0	0	0
GPT-5.4 mini	0	1	1
Gemini 3.5 Flash	1	1	2
Perplexity Sonar	0	0	0
Grok 4.1 Fast	0	0	0
Mistral Small	0	0	0
DeepSeek V4 Flash	0	0	0
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

Direct1 labelNone

Paraphrase0 labelsNone

Comparative5 labelsNone

Budget-constrained0 labelsNone

Scale-constrained3 labelsNone

Negative4 labels1not counted in share

First choiceAlternativeMentionNegative13 labels in all, every segment counted; 0 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.

“Best For: Medium-to-large enterprises with heavily fragmented internal documentation across dozens of tools.” Gemini 3.5 Flash · Knowledge base · comparative prompt · alternative

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.

No model argued against it.

Named alongside

The products named in the same answers as Glean, over the 13 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and Glean was named but was not.

ProductSame answerTook the first choice insteadHead to head

Notion10 of 130Not in the top three

Confluence9 of 132Not in the top three

Guru9 of 130Not in the top three

Zendesk Guide9 of 130Not in the top three

Document3608 of 131Not in the top three

Bloomfire4 of 130Not in the top three

SharePoint3 of 130Not in the top three

Atlassian Confluence2 of 131Not in the top three

GitBook2 of 130Not in the top three

Google Drive2 of 130Not 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 Glean. 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 3 of the 13 answers that named Glean and are not a share of its labels.

Domains cited

gartner.com2

monday.com2

slite.com2

assembly.com1

atlan.com1

atlassian.com1

betterdocs.co1

brewsterconsulting.io1

egain.com1

ferndesk.com1

Thirteen of the thirteen domain citations in answers naming Glean came from somebody else's page.

Pages cited

gartner.com/reviews/market/knowledge-management-software2

monday.com/blog/service/enterprise-knowledge-base-platforms2

slite.com/learn/knowledge-base-softwares2

assembly.com/blog/best-knowledge-base-software1

atlan.com/know/llm-knowledge-base-tools1

atlassian.com/software/confluence/comparison/confluence-vs-notion1

betterdocs.co/knowledge-base-challenges-you-should-look-out1

brewsterconsulting.io/best-ai-knowledge-base-20261

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 Glean'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 Glean, 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 glean.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.