One of fourteen models named AppOmni first on the direct prompt; three named Adaptive Shield. AppOmni was named by fourteen of the fourteen models and Adaptive Shield by ten and AppOmni carries 52 labels and Adaptive Shield 22, so the shares are not directly comparable.
Named in one category this edition.
Named in one category this edition.
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 saas security posture management page.
Across every category in the November 2026 Edition, AppOmni and Adaptive Shield were named in the same answer sixty-two times, of the 165 answers naming AppOmni and the 73 naming Adaptive Shield. In those answers Adaptive Shield took the first choice three times and AppOmni twelve.
| Model | Direct | Paraphrase | Comparative | Budget-constrained | Scale-constrained | Negative |
|---|---|---|---|---|---|---|
| Claude Haiku 4.5 | AS | |||||
| GPT-5.4 mini | AS | |||||
| Gemini 3.5 Flash | ||||||
| Perplexity Sonar | ||||||
| Grok 4.20 | ||||||
| Mistral Small | ||||||
| DeepSeek V4 Flash | ||||||
| Llama 4 Maverick | ||||||
| Qwen 3.7 Flash | ||||||
| Kimi K2 | ||||||
| GLM 4.7 FlashX | ||||||
| MiniMax M2.5 | ||||||
| GPT-6 Luna | ||||||
| Muse Glimmer 30B |
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.
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of eight in this category shown.
“Be cautious with AppOmni. Recent independent AI-driven sentiment analysis ... flags it as one to potentially avoid or approach carefully” Grok 4.20 · negative prompt · hard negative
“Avoid enterprise-first platforms like AppOmni, Obsidian Security (paid tier), and CrowdStrike Falcon SSPM if you're a small business.” Muse Glimmer 30B · negative prompt · hard negative
“What to Avoid on a Budget ... (AppOmni, Palo Alto Prisma, Zscaler, CrowdStrike Falcon Shield) require sales quotes” Kimi K2 · budget prompt · hard negative
“Choose AppOmni if you run heavily customized instances of Salesforce, ServiceNow, or Workday that demand granular configuration oversight.” Gemini 3.5 Flash · comparative prompt · first choice
“Best for deep configuration coverage and visibility into SaaS apps like Salesforce, Slack, and Microsoft 365.” Mistral Small · paraphrase prompt · first choice
“AppOmni remains the go-to for deep configuration management of tier-1 SaaS like Salesforce and Workday.” Claude Haiku 4.5 · comparative prompt · first choice
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of eight in this category shown.
“Heavyweight enterprise solutions (such as AppOmni, Adaptive Shield/CrowdStrike Falcon Shield, or Varonis) often carry high annual contract minimums” Gemini 3.5 Flash · budget prompt · soft negative
“Also labeled a "challenger" in recent indices, with some negative sentiment... can feel limited in breadth or remediation compared to leaders” Grok 4.20 · negative prompt · soft negative
“Some reviews suggest caution due to potential integration or support issues following the acquisition.” Mistral Small · negative prompt · soft negative
“Best for: Organizations needing continuous monitoring and control of their entire SaaS stack... often praised for its depth and breadth of coverage.” Mistral Small · comparative prompt · first choice
“Adaptive Shield and AppOmni are top contenders, with Adaptive Shield being especially popular for its comprehensive features and ease of use” Mistral Small · direct prompt · first choice
“Go with Wing Security or Adaptive Shield. They offer turn-key configurations, quick agentless API deployment” Gemini 3.5 Flash · paraphrase prompt · first choice
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.