IT AI Index

Index › Vendors › AlertOps · September 2026 Edition

1 category · Named, not ranked

AlertOps

8Judge labels

0First 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

2 labels, too few to rank

A product needs 10 labels in a category before a share or quadrant is stated. AlertOps was named 2 times in Incidents, where incident.io led with 25%. The labels and the evidence are below, counted exactly.

By buyer segmentRead the same way at every buyer size.

Small business27 of 60

under the label threshold

Mid-market41 of 53

under the label threshold

Enterprise18 of 52

under the label threshold

In incidents · 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 AlertOps 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
Incident management and on-call	IT operations and endpoint	0%	41 of 53	50%	2	under 10 labels · led by incident.io at 25%

Movement

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

Model	Alternative	Negative	Labels
Claude Haiku 4.5	0	1	1
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	0	0	0
DeepSeek V4 Flash	0	0	0
Llama 4 Maverick	0	0	0
Qwen 3.7 Flash	0	0	0
Kimi K2	1	0	1
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

Paraphrase1 labelNone

Comparative1 labelNone

Budget-constrained2 labelsNone

Scale-constrained1 labelNone

Negative2 labelsNone

First choiceAlternativeMentionNegative8 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.

“Need full features, small budget | Spike ($7/user) or AlertOps ($8/user)” Kimi K2 · Incidents · budget 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.

“reviewers describe the interface as hard to navigate, particularly around managing on-call rosters” Claude Haiku 4.5 · Incidents · budget prompt · soft negative

Named alongside

The products named in the same answers as AlertOps, over the 8 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and AlertOps was named but was not.

ProductSame answerTook the first choice insteadHead to head

PagerDuty7 of 82Not in the top three

Opsgenie5 of 80Not in the top three

Jira Service Management4 of 80Not in the top three

Rootly4 of 80Not in the top three

incident.io3 of 81Not in the top three

Splunk On-Call3 of 80Not in the top three

xMatters3 of 80Not in the top three

Squadcast2 of 82Not in the top three

Spike.sh2 of 81Not in the top three

Grafana IRM2 of 80Not 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 AlertOps. 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 7 of the 8 answers that named AlertOps and are not a share of its labels.

Domains cited

rootly.com5

alertops.comYour site4

complyjet.com4

incident.io4

xurrent.com4

allquiet.app3

monday.com3

pagerduty.com3

atlassian.com2

dev.to2

Thirty of the thirty-four domain citations in answers naming AlertOps came from somebody else's page.

Pages cited

complyjet.com/blog/best-incident-management-software4

incident.io/blog/incident-management-tools-for-enterprise3

monday.com/blog/service/incident-management-software3

allquiet.app/blog/top-incident-management-solutions2

atlassian.com/incident-management/2024-state-of-incident-management2

gitnux.org/best/enterprise-incident-management-software2

hyperping.com/blog/best-incident-management-tools2

pagerduty.com/resources/devops/learn/opsgenie-alternatives2

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 AlertOps'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 AlertOps, 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 alertops.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.