Interesting approach — treating ads as something you can reverse-engineer instead of just “inspire from” is the real value here. Most creative tools generate content blindly; this actually tries to deconstruct what makes a winning ad work: structure, pacing, hooks, messaging patterns, etc.
If you can consistently break an ad down into reusable components (hook, setup, proof, CTA, visual pattern) and let people remix those templates, that’s powerful. It basically turns high-performing ads into a library of “design patterns” for creatives.
Curious how deep the reverse engineering goes:
• Are you analyzing just text, or also visual rhythm, shot sequence, and narrative beats?
• Can the system infer why an ad might be converting well, or just what it contains?
• How do you avoid overfitting on trends from one platform/vertical?
If you can consistently break an ad down into reusable components (hook, setup, proof, CTA, visual pattern) and let people remix those templates, that’s powerful. It basically turns high-performing ads into a library of “design patterns” for creatives.
Curious how deep the reverse engineering goes: • Are you analyzing just text, or also visual rhythm, shot sequence, and narrative beats? • Can the system infer why an ad might be converting well, or just what it contains? • How do you avoid overfitting on trends from one platform/vertical?