
Simple Client Onboarding and Verification

Hotjar
Attention Insight
Microsoft Clarity
HeatScope.space
heatmap.js
See what users see before they do. Upload any interface or enter a URL to generate an AI-powered visual attention heatmap in seconds.

Website, pricing, platforms and company facts side by side.
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| Website | stackgo.io | heatpoints.com |
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| Company | — | Startup from France · 1 - 9 employees · 2026 |
| Listed in |
In their own words, as submitted to SaaSHub.


No description of StackGo yet.
AI attention heatmap tool built on peer-reviewed eye-tracking research. Paste a URL or upload a design and get a predictive heatmap, an attention score /100 and an AI-written audit in 30 seconds — before your page has any traffic. No tracking script, no cookies, no consent banner. Free plan with...
What each product offers, as listed by its team.


Possible disadvantages
An editorial look at what each product does well and who it suits.


Overall verdict
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Overall verdict
Why this product is good
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How often each product is chosen within a category, 0–100% relative to the other.


As answered by people managing StackGo and Heatpoints.
Heatpoints's answer:
Heatpoints predicts where visitors will look — and which words they will actually read — before a page is live, with no tracking script, no cookie and no consent banner. It runs a peer-reviewed eye-tracking AI on any URL, mockup or screenshot and returns a heatmap, an attention score out of 100 and an AI-written audit in about 30 seconds. Its Words Map (word-by-word reading attention) and its cookieless prediction-vs-reality check (Pulse) are things no other commercial tool offers.
Heatpoints's answer:
Session-recording and real-user heatmap tools (Hotjar, Microsoft Clarity, Plerdy) need a live site, traffic and a consent banner — they can only tell you what already happened. Heatpoints answers the question before you have any traffic: what will a first-time eye do on this page. Versus other predictive tools, it is self-serve from a free plan, never watermarks exports, ships white-label reports from a lower tier, and adds an AI audit and word-level copy analysis on top of the heatmap.
Heatpoints's answer:
CRO specialists, UX and web designers, marketers and founders who want to validate a page's visual hierarchy and messaging before launch. It is also built for people shipping pages fast with AI builders (Lovable, v0, Bolt, Cursor) who need a quick quality check, and for agencies who deliver white-label attention audits to clients.
Heatpoints's answer:
The attention engine is UniSAL, a peer-reviewed saliency model (ECCV 2020) running in PyTorch, trained on real human eye-tracking datasets. The backend is Python/FastAPI, page capture runs on Playwright/Chromium, the frontend is Next.js, and data is stored in MongoDB. There is also a public REST API and an MCP server for AI agent workflows.
Heatpoints's answer:
AI now generates landing pages faster than anyone can judge them — but nothing checks whether a human will actually look at the right place before the page ships. Heatpoints was built to be that visual QA step: paste a URL or a mockup and see where attention lands, before you pay for traffic. It's an independent product by Dropnir, built to make attention testing instant, deterministic and consent-free.
Share your experience with using StackGo and Heatpoints. For example, how are they different and which one is better?