MedullaAI combines AI and cognitive science to help brands design marketing that truly captures human attention and stays in memory. We help brands and agencies understand why their marketing won’t perform, improve it, and ship a better version with scientific confidence.
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Maker
📌
Hey PH! 👋
I'm thrilled to finally share MedullaAI with you today.
Brands spend $800B+ annually on advertising, and creative quality determines 49% of whether that spend actually works.
Yet, creative selection is the last remaining competitive lever driven entirely by gut feel. Teams sit in a conference room, pick a creative, and only find out if it worked after the budget is completely gone.
The Insight: We realized that ads don’t usually fail because the visuals are objectively "bad." They fail because of invisible cognitive failure. People don't make decisions through logic alone - the brain filters information through attention, encodes it into memory, and only then influences behaviour. If an ad loses attention in the first two seconds, the rest of the funnel collapses.
The Solution: We built MedullaAI to close this pre-launch intelligence gap. It is a neural analytics platform that validates creative performance before you launch.
Instead of waiting 8 weeks and spending $80K on traditional neuromarketing labs, our AI-powered eye-tracking and cognitive science models tell you:
👀 Exactly where human attention goes
🧠 How viewers respond emotionally
⚡ Which creative will actually drive action
It takes minutes, not months, and is MIT-validated with 90%+ accuracy against hardware-based lab studies.
Whether you are a CMO at a scaling D2C brand or an agency leader defending a strategy, we want to help you ship with confidence before a single dollar of media spend goes live.
I’d love to know what you think! Drop your questions below about our cognitive models, rapid prototyping, or how you currently validate your ad creatives. I'll be hanging out in the comments all day! 🚀
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the "understand why it won't perform" framing caught me. most tools help you produce more stuff faster. this feels like it's trying to slow brands down first and diagnose before shipping. harder sell, probably the more useful one.
curious how the cognitive science piece actually works in practice. is it pattern-matching against existing attention research, or something closer to simulating how a brain processes a new visual? not sure if that distinction matters to most users but i'd want to know what's actually under the hood before trusting a "scientific confidence" score.
congrats on shipping this.
Report
Maker
@fraser_svg Thank you Fraser! You named it better than we did - "diagnose before shipping" is exactly the intent.
On the technical question: it's both, working together. The cognitive simulation layer is grounded in established neuroscience - how the brain processes visual hierarchy, where attention is drawn first, how emotional response builds. That gives us a theoretical baseline for any new creative.
But theory alone isn't enough to trust. So we cross-reference against patterns from high-performing ad creatives - what actually drove attention and action in the real world. Where both signals agree, confidence goes up. Where they diverge, we flag it rather than paper over it.
The honest answer is that the brain simulation is more directional than it is precise. The creative analysis is what keeps us grounded. Together, that's what makes the confidence score mean something, and what the MIT validation was actually testing.
Happy to go deeper if you're curious.
Report
Congrats on your launch! Building creative for a mobile app launch with zero budget for guesswork, and knowing where attention actually lands before we spend anything is huge. Does it work on mobile ad formats specifically, or is it mostly built around desktop/static creatives.
Report
Maker
@aya_vlasoff Thank you Aya! Mobile format is fully in scope - Stories, Reels, the works.
Mobile actually changes the attention math a lot. On desktop you have a few seconds. On mobile you have one, maybe two, before the thumb moves. Our models are calibrated for that window specifically, so you're not getting desktop predictions dressed up for mobile.
For a zero-budget launch, running validation before spend makes a lot more sense than A/B testing after. If you want, share a format you're working with and I'll be happy to show you what the attention map looks like on something real.
the "understand why it won't perform" framing caught me. most tools help you produce more stuff faster. this feels like it's trying to slow brands down first and diagnose before shipping. harder sell, probably the more useful one.
curious how the cognitive science piece actually works in practice. is it pattern-matching against existing attention research, or something closer to simulating how a brain processes a new visual? not sure if that distinction matters to most users but i'd want to know what's actually under the hood before trusting a "scientific confidence" score.
congrats on shipping this.
@fraser_svg
Thank you Fraser!
You named it better than we did - "diagnose before shipping" is exactly the intent.
On the technical question: it's both, working together. The cognitive simulation layer is grounded in established neuroscience - how the brain processes visual hierarchy, where attention is drawn first, how emotional response builds. That gives us a theoretical baseline for any new creative.
But theory alone isn't enough to trust. So we cross-reference against patterns from high-performing ad creatives - what actually drove attention and action in the real world. Where both signals agree, confidence goes up. Where they diverge, we flag it rather than paper over it.
The honest answer is that the brain simulation is more directional than it is precise. The creative analysis is what keeps us grounded. Together, that's what makes the confidence score mean something, and what the MIT validation was actually testing.
Happy to go deeper if you're curious.
Congrats on your launch! Building creative for a mobile app launch with zero budget for guesswork, and knowing where attention actually lands before we spend anything is huge. Does it work on mobile ad formats specifically, or is it mostly built around desktop/static creatives.
@aya_vlasoff
Thank you Aya!
Mobile format is fully in scope - Stories, Reels, the works.
Mobile actually changes the attention math a lot. On desktop you have a few seconds. On mobile you have one, maybe two, before the thumb moves. Our models are calibrated for that window specifically, so you're not getting desktop predictions dressed up for mobile.
For a zero-budget launch, running validation before spend makes a lot more sense than A/B testing after. If you want, share a format you're working with and I'll be happy to show you what the attention map looks like on something real.