EntityKeeper vs MinuteBox
Zero of fourteen models named EntityKeeper first on the direct prompt; zero named MinuteBox. EntityKeeper was named by fourteen of the fourteen models and MinuteBox by eight and EntityKeeper carries 40 labels and MinuteBox 16, 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 entity management page.
By framing
EntityKeeperFirst choices, of fourteen modelsMinuteBox
Across every category in the October 2026 Edition, EntityKeeper and MinuteBox were named in the same answer twenty-six times, of the 103 answers naming EntityKeeper and the 41 naming MinuteBox. In those answers MinuteBox took the first choice four times and EntityKeeper two.
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 | | |
EntityKeeper MinuteBox first choice named as an alternative argued againstblank: not namedEach cell is one answer, EntityKeeper on the left and MinuteBox on the right.The direct prompt
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
9 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
EntityKeeper23%#1 of 8MinuteBox8%#3 of 8EntityKeeper6%#4 of 11MinuteBox4%#7 of 11EntityKeeper0%#9 of 9MinuteBox0%#8 of 9What the models said about EntityKeeper
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of eight in this category shown.
“I'd skip EntityKeeper on a tight budget: its published annual plans start at $5,000” GPT-6 Luna · budget prompt · hard negative
“Avoid giants like EntityKeeper or Diligent unless you are prepared to pay $5,000+/year” Qwen 3.7 Flash · budget prompt · hard negative
“"Legacy/Standalone Entity Databases (e.g., Basic Spreadsheets or Early CRMs like Generic \"EntityKeeper\" for Scale-Up Beyond Small Portfolios)"” Muse Glimmer 30B · negative prompt · soft negative
“For the most budget-conscious option, EntityKeeper's free plan is a strong starting point.” Mistral Small · budget prompt · first choice
“🥇 Top Pick: EntityKeeper (for Entity Management)” DeepSeek V4 Flash · paraphrase prompt · first choice
“EntityKeeper is the tool I'd recommend first” MiniMax M2.5 · paraphrase prompt · first choice
What the models said about MinuteBox
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Four of five in this category shown.
“The main drawback is its interface, which feels slightly outdated compared to newer platforms.” Claude Haiku 4.5 · negative prompt · soft negative
“the best legal entity management software for a limited budget is MinuteBox due to its extremely low entry-level pricing” GLM 4.7 FlashX · budget prompt · first choice
“MinuteBox is an excellent choice for companies with limited budgets, starting at just $5 per entity.” Claude Haiku 4.5 · budget prompt · first choice
“Choose Athennian or MinuteBox if you are an in-house legal operations team or law firm” Gemini 3.5 Flash · 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.