Thunderdome B2B SaaS AI Visibility Index

← No-Code & Internal Tool Builders ranking

Brand report · September 2026

Superblocks Superblocks: AI Visibility Report

superblocks.com ↗

When buyers ask ChatGPT, Claude, and Gemini about no-code & internal tool builders, Superblocks ranks #8 of 15, a Visibility Score of 16 in No-Code & Internal Tool Builders .

These rankings are measured from what the three models know from training, not a live web search. The live-web grounded surface is rolling out across the index. Methodology.

How AI sees Superblocks

One field, one race, stuck in the middle of it.

Where it wins. Superblocks earns a 24% mention rate in No-Code and Internal Tool Builders, which is a respectable floor for a crowded 15-tool category. The startup and small team prompt theme is where AI models reach for it most consistently.

Where it loses. A rank of 8 and zero first-pick selections means buyers asking for a top recommendation almost never hear Superblocks named first. The models also skip it entirely when the conversation turns to use-case fit or budget trade-offs, which are exactly the angles serious buyers use to make a final call.

AI-generated analysis of the September 2026 measurements.

Gap

How Superblocks positions itself vs how AI ranks it

Superblocks's homepage sells it as AI App Builders. Ask the models that question and they name Replit, Lovable and Bolt, not Superblocks.

The pitch

"Build and Govern AI Generated Enterprise Apps"

Positions in AI App Builders
Targets Enterprise
What AI actually says
In AI App Builders Not named. Replit, Lovable and Bolt lead

Why, and what closes it. Models recommend what the web says about a brand, not what its homepage asserts. That is a content and coverage gap, not a product one. Earned mentions and clearer positioning can move it.

Homepage self-messaging · September 2026 ranking · the biggest gaps across the index →

How well the models know Superblocks

A different question from visibility: not “do the models recommend Superblocks?” but “asked about it directly, how specifically and confidently do they describe it?” High knowledge with low cross-model agreement is a warning sign — one model may be confidently filling gaps.

78 / 100
knowledge depth
models ranged 62–92
92 / 100
cross-model agreement
do the models describe the same product?
ChatGPT
80
Claude
62
Gemini
92

from 6 direct-question answers across ChatGPT, Claude & Gemini

No-Code & Internal Tool Builders · #8 of 15

16 / 100 flat vs last month
24%
mention rate (72 answers)
4
avg. position
0%
first pick
3%
share of voice
18.9Jul 2026Jul 2026: 18.916.5Aug 2026Aug 2026: 16.515.6Sep 2026Sep 2026: 15.6
ChatGPT
11
Claude
3
Gemini
33

One of the index's bigger model splits: see where the models disagree →

How the models portray Superblocks

Being named is not the same as being recommended. Each mention is graded endorsed (a strong pick), listed (a neutral option), or caveated (named with a reservation).

29% 35% 35%
endorsed · 95% band 13–53% listed caveated graded across 17 mentions in No-Code & Internal Tool Builders answers
Prompt themes Superblocks would want to own

Share of each theme's answers that mention Superblocks. Hover a row for the exact prompt. Compare shapes on the head-to-head page.

Gaps Use-case fit · Budget & alternatives

Most co-mentioned competitors

Share of Superblocks's mentions where the AI models name this brand in the same answer. That is the real competitive set in the AI channel.

Retool
100%
Appsmith
88%
Budibase
65%
ToolJet
35%
Microsoft Power Apps
29%
Glide
18%

Scores are measured from real AI answers, refreshed monthly. Methodology.

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