Launch Intel
Ta

Tagle – Discover Social Profiles Locally Based on Shared Interests

Hacker News

Tagle – Discover Social Profiles Locally Based on Shared Interests

Hey HN, I’m excited to introduce Tagle, an app that helps people discover others around them based on real interests rather than superficial social profiles. What it does: • Find people locally who share your passions using flexible interest tags. • Users can unlock social profiles (like Instagram, X) to connect directly. • It’s not about superficial browsing, but about building meaningful connections through niche interests and hobbies. I’ve built Tagle to give users a way to connect authentically by focusing on what matters to them—whether it’s discovering fellow hobbyists nearby or engaging with people who have similar passions. Why I built it: Most social platforms focus on global interactions, but I wanted to create a tool that helps people connect locally through shared, genuine interests. It bridges the gap between the online world and real-world interactions by highlighting what people actually care about. Looking for feedback: I’d love to hear any feedback from the community— thoughts on the concept, ideas for improvement, or even potential challenges I might face. The app is currently available on the App Store, and I’m eager to learn what works and what could be better. Thanks for your time!

Visit productView on Hacker NewsSep 15, 2024
Share card

Actual performance

2points
Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →
Product HuntOn track for Day 1 leaderboard · Strong signals: user, using · Missing: mac, agents, macos
74%74% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
70%70% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform, users · Missing: plus, intuitive, reviews
48%48% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: users, way · Missing: mobile apps, ios, personal
40%40% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: excited, ide, io · Missing: https docs, just released, exist
38%38% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
18%18% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: introduce · Missing: web3, chat, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

Similar products

In
Instantly discover all social profiles of celebrities in one click46%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Instantly discover all social profiles of celebrities in one click

Hacker News1
In
Instantly find social profiles of any celebrity47%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Instantly find social profiles of any celebrity

Hacker News1
Di
Discover all social profiles of people in a single click47%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Discover all social profiles of people in a single click

Hacker News3
diip
diip14%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Increase your social profiles with a tip catalogues

Indie Hackerscommitment-side-project
Re
Regular expressions for social media profiles46%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Regular expressions for social media profiles

Hacker News5
Pr
Procman, a TUI for run Procfile based app locally40%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Procman, a TUI for run Procfile based app locally

Hacker News2
The Shared Dawn
The Shared Dawn34%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Civic ritual for a fictional civilisation

Indie Hackerscommitment-side-project
ProfileUI
ProfileUI38%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Simplistic online profiles

Indie Hackerscommitment-side-project
Gr
Groovli – Jukebox powered by music shared in your social circles56%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Groovli – Jukebox powered by music shared in your social circles

Hacker News4
Gr
Groovli – Jukebox powered by music shared in your social circles56%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Groovli – Jukebox powered by music shared in your social circles

Hacker News6
Browse all productsAnalyze your launch