Both Omi (formerly Friend) and Oopsie are in our Android index. Both crossed our engagement threshold. Here's how they compare on the numbers that are hard to fake.
Side-by-side comparison of Omi (formerly Friend) and Oopsie based on community engagement data.
An open source AI necklace
Debug Flutter & React Native apps with AI & Session Replays
Both Omi (formerly Friend) and Oopsie are in our Android index. Both crossed our engagement threshold. Here's how they compare on the numbers that are hard to fake.
| Category | Omi (formerly Friend) | Oopsie |
|---|---|---|
| Android | Yes | Yes |
| Artificial Intelligence | Yes | - |
| Developer Tools | - | Yes |
| GitHub | Yes | - |
| Hardware | Yes | - |
| Productivity | Yes | - |
| iOS | - | Yes |
🚀 Excited to introduce Friend Necklace on Product Hunt today! 🚀 To celebrate the launch, giving 5 devices to 5 random supporters! Results on Monday! ----- Meet Friend Necklace - your open-source personal AI that does more than just listen. It remembers your conversations, takes notes, and helps you ...
How can I become a supporter? I guess I would need to make a comment and upvote. Oh this device will force kids to talk if they think it's their friend, actually become more confident.
Cant wait to see this, and try it. It will be so handy when ideas pop into your head while driving. No more ideas forgotten
Hey everyone, 👋 I am Vishalini, Founder of Zipy and we’re super excited to go live with Oopsie, AI based mobile monitoring product by Zipy on Product Hunt today! Huge thanks to @kevin for hunting us, @rohanrecommends for guidance, PH community and PH team who make this platform amazing. 🤔 What is Oo...
Big congrats @vishalini_paliwal1 and @msnkarthik for this. Looking forward how this can also help with understanding where we are losing users on the product.
This is an incredible step forward for debugging! I'm curious—do you plan to expand beyond Flutter and React Native to include frameworks like Xamarin or Ionic? That could widen your reach even further.
Omi (formerly Friend) leads on raw interest score. Oopsie leads on engagement ratio. That split is worth paying attention to. Omi (formerly Friend) attracted more initial eyeballs, but Oopsie's audience engaged deeper. For most buyers, engagement ratio is the better signal.
These products share 1 categories: Android. Moderate overlap suggests they target related but distinct use cases.
Omi (formerly Friend) is also tagged in Artificial Intelligence, GitHub, Productivity, which Oopsie isn't. That suggests Omi (formerly Friend) positions itself more broadly or targets an adjacent audience.
Oopsie has unique category tags in Developer Tools, iOS. Different positioning can mean a different buyer profile, even within the same space.
Omi (formerly Friend) launched Jul 2024. Oopsie launched Dec 2024. Both launched the same year, meaning they faced similar market conditions and competition levels.
Omi (formerly Friend) has a 0.23 engagement ratio (average), based on 171 discussion threads across 748 interest points. Middle of the pack for Android. Enough discussion to suggest real usage, but not the kind of buzz that indicates a category-defining product.
Oopsie has a 0.34 engagement ratio (strong), based on 240 discussions across 714 interest points. Strong engagement suggests an audience that tested the product and came back to talk about it.
Within the Android category (1,913 total products), Omi (formerly Friend) ranks #6 and Oopsie ranks #7 by interest score. Omi (formerly Friend) sits in the top 10 for the category.
Omi (formerly Friend) is in the top 0% of Android by interest. Oopsie is in the top 0%.
Pick Omi (formerly Friend) if you want the product with the larger community behind it; you need something that also covers Artificial Intelligence.
Pick Oopsie if community size matters less to you than engagement depth; sustained discussion and active users are your priority; you need something that also covers Developer Tools.
Omi (formerly Friend): Discover Friend necklace - your open-source personal AI that listens, remembers conversations, takes notes, and prepares tasks for you. Stay organized with real-time notifications and comprehensive memory assistance. Explore the future of AI wearables!
Oopsie: Oopsie by Zipy is the only AI-powered mobile debugging tool you need, offering ▶️ session replays, 🤖 error monitoring, 💡AI-summaries, and 🔥 Firebase Crashlytics integration. Debug smarter and resolve Flutter and React Native issues faster with Zipy.
These products also compete in the Android category:
Presence — Connect with your community and culture in new places (Interest: 864, Engagement: 0.47)
Thunai — Human-like AI agents with real-time voice & screen assist (Interest: 630, Engagement: 0.15)
ULY — Modern daily journal (Interest: 510, Engagement: 0.18)
Pinch to Build by Vibecode App — The most powerful way to build professional mobile apps. (Interest: 446, Engagement: 0.12)
WinDiary — Mental health and personal achievement journal (Interest: 325, Engagement: 0.35)
Nook Calendar — Own your time, reclaim your attention (Interest: 307, Engagement: 0.47)
Generally, yes. Engagement ratio is hard to fake. A product can generate artificial interest, but sustained discussion threads require people who actually used the product and had something to say about it.
Automatically. We compare products that share at least one category and have similar interest scores. Products too far apart in traction don't make for useful comparisons.
No. Interest is launch-day attention. Engagement ratio is a better quality signal. The product with more discussions per interest point usually has stronger product-market fit.
How directly these products compete. Three or more shared categories means they're going after the same user. One shared category means they approach the space from different angles. Zero overlap and they probably shouldn't be compared.
Comparisons are generated automatically when two products have enough data overlap. If the pair you want isn't here, the products might be in different categories or too far apart in engagement.
Either the product didn't meet our engagement threshold, or it doesn't share enough category tags with the other product to generate a meaningful comparison. We'd rather show no comparison than a misleading one.