Every category where a model named Strac 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
Data loss prevention	Security operations	0%	14 of 84	0%	10	accepted challenger

Movement

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

Model	First choice	Alternative	Mention	Labels
Claude Haiku 4.5	1	0	0	1
GPT-5.4 mini	0	0	0	0
Gemini 3.5 Flash	1	0	0	1
Perplexity Sonar	0	0	2	2
Grok 4.1 Fast	0	0	0	0
Mistral Small	1	0	0	1
DeepSeek V4 Flash	0	3	0	3
Llama 4 Maverick	0	0	1	1
Qwen 3.7 Flash	0	0	0	0
Kimi K2	0	0	0	0
GLM 4.7 FlashX	0	0	0	0
MiniMax M2.5	0	0	1	1

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

Direct5 labels1

Paraphrase1 labelNone

Comparative9 labels3not counted in share

Budget-constrained1 labelNone

Scale-constrained3 labelsNone

Negative3 labels2not counted in share

First choiceAlternativeMentionNegative22 labels in all, every segment counted; 1 of the 6 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.

“1. Strac - Best for: SaaS, cloud, GenAI, browser, endpoint, and MCP environments... Strengths: Highly rated for quick integration, high accuracy” Mistral Small · DLP · comparative prompt · first choice

“Strac leads for teams whose data lives in SaaS, cloud, GenAI/MCP, and on endpoints, because it both detects and remediates” Claude Haiku 4.5 · DLP · comparative prompt · first choice

“modern data-lineage and browser-focused DLP tools (e.g., Cyberhaven, Nightfall, Strac, or Next DLP)” Gemini 3.5 Flash · DLP · negative prompt · first choice

“Strong cloud-native and SaaS-focused options (e.g., Netskope, Strac, Forcepoint, Proofpoint, Mimecast) may fit better.” DeepSeek V4 Flash · DLP · scale 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 Strac, over the 22 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and Strac was named but was not.

ProductSame answerTook the first choice insteadHead to head

Microsoft Purview DLP19 of 227Not in the top three

Forcepoint DLP17 of 222Not in the top three

Symantec Data Loss Prevention17 of 220Not in the top three

Nightfall AI13 of 220Not in the top three

Netskope DLP12 of 220Not in the top three

Proofpoint Enterprise DLP11 of 220Not in the top three

Cyberhaven9 of 220Not in the top three

Zscaler8 of 220Not in the top three

Safetica6 of 220Not in the top three

CurrentWare3 of 220Not 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 Strac. 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 19 of the 22 answers that named Strac and are not a share of its labels.

Domains cited

strac.ioYour site19

gartner.com14

underdefense.com12

forcepoint.com11

learn.g2.com10

miniorange.com9

currentware.com8

cyberhaven.com8

proofpoint.com8

blog.scalefusion.com7

Eighty-seven of the 106 domain citations in answers naming Strac came from somebody else's page.

Pages cited

gartner.com/reviews/market/data-loss-prevention14

strac.io/blog/top-data-loss-prevention-dlp-tools13

underdefense.com/blog/dlp-solutions12

forcepoint.com/blog/insights/best-dlp-software10

learn.g2.com/best-data-loss-prevention-software10

miniorange.com/blog/top-data-loss-prevention-tools9

strac.io/blog/top-7-data-loss-prevention-solutions-comparison-and-dlp-evaluation-checklist9

currentware.com/blog/best-data-loss-prevention-software8

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 Strac'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 Strac, 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 strac.io 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.