Index › GTM › Marketing › Brand protection › IP Moat vs Bolster AI
Brand protection platforms · November 2026 Edition

IP Moat vs Bolster AI

One of fourteen models named IP Moat first on the direct prompt; four named Bolster AI. IP Moat was named by twelve of the fourteen models and Bolster AI by nine and IP Moat carries 14 labels and Bolster AI 12, so the shares are not directly comparable.

IP Moat

accepted challenger

Named in one category this edition.

Bolster AI

accepted challenger

Named in one category this edition.

First-choice share23%10%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#1#4A position in a field of 11; printed, not drawn.
Labels1412A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, IP Moat reading right to left. Rank and label count are printed, not drawn.BrandShield was named alongside these two in eleven of the fourteen direct answers. IP Moat vs BrandShield · IP Moat vs Red Points · IP Moat vs Bolster

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 brand protection platforms page.

By framing

How many of the fourteen models made each the first choice, per way of asking, and how many argued against it.
IP MoatFirst choices, of fourteen modelsBolster AI
Direct14
Paraphrase01
Comparative00
Budget-constrained100
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.

Every model, every framing

The eighty-four answers behind the chart above, one cell each: where IP Moat and Bolster AI stood in it.
ModelDirectParaphraseComparativeBudget-constrainedScale-constrainedNegative
Claude Haiku 4.5
GPT-5.4 mini
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
IP Moat Bolster AI first choice named as an alternative argued againstblank: not namedEach cell is one answer, IP Moat on the left and Bolster AI on the right.

The direct prompt

The plain question, one answer per model, grouped by where IP Moat and Bolster AI stood in it.

IP Moat first, Bolster AI not the choice

1 of 14 modelsBolster AI was named in the answer but not as the choice, or not at all.
Qwen 3.7 FlashIP Moat, Red Points alternatives: Bolster

Bolster AI first, IP Moat not the choice

4 of 14 modelsIP Moat was named in the answer but not as the choice, or not at all.
Mistral SmallBolster AI alternatives: BrandShield, Cyble, Red Points, ZeroFox Brand Protection
DeepSeek V4 FlashBolster AI alternatives: BrandShield, Red Points
GLM 4.7 FlashXBolster AI, BrandShield alternatives: ZeroFox
MiniMax M2.5Bolster AI alternatives: BrandShield

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.
Grok 4.20Red Points alternatives: Bolster AI, BrandShield, Cyble, MarqVision
Kimi K2BrandShield, Red Points alternatives: Bolster AI, ZeroFox
Muse Glimmer 30BBrandShield alternatives: Bolster AI, Red Points

Neither was named

6 of 14 modelsThe answer made no first choice from these two in this category.
Claude Haiku 4.5Bolster alternatives: MarqVision, Podqi, Red Points
GPT-5.4 miniRed Points alternatives: BrandShield, CTM360, Fortra Brand Protection
Gemini 3.5 FlashBrandShield alternatives: Bolster, Corsearch, Red Points, ZeroFox
Perplexity SonarBolster alternatives: BrandShield, Corsearch, MarqVision, Red Points
Llama 4 MaverickBrandShield alternatives: Bolster, Netcraft Domain Protection, ZeroFox Brand Protection
GPT-6 LunaBolster alternatives: Doppel, Fortra Brand Protection, Netcraft

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
IP Moat leads by thirty points.
IP Moat32%#1 of 11
Bolster AI2%#– of 11
The full small business standing →
Mid-marketThe figures above
IP Moat leads by twelve points.
IP Moat23%#1 of 11
Bolster AI10%#4 of 11
The full mid-market standing →
Enterprise
IP Moat is not named for this buyer.
Bolster AI2%#6 of 10
IP Moat—not named
The full enterprise standing →

What the models said about IP Moat

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

“IP Moat looks like the strongest value pick I found because its pricing starts at $105/month” GPT-5.4 mini · budget prompt · first choice
“IP Moat stands out as the best brand protection platform for companies with a limited budget.” Grok 4.20 · budget prompt · first choice
“IP Moat is the best overall choice because it is built specifically for SME e-commerce brands” GLM 4.7 FlashX · budget prompt · first choice

What the models said about Bolster AI

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

“For most mid-market B2B companies, Bolster AI stands out for its comprehensive, AI-driven approach, strong ROI, and integration capabilities.” Mistral Small · direct prompt · first choice
“Start with BrandShield or Bolster AI as they offer the best balance of comprehensive coverage, mid-market pricing, and support levels.” GLM 4.7 FlashX · direct prompt · first choice
“1. Bolster.ai — *Best for Real-Time Automated Takedowns of Fake Websites & Portals*” Gemini 3.5 Flash · paraphrase prompt · first choice
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.