SEON vs Sift
Six of fourteen models named SEON first on the direct prompt; two named Sift. SEON was named by thirteen of the fourteen models and Sift by fourteen and SEON carries 34 labels and Sift 44, so the shares are not directly comparable.
Named in three categories this edition.
Named in three categories 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 ecommerce fraud prevention page.
By framing
SEONFirst choices, of fourteen modelsSift
Across every category in the October 2026 Edition, SEON and Sift were named in the same answer seventy times, of the 121 answers naming SEON and the 161 naming Sift. In those answers Sift took the first choice seven times and SEON ten.
Every model, every framing
| Model | Direct | Paraphrase | Comparative | Budget-constrained | Scale-constrained | Negative |
|---|---|---|---|---|---|---|
| Claude Haiku 4.5 | | | | |||
| GPT-5.4 mini | | | | | ||
| Gemini 3.5 Flash | | | | | ||
| Perplexity Sonar | | | | |||
| Grok 4.1 Fast | | | | | ||
| 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 | | | | | |
SEON Sift first choice named as an alternative argued againstblank: not namedEach cell is one answer, SEON on the left and Sift on the right.The direct prompt
SEON first, Sift an alternative
6 of 14 modelsSift was named in the answer but not as the choice, or not at all.Sift first, SEON an alternative
2 of 14 modelsSEON was named in the answer but not as the choice, or not at all.Neither was the first choice, one was named
5 of 14 modelsThe answer put something else first and named one of the two as an alternative.Neither was named
1 of 14 modelsThe answer made no first choice from these two in this category.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
What the models said about SEON
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of eight in this category shown.
“SEON is often featured for flexible fraud signals, but it is not as clearly the cheapest option” Perplexity Sonar · budget prompt · soft negative
“SEON — Mixed Reviews (21% 1-star ratings) ... blackbox nature (opaque ML models)” GLM 4.7 FlashX · negative prompt · soft negative
“Examples of platforms using this model: Sift, Kount, SEON, Forter” Gemini 3.5 Flash · negative prompt · soft negative
“SEON offers modular fraud prevention tools with a free tier... particularly accessible to small and mid-market businesses” Claude Haiku 4.5 · budget prompt · first choice
“I'd recommend starting with ClearSale or SEON as they specifically target mid-market businesses” MiniMax M2.5 · direct prompt · first choice
“SEON is highly recommended for mid-market B2B companies that have an in-house operations or risk team” Gemini 3.5 Flash · direct prompt · first choice
What the models said about Sift
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of eight in this category shown.
“Can be complex to configure; occasional false positives requiring manual review. Not ideal for very small teams due to setup overhead.” Grok 4.1 Fast · negative prompt · soft negative
“Unlike consumer-focused tools (like Sift or Stripe Radar), these are specifically designed for B2B payment workflows” Kimi K2 · paraphrase prompt · soft negative
“Some users note that the system can occasionally generate false positives, which may require additional review time.” Claude Haiku 4.5 · negative prompt · soft negative
“Start with Sift for most mid-market B2B ecommerce—it's consistently #1 in G2 rankings for balanced performance without overkill.” Grok 4.1 Fast · direct prompt · first choice
“Sift maintains #1 position across all fraud prevention categories in G2's Fall 2025 Reports” Muse Glimmer 30B · comparative prompt · first choice
“Sift - Top-rated on G2 for real-time detection.” Grok 4.1 Fast · comparative 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.