Adaptrix

I’ve been building Adaptrix, an AI that helps brands and creators adapt ad videos for different markets.
When I started, I thought getting early feedback would be easy: post on IH, Reddit, and a few Slack groups, and people would test it.
But real usage is a totally different story.

Here’s what I’ve learned so far:

• People love giving feedback… but rarely actually use a free alpha unless it directly solves something they feel right now.

• The easiest testers to get are often other builders, but their feedback focuses on features not outcomes.

• The hardest thing is explaining value fast enough that someone wants to upload a video and try it.

So lately I’ve been shifting focus from “collecting testers” to “finding real use cases” — basically treating feedback as validation only if someone acts on it.

Curious how others handle this:
👉 How did you turn casual interest or comments into actual product usage?
👉 What made your first few users stick?

I’ve been working on Adaptrix, an AI that adapts ad content for different markets and I wanted to share a small but eye-opening lesson from the alpha tests.

When I started, I thought localization was mainly a translation problem. Just make the text correct in another language and you’re good, right?
Turns out… not even close.

Here’s what I’ve learned the hard way:

• You can translate every word perfectly, but still completely miss the emotion that made the ad work.

• Humor, urgency, or slang often collapse when moved across cultures.

• Even sentence rhythm matters what feels “energetic” in English might sound “aggressive” in German or “awkwardly polite” in Japanese.

One of my early testers ran a simple A/B experiment: same ad, two translations:
one literal, one adapted to local tone.
The second version (the one that felt native) got 28% more clicks.

That small test hit me hard. Because it’s not just a marketing insight it’s a reminder of how much nuance drives trust in global communication.

Right now I’m working on improving how Adaptrix handles nuance and slang even further. It already adapts tone and phrasing pretty well, but I’ve realized how subtle those cultural cues can be, especially when humor or urgency are involved. Still messy, but fun to explore.

💬 Curious:
If you’ve worked with multiple markets or languages:
How do you handle this? Do you localize, or just run everything in English and hope it lands?

Would love to hear how others think about cross-cultural content.

Hey IH 👋

I’ve been building Adaptrix, a small AI tool that helps brands and creators make their ads sound natural in different markets — not just translated, but actually native.

I realized most AI translation tools get the words right but miss the tone — the slang, humor, and rhythm that make an ad click. Something that sounds fun in English can come off as awkward or too formal in French, Spanish, or Japanese.

Right now we’re in free alpha and testing how well our tone-localization model works across languages.
We’ll adapt one short ad clip (15–60 seconds) for another market and share it back so you can hear how it sounds.

We’re especially looking for:
🌍 Multilingual founders or marketers who can compare how tone or emotion carries across languages.
💬 People who’ve run international ads or localized products and know how tricky it can be.

Our goal is simple: Learn how cultural nuance and tone affect ad performance before moving to paid plans.

If you’re curious, you can check it out or DM me:
https://adaptrix.io

Would love honest feedback, especially if you’ve ever thought, “This translation sounds right, but it doesn’t feel right.”

Thanks for helping shape the alpha 🙌

#ai #marketing #ecommerce #localization #feedback #buildinpublic