iDeals vs SecureDocs
Eight of fourteen models named iDeals first on the direct prompt; zero named SecureDocs. iDeals was named by fourteen of the fourteen models and SecureDocs by thirteen and iDeals carries 46 labels and SecureDocs 28, so the shares are not directly comparable.
Named in two categories 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 virtual data rooms page.
By framing
iDealsFirst choices, of fourteen modelsSecureDocs
Across every category in the October 2026 Edition, iDeals and SecureDocs were named in the same answer forty-six times, of the 108 answers naming iDeals and the 100 naming SecureDocs. In those answers SecureDocs took the first choice ten times and iDeals eight.
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 | | | | |
iDeals SecureDocs first choice named as an alternative argued againstblank: not namedEach cell is one answer, iDeals on the left and SecureDocs on the right.The direct prompt
iDeals first, SecureDocs an alternative
8 of 14 modelsSecureDocs was named in the answer but not as the choice, or not at all.Neither was the first choice, one was named
4 of 14 modelsThe answer put something else first and named one of the two as an alternative.Neither was named
2 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
SecureDocs15%#2 of 17iDeals7%#4 of 17iDeals25%#1 of 15SecureDocs8%#5 of 15SecureDocs11%#3 of 10iDeals5%#5 of 10What the models said about iDeals
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Five of six in this category shown.
“iDeals frequently appears in negative discussions regarding its business practices and administrative friction.” Qwen 3.7 Flash · negative prompt · soft negative
“Some concerns (though generally well-reviewed) - Pricing concerns” DeepSeek V4 Flash · negative prompt · soft negative
“often positioned as a strong *overall* choice, with broad use across M&A, fundraising, and life sciences, and a high review score in one comparison” Perplexity Sonar · comparative prompt · first choice
“Often positioned as a strong all-around choice for teams that want a user-friendly VDR with broad functionality and more transparent pricing” GPT-5.4 mini · comparative prompt · first choice
“The mid-market leaders (iDeals, FirmEx, FirmRoom, SecureDocs, Papermark) offer strong security and features at flat-rate pricing” DeepSeek V4 Flash · scale prompt · first choice
What the models said about SecureDocs
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Three of four in this category shown.
“The mid-market leaders (iDeals, FirmEx, FirmRoom, SecureDocs, Papermark) offer strong security and features at flat-rate pricing” DeepSeek V4 Flash · scale prompt · first choice
“SecureDocs at $250/month (flat-rate plan, good for small businesses and ongoing diligence)” Mistral Small · budget prompt · first choice
“If you prefer predictable, flat-rate pricing, SecureDocs or Papermark are excellent choices.” Claude Haiku 4.5 · budget 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.