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Whistleblowing and investigations · October 2026 Edition

Whispli vs Case IQ

Three of fourteen models named Whispli first on the direct prompt; one named Case IQ. Whispli was named by eight of the fourteen models and Case IQ by eight and Whispli carries 12 labels and Case IQ 11, so the shares are not directly comparable.

Whispli

accepted challenger

Named in one category this edition.

Case IQ

accepted challenger

Named in two categories this edition.

First-choice share8%4%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate0%0%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#4#8A position in a field of 12; printed, not drawn.
Labels1211A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Whispli reading right to left. Rank and label count are printed, not drawn.FaceUp was named alongside these two in nine of the fourteen direct answers. FaceUp vs Whispli · FaceUp vs Case IQ · Whistlelink vs Whispli

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 whistleblowing and investigations page.

By framing

How many of the fourteen models made each the first choice, per way of asking, and how many argued against it.
WhispliFirst choices, of fourteen modelsCase IQ
Direct31
Paraphrase11
Comparative00
Budget-constrained00
Scale-constrained00
Negative00
Bars are first choices, 0 to 14 each sideModels that argued againstA model can name both, so the two sides of a row do not sum to fourteen.

Across every category in the October 2026 Edition, Whispli and Case IQ were named in the same answer seventeen times, of the 57 answers naming Whispli and the 50 naming Case IQ. In those answers Case IQ took the first choice zero times and Whispli two.

Every model, every framing

The eighty-four answers behind the chart above, one cell each: where Whispli and Case IQ stood in it.
ModelDirectParaphraseComparativeBudget-constrainedScale-constrainedNegative
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
Whispli Case IQ first choice named as an alternative argued againstblank: not namedEach cell is one answer, Whispli on the left and Case IQ on the right.

The direct prompt

The plain question, one answer per model, grouped by where Whispli and Case IQ stood in it.

Whispli first, Case IQ not the choice

3 of 14 modelsCase IQ was named in the answer but not as the choice, or not at all.
GPT-5.4 miniWhispli alternatives: Ethico, SpeakUp, Whistleblower Software
Perplexity SonarWhispli alternatives: FaceUp, NAVEX One, Whistleblower Software
Qwen 3.7 FlashWhispli alternatives: AllVoices, Ethico

Case IQ first, Whispli not the choice

1 of 14 modelsWhispli was named in the answer but not as the choice, or not at all.
GPT-6 LunaCase IQ alternatives: Ethico, HR Acuity, NAVEX One

Neither was the first choice, one was named

3 of 14 modelsThe answer put something else first and named one of the two as an alternative.
Claude Haiku 4.5FaceUp alternatives: AllVoices, SpeakUp Report, VoxWel, Whispli
DeepSeek V4 FlashFaceUp alternatives: Case IQ, WeMoral, Whistleblower Software
Muse Glimmer 30BFaceUp alternatives: AllVoices, Case IQ, WhistleBlower Security

Neither was named

7 of 14 modelsThe answer made no first choice from these two in this category.
Gemini 3.5 FlashFaceUp alternatives: HR Acuity, Whistleblower Software, Whistlelink
Grok 4.1 FastWhistleblower Software alternatives: FaceUp, NAVEX One
Mistral SmallFaceUp alternatives: AllVoices, Safecall
Llama 4 MaverickOrdio alternatives: NAVEX One, NotMe, WhistleBlower Security
Kimi K2FaceUp alternatives: EQS Integrity Line, Ethicontrol
GLM 4.7 FlashXWhistleblower Software alternatives: EQS Integrity Line, NAVEX One, Whistlelink
MiniMax M2.5FaceUp, NAVEX One alternatives: OneTrust EthicalTrack

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

The same question asked on behalf of a different buyer. Each standing is computed within its segment and they are never added together. The figures above are the mid-market standing, which is the one the category orders by.
Small business
Whispli leads by two points.
Whispli3%#6 of 10
Case IQ2%#9 of 10
The full small business standing →
Mid-marketThe figures above
Whispli leads by four points.
Whispli8%#4 of 12
Case IQ4%#8 of 12
The full mid-market standing →
Enterprise
Level: the same share of first choices.
Whispli6%#5 of 11
Case IQ6%#4 of 11
The full enterprise standing →

What the models said about Whispli

Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Three of four in this category shown.

“if you want a single default recommendation, I'd lean Whispli for mid-market B2B” GPT-5.4 mini · direct prompt · first choice
“Whispli is the most commonly cited best-fit for mid-market teams” Muse Glimmer 30B · paraphrase prompt · first choice
“the strongest all-around choice is usually Whispli” Perplexity Sonar · direct prompt · first choice

What the models said about Case IQ

Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Three of four in this category shown.

“Best overall fit: Case IQ — ... I would choose Case IQ because the available results emphasize the core features a mid-sized company usually needs most” Perplexity Sonar · paraphrase prompt · first choice
“My default pick: Case IQ” GPT-6 Luna · direct prompt · first choice
“A useful candidate when investigation handling and reporting are as important as the reporting channel itself.” GPT-6 Luna · comparative prompt · alternative
Also compared

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.