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AI governance platforms · November 2026 Edition

dope.security vs Microsoft Purview

Two of fourteen models named dope.security first on the direct prompt; one named Microsoft Purview. dope.security was named by seven of the fourteen models and Microsoft Purview by twelve and dope.security carries 14 labels and Microsoft Purview 24, so the shares are not directly comparable.

dope.security

accepted challenger

Named in three categories this edition.

Microsoft Purview

accepted challenger

Named in eleven categories this edition.

First-choice share12%5%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate0%12%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#2#4A position in a field of 10; printed, not drawn.
Labels1424A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, dope.security reading right to left. Rank and label count are printed, not drawn.Credo AI was named alongside these two in ten of the fourteen direct answers. Credo AI vs dope.security · Credo AI vs Microsoft Purview · dope.security vs Strac

Share is the count of first choices across the direct, paraphrase, budget and scale prompts over all fourteen models, for a mid-market B2B company; rank is within the category; every quote names the model and the prompt it came from. Both figures come from the AI governance platforms page.

By framing

How many of the fourteen models made each the first choice, per way of asking, and how many argued against it.
dope.securityFirst choices, of fourteen modelsMicrosoft Purview
Direct21
Paraphrase511 against Microsoft Purview
Comparative00
Budget-constrained01
Scale-constrained00
Negative002 against Microsoft Purview
Bars are first choices, 0 to 14 each sideModels that argued againstA model can name both, so the two sides of a row do not sum to fourteen.

Every model, every framing

The eighty-four answers behind the chart above, one cell each: where dope.security and Microsoft Purview stood in it.
ModelDirectDSParaphraseDSComparativeDSBudget-constrainedDSScale-constrainedDSNegativeDS
Claude Haiku 4.5
GPT-5.4 mini
Gemini 3.5 Flash
Perplexity Sonar
Grok 4.20DS
Mistral SmallDSDS
DeepSeek V4 FlashDSDS
Llama 4 MaverickDSDS
Qwen 3.7 FlashDSDS
Kimi K2
GLM 4.7 FlashXDSDS
MiniMax M2.5
GPT-6 Luna
Muse Glimmer 30BDSDS
DS dope.security Microsoft PurviewDS first choiceDS named as an alternativeDS argued againstblank: not namedEach cell is one answer, dope.security on the left and Microsoft Purview on the right.

The direct prompt

The plain question, one answer per model, grouped by where dope.security and Microsoft Purview stood in it.

dope.security first, Microsoft Purview not the choice

2 of 14 modelsMicrosoft Purview was named in the answer but not as the choice, or not at all.
Llama 4 Maverickdope.security alternatives: Cakewalk, Govern365, Pillar Security
Muse Glimmer 30BStrac, dope.security alternatives: Credo AI, Govarna, IBM watsonx.governance, OneTrust AI Governance

Microsoft Purview first, dope.security an alternative

1 of 14 modelsdope.security was named in the answer but not as the choice, or not at all.
Grok 4.20Microsoft Purview alternatives: Credo AI, Drata, Holistic AI, Vanta, dope.security

Neither was the first choice, one was named

4 of 14 modelsThe answer put something else first and named one of the two as an alternative.
Perplexity SonarCredo AI alternatives: AWS SageMaker AI Governance, Govarna, Microsoft Purview, OneTrust AI Governance, Speakeasy
Mistral SmallGovarna alternatives: Govern365, dope.security
Qwen 3.7 FlashGovarna alternatives: Credo AI, Govern365, dope.security
GLM 4.7 FlashXGovern365 alternatives: IBM watsonx.governance, dope.security

Neither was named

7 of 14 modelsThe answer made no first choice from these two in this category.
Claude Haiku 4.5Credo AI alternatives: Govern365, Holistic AI, Walled AI
GPT-5.4 miniCredo AI alternatives: IBM watsonx.governance, OneTrust AI Governance
Gemini 3.5 FlashCredo AI alternatives: Fiddler AI, ModelOp Center, Trustible, Vanta
DeepSeek V4 FlashVanta alternatives: Credo AI, Govarna, Holistic AI
Kimi K2Govarna alternatives: Vanta
MiniMax M2.5Credo AI alternatives: Drata, Govarna, IBM watsonx.governance
GPT-6 LunaTrustible alternatives: Credo AI, OneTrust AI Governance

Bold names in an answer are the products the judge labeled a first choice; a model naming several gives each of them that label. The full answer text for every row is in the record.

By buyer segment

The same question asked on behalf of a different buyer. Each standing is computed within its segment and they are never added together. The figures above are the mid-market standing, which is the one the category orders by.
Small business
dope.security is not named for this buyer.
Microsoft Purview2%#5 of 12
dope.security—not named
The full small business standing →
Mid-marketThe figures above
The order flips: dope.security leads at mid-market.
dope.security12%#2 of 10
Microsoft Purview5%#4 of 10
The full mid-market standing →
Enterprise
dope.security is not named for this buyer.
Microsoft Purview7%#4 of 11
dope.security—not named
The full enterprise standing →

What the models said about dope.security

Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Three of three in this category shown.

“Enforcement and shadow-AI control now - e.g. dope.security - to discover every AI app, enforce enterprise-only accounts and block sensitive data in prompts.” Muse Glimmer 30B · paraphrase prompt · first choice
“The author argues the best AI governance tool for a mid-size company is "an enforcement layer that sees and controls AI use on every laptop"” Muse Glimmer 30B · direct prompt · first choice
“dope.security - discovers every AI app in use, enforces enterprise-only accounts, and blocks sensitive data in prompts from one console.” Llama 4 Maverick · paraphrase prompt · first choice

What the models said about Microsoft Purview

No label in this category carried a quote.

Also compared

Comparisons are drawn for the top eight products in each category, each against each. The output is the models' output; nothing here is a recommendation by the index.