Small business=heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked.
0%from 0% in September 2026
Inside the floor by 11 pointsRank 47 → 56 of 77
OpenDLP
15Judge labels
0First choices
6Negative labels
7 / 14Models named it
3Categories
October 2026 Edition. Every number here is derived from the raw labels under vendor table v2026-10.8, every buyer segment counted.
Standing
8 labels, too few to rank
A product needs 10 labels in a category before a share or quadrant is stated. OpenDLP was named 8 times in DLP and 2 other categories, where Microsoft Purview DLP led with 46%. The labels and the evidence are below, counted exactly.
By buyer segmentRead the same way at every buyer size.
Small business76 of 82
0%4 labels
under the label threshold
Mid-market25 of 89
0%5 labels
under the label threshold
Enterprise57 of 60
0%1 label
under the label threshold
In dlp · 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 OpenDLP 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 | Since September 2026 |
|---|---|---|---|---|---|---|---|
| Data loss prevention | Security operations | 0% | 25 of 89 | 20% | 5 | under 10 labels · led by Microsoft Purview DLP at 46% | =heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked. |
| Insider risk management | Security operations | 0% | 77 of 84 | 50% | 2 | under 10 labels · led by Microsoft Purview Insider Risk Management at 22% | |
| Client-side protection | Security operations | 0% | 97 of 120 | 0% | 1 | under 10 labels · led by cside at 13% |
Movement
Since September 2026, OpenDLP held within the floor in all three categories: no change cleared 11 points.
Best category · DLP · by segment
Mid-market=heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked.
0%from 0% in September 2026
Inside the floor by 11 pointsRank 70 → 26 of 80
EnterprisenewNew since September 2026: not ranked then, 0% now.
0%from 0% in September 2026
Inside the floor by 11 pointsRank 53 of 55, unchanged
All categories · Mid-market
| Category | September 2026 | Now | Change | Reading | Rank |
|---|---|---|---|---|---|
| DLP | 0% | 0% | =heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked. | Within noise | Rank 70 → 25 of 89 |
| Insider risk | 0% | 0% | newNew since September 2026: not ranked then, 0% now. | New this edition | Rank 77 of 84, unchanged |
| Client-side protection | 0% | 0% | newNew since September 2026: not ranked then, 0% now. | New this edition | Rank 97 of 120, unchanged |
Shares here are read over the models both editions asked, so they can differ by a point or two from the standing above, which counts every model in this edition.
The floor is 11 points of share, measured: how far the models move a leader on their own when the same questions are asked twice with nothing changed. A larger change is movement; a smaller one is noise, and both are shown. Movement is read over the twelve models both editions asked; GPT-6 Luna, Muse Glimmer 30B joined this edition and are in the standing but not yet in the comparison. How the floor is measured · The editions
By model
How each model treated OpenDLP across every prompt where it was named for a mid-market B2B company. Fourteen models, six prompts per category.ShowHide
By model
How each model treated OpenDLP across every prompt where it was named for a mid-market B2B company. Fourteen models, six prompts per category.
ShowHide| Model | First choice | Alternative | Mention | Negative | Labels |
|---|---|---|---|---|---|
| Claude Haiku 4.5 | 0 | 0 | 1 | 0 | 1 |
| GPT-5.4 mini | 0 | 0 | 0 | 0 | 0 |
| Gemini 3.5 Flash | 0 | 0 | 0 | 0 | 0 |
| Perplexity Sonar | 0 | 0 | 0 | 1 | 1 |
| Grok 4.20 | 0 | 1 | 0 | 1 | 2 |
| Mistral Small | 0 | 1 | 0 | 0 | 1 |
| DeepSeek V4 Flash | 0 | 0 | 0 | 0 | 0 |
| Llama 4 Maverick | 0 | 0 | 0 | 0 | 0 |
| Qwen 3.7 Flash | 0 | 0 | 0 | 0 | 0 |
| Kimi K2 | 0 | 1 | 1 | 0 | 2 |
| GLM 4.7 FlashX | 0 | 0 | 0 | 0 | 0 |
| MiniMax M2.5 | 0 | 0 | 0 | 0 | 0 |
| GPT-6 Luna | 0 | 0 | 0 | 0 | 0 |
| Muse Glimmer 30B | 0 | 1 | 0 | 0 | 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
Direct0 labelsNone
Paraphrase1 labelNone
Comparative1 labelNone
Budget-constrained11 labelsNone
Scale-constrained0 labelsNone
Negative2 labelsNone
First choiceAlternativeMentionNegative15 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.
“Fully free, on-premise tools for scanning files/databases and basic monitoring... cons: Outdated interfaces, no cloud support” Grok 4.20 · DLP · budget prompt · alternative
“Free Open Source Option... Lacks cloud-native features and AI classification” Kimi K2 · DLP · budget prompt · alternative
“MyDLP Community Edition for prevention + OpenDLP for discovery” Muse Glimmer 30B · DLP · budget prompt · alternative
“consider open-source or self-hosted options like OpenDLP” Mistral Small · DLP · 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.
“Outdated open-source/on-prem tools like OpenDLP and MyDLP, which one 2026 review explicitly labels "outdated."” Perplexity Sonar · DLP · negative prompt · hard negative
“Truly zero cost but require technical expertise and lack advanced analytics—best as supplements, not full solutions” Grok 4.20 · Insider risk · budget prompt · soft negative
Named alongside
The products named in the same answers as OpenDLP, over the 15 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and OpenDLP was named but was not.ShowHide
Named alongside
The products named in the same answers as OpenDLP, over the 15 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and OpenDLP was named but was not.
ShowHideProductSame answerTook the first choice insteadHead to head
A head-to-head page exists where both products are among a category's top eight. 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 OpenDLP. A fact about retrieval, not a lever on the model.
Citations exist only for the models that return a source list, five of the fourteen in this edition, so these counts come from 14 of the 15 answers that named OpenDLP and are not a share of its labels.
Domains cited
kickidler.com12
currentware.com9
aimultiple.com8
spotsaas.com7
techradar.com7
us.fitgap.com7
forcepoint.com6
nightfall.ai6
checkpoint.com5
comparitech.com5
No domain is on file for OpenDLP, so its own site is not marked.
Pages cited
Pages are listed as the models cited them.
Search and answers
Where OpenDLP stands in Google search beside where it stands in the models' answers.ShowHide
Search and answers
Where OpenDLP stands in Google search beside where it stands in the models' answers.
ShowHideIn search
Google, US estimates- Searches for its name, Google
- 90 a month (“opendlp”)
- AI search demand for its name, est.
- 1 a month
- Its own site
- No site of its own on file, so no site figures
In answers
This editionShare of first choices
0%
rank 25 of 89 in DLP
Segment leader
46%
Microsoft Purview DLP
- First choices
- 0 across its categories
- Named in
- 15 answers
- Its own site cited
- No site on file to match
Search figures are US estimates from DataForSEO, read September 28, 2026; AI search demand is its modeled, directional estimate, not a count of queries to any assistant. The answers are this edition's. Two measurements side by side: neither is read as the cause of the other.
Follow OpenDLP
An email the morning each edition publishes: where this product moved, where it held, and by how much against the noise floor. One address, confirmed by a click; a stop link in every email.
Already following? Everything you follow, with a stop for each.
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 OpenDLP'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 OpenDLP, applied by version and listed in the change log; and a one-line description supplied by the vendor and marked as such.
What a new claim receivesHide what a new claim receives
A new claim receives the current edition's vendor brief for OpenDLP by email, built from the raw record of the edition. It shows:
- where OpenDLP is named, by buyer and by framing, and which cells hold its first choices;
- the claims the models make when they name it, ranked, with the strongest and the weakest quoted;
- its vocabulary against the segment leader's, and the pages the models cited;
- who was chosen in the answers that did not name OpenDLP, and every reason the record gives;
- a battlecard for each top rival: the head-to-head split, why they win, and the reservation quoted against them;
- one page of published figures cleared to show a buyer.