Neurons AI

Neurons AI is an online platform that predicts where people will look on creative assets by combining large-scale neuroscience data with machine learning.

How to use Neurons AI

1. Open an account through the official site and pick the credit package that fits your workload.
2. Upload a static image, video frame, prototype link or live URL straight into the dashboard.
3. Select the output you need—heatmap, clarity score or engagement forecast—then press “Run”.
4. Review the instant visual overlay that highlights predicted attention hotspots and potential blind areas.
5. Iterate on the creative inside your design tool or export the findings for the wider team.

What we discovered while testing Neurons AI

Advantages

• Instant feedback saves budget: eye-tracking style insights arrive in seconds, so we skipped costly lab sessions.
• Heatmaps are easy to grasp: designers, marketers and stakeholders all understood the coloured overlay at first glance.
• Seamless design-tool plug-ins: the Figma extension let us check concepts mid-flow without leaving the canvas.
• Clear scoring system: attention, clarity and cognitive load metrics come with simple explanations, helping the team set measurable targets.
• Responsive support crew: live chat solved our API question within ten minutes and followed up by email later that day.

Drawbacks

• Pricing piles up quickly: high-resolution video predictions eat through monthly credits faster than expected.
• Limited emotional insight: the platform focuses on visual attention, so sentiment analysis still needs another tool.
• File size ceiling: anything above 20 MB needs manual compression before upload, slowing momentum during large campaign reviews.
• Occasional render delay: very detailed banner sets took up to two minutes, which interrupts rapid A/B testing runs.
• Learning curve for API: developers needed a full afternoon with the documentation to automate batch jobs smoothly.

Wrapping up our experience

Neurons AI gave the team an accessible way to spot attention pitfalls early and refine artwork before media spend went live. The credit-based model and focus on gaze prediction mean it is most valuable when used alongside broader research tools, yet for fast visual feedback it earned a permanent place in our pre-launch checklist.