IT AI Index

Index › Vendors › Checkly · September 2026 Edition

1 category · Named, not ranked

Checkly

2Judge labels

0First choices

2Negative labels

2 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. Checkly was named 2 times in Infra monitoring, where Site24x7 led with 24%. 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-market63 of 65

under the label threshold

Enterprisenot named

No model named it for this buyer.

In infra monitoring · 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 Checkly 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
Infrastructure monitoring	IT operations and endpoint	0%	63 of 65	100%	2	under 10 labels · led by Site24x7 at 24%

Movement

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

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

Direct0 labelsNone

Paraphrase0 labelsNone

Comparative0 labelsNone

Budget-constrained0 labelsNone

Scale-constrained0 labelsNone

Negative2 labelsNone

First choiceAlternativeMentionNegative2 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.

“has no built-in infrastructure checks ... Avoid if you need to monitor server health” GLM 4.7 FlashX · Infra monitoring · negative prompt · hard negative

“not ideal if you need deep infrastructure or protocol-level checks” Perplexity Sonar · Infra monitoring · negative prompt · soft negative

Named alongside

The products named in the same answers as Checkly, over the 2 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and Checkly was named but was not.

ProductSame answerTook the first choice insteadHead to head

Datadog2 of 20Not in the top three

New Relic2 of 20Not in the top three

Pingdom2 of 20Not in the top three

Zabbix2 of 20Not in the top three

Netdata1 of 21Not in the top three

Dash01 of 20Not in the top three

Dynatrace1 of 20Not in the top three

Grafana1 of 20Not in the top three

Nagios1 of 20Not in the top three

Prometheus1 of 20Not 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 Checkly. 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 2 of the 2 answers that named Checkly and are not a share of its labels.

Domains cited

ciopages.com2

dash0.com2

dotcom-monitor.com2

gartner.com2

instatus.com2

middleware.io2

netdata.cloud2

newrelic.com2

signoz.io2

betterstack.com1

Nineteen of the nineteen domain citations in answers naming Checkly came from somebody else's page.

Pages cited

ciopages.com/articles/infrastructure-monitoring-guide2

dash0.com/comparisons/infrastructure-monitoring-tools2

dotcom-monitor.com/blog/best-tools-for-synthetic-infrastructure-monitoring2

gartner.com/reviews/market/infrastructure-monitoring-tools2

instatus.com/blog/infrastructure-monitoring-tools2

middleware.io/blog/infrastructure-monitoring-tools2

netdata.cloud/resources/best-infrastructure-monitoring-tools2

newrelic.com/blog/infrastructure-monitoring/how-to-choose-the-best-infrastructure-monitori2

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 Checkly'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 Checkly, 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 checkly.ai 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.