| Category | Function | Share | Rank | Negative rate | Labels | Quadrant | Since September 2026 |
|---|---|---|---|---|---|---|---|
| AI SOC agents | Security operations | 4% | 4 of 104 | 7% | 14 | accepted challenger | |
| AI security platforms | Security operations | 2% | 21 of 233 | 0% | 2 | under 10 labels · led by SentinelOne Singularity at 11% |
| Model | First choice | Alternative | Mention | Negative | Labels |
|---|---|---|---|---|---|
| Claude Haiku 4.5 | 0 | 0 | 0 | 0 | 0 |
| GPT-5.4 mini | 0 | 0 | 0 | 1 | 1 |
| Gemini 3.5 Flash | 0 | 0 | 1 | 0 | 1 |
| Perplexity Sonar | 1 | 0 | 1 | 0 | 2 |
| Grok 4.1 Fast | 0 | 2 | 2 | 0 | 4 |
| Mistral Small | 1 | 1 | 0 | 0 | 2 |
| DeepSeek V4 Flash | 0 | 1 | 0 | 0 | 1 |
| Llama 4 Maverick | 0 | 1 | 0 | 0 | 1 |
| Qwen 3.7 Flash | 1 | 0 | 0 | 0 | 1 |
| Kimi K2 | 0 | 0 | 1 | 0 | 1 |
| GLM 4.7 FlashX | 0 | 0 | 0 | 0 | 0 |
| MiniMax M2.5 | 0 | 0 | 1 | 0 | 1 |
| GPT-6 Luna | 0 | 1 | 0 | 0 | 1 |
| Muse Glimmer 30B | 0 | 0 | 0 | 0 | 0 |
Verbatim evidence the judge attached to positive labels.
“frequently cited as the top choice for mid-market organizations because its pricing model does not scale with the number of alerts generated” Qwen 3.7 Flash · AI SOC agents · direct prompt · first choice
“If you want the single best fit for most mid-market B2B companies, I would lean toward SentinelOne Purple AI” Perplexity Sonar · AI security · direct prompt · first choice
“SentinelOne Purple AI is highly recommended for mid-market to enterprise SOCs” Mistral Small · AI SOC agents · direct prompt · first choice
“Focuses on automating SOC (Security Operations Center) tasks, enabling faster, more efficient threat detection and response” Mistral Small · AI security · comparative prompt · alternative
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.
“I'm being a bit more cautious here because the comparison pages are vendor-curated and can be marketing-heavy.” GPT-5.4 mini · AI SOC agents · comparative prompt · soft negative
Citations exist only for the models that return a source list, five of the fourteen in this edition, so these counts come from 36 of the 36 answers that named SentinelOne Purple AI and are not a share of its labels.
150 of the 159 domain citations in answers naming SentinelOne Purple AI came from somebody else's page.
Pages are listed as the models cited them.
Search figures are US estimates from DataForSEO, read October 5, 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.
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.
What SentinelOne Purple AI's own pages state, read October 5, 2026: sentinelone.com/platform/purple, sentinelone.com/platform/ai-siem, sentinelone.com/platform/securing-ai, university.sentinelone.com/courses/purple-ai, sentinelone.com/platform/ai-cybersecurity. A claimed page can correct any of them.
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 SentinelOne Purple AI'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 SentinelOne Purple AI, applied by version and listed in the change log; and a one-line description supplied by the vendor and marked as such.
A new claim receives the current edition's vendor brief for SentinelOne Purple AI by email, built from the raw record of the edition. It shows: