IT AI Index
Index Vendors › Orca · September 2026 Edition
5 categories · Ranked

Orca

90Judge labels
1First choices
24Negative labels
12 of 12Models named it
5Categories
September 2026 Edition. Every number here is derived from the raw labels under vendor table vv2026-09.2, every buyer segment counted.
Best standing
2% in CNAPP for mid-market buyers
Rank 6 of 57 in the mid-market standingaccepted challenger
0 of 12 models made it the first choice on the direct prompt; 20% of its 10 labels there were negative.
By buyer segmentRead the same way at every buyer size.
In cnapp · 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 Orca 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.
CategoryFunctionShareRankNegative rateLabelsQuadrant
Cloud-native application protectionCloud and infrastructure2%6 of 5720%10accepted challenger
Cloud security posture managementCloud and infrastructure0%40 of 5333%9under 10 labels · led by Wiz at 43%
Container and Kubernetes securityCloud and infrastructure0%25 of 7820%5under 10 labels · led by Aqua Security at 18%
Vulnerability management platformsSecurity operations0%32 of 800%3under 10 labels · led by Rapid7 InsightVM at 45%
Attack surface managementSecurity operations0%78 of 1040%1under 10 labels · led by Intruder at 59%

Movement

This is the first edition on this tier, so no move can be computed for Orca 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 Orca across every prompt where it was named for a mid-market B2B company. Twelve models, six prompts per category.
ModelFirst choiceAlternativeMentionNegativeLabels
Claude Haiku 4.500011
GPT-5.4 mini01023
Gemini 3.5 Flash00112
Perplexity Sonar00101
Grok 4.1 Fast11215
Mistral Small00101
DeepSeek V4 Flash00415
Llama 4 Maverick03104
Qwen 3.7 Flash00202
Kimi K201203
GLM 4.7 FlashX00000
MiniMax M2.500101

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
Direct11 labelsNone
Paraphrase1 labelNone
Comparative9 labelsNone
Budget-constrained23 labelsNone
Scale-constrained27 labels1
Negative19 labels1not counted in share
First choiceAlternativeMentionNegative90 labels in all, every segment counted; 1 of the 2 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.

“Start with agentless leaders (Wiz, Orca)” Grok 4.1 Fast · CNAPP · scale prompt · first choice
“Orca is an agentless pioneer with strong data security and is a good fit for teams that want quick onboarding” Llama 4 Maverick · CSPM · comparative prompt · alternative
“often a good fit when you want strong risk visibility and agentless-style deployment simplicity” GPT-5.4 mini · CSPM · direct prompt · alternative
“Wiz or Orca are suitable for companies that want agentless-first workload visibility” Llama 4 Maverick · Container security · direct 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.

“Orca/Wiz | $7K+/mo (small) | Agentless full CNAPP | Avoid for tight budgets” Grok 4.1 Fast · CNAPP · budget prompt · hard negative
“What to avoid at low budget ... overkill for a company on a limited budget” DeepSeek V4 Flash · CSPM · budget prompt · hard negative
“AI-generated remediation code appeared in multiple platforms (Wiz, Orca, Prisma Cloud) but accuracy varies enough that auto-applying AI fixes remains risky” Claude Haiku 4.5 · CSPM · negative prompt · soft negative
“often strong, but they tend to be more expensive and are usually better suited to larger or more mature security programs” GPT-5.4 mini · CSPM · budget prompt · soft negative

Named alongside

The products named in the same answers as Orca, over the 90 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and Orca was named but was not.
ProductSame answerTook the first choice insteadHead to head
Wiz86 of 9010Not in the top three
Microsoft Defender for Cloud58 of 9022Not in the top three
Prisma Cloud57 of 902Not in the top three
Sysdig30 of 901Not in the top three
Prowler22 of 9010Not in the top three
Aqua Security20 of 902Not in the top three
Falco15 of 905Not in the top three
Trivy14 of 904Not in the top three
Snyk13 of 902Not in the top three
AWS Security Hub12 of 905Not 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 Orca. 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 78 of the 90 answers that named Orca and are not a share of its labels.

Domains cited

cyberpress.org50
gbhackers.com43
expertinsights.com34
cybersecuritynews.com32
cloudaware.com28
orca.securityYour site25
cipherssecurity.com17
decryptiondigest.com17
microsoft.com15
wiz.io15

251 of the 276 domain citations in answers naming Orca came from somebody else's page.

Pages cited

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 Orca'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 Orca, 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 orca.security 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.