r/launchigniter

Managing investments across multiple apps is messy.

Arthavi helps you track your mutual funds and stocks together in one place, without spreadsheets or cluttered dashboards.

### 🚀 What it does

- Unified portfolio view (MF + stocks)

- Clean and minimal interface

- Simple performance tracking (no confusing metrics)

- AI-powered insights (early feature)

### 💡 Why it’s different

Most tools either:

- Focus only on stocks

- Or only on mutual funds

- Or overwhelm users with too many features

Arthavi is built for clarity and simplicity first.

### 👤 Who it’s for

- Long-term investors

- People tired of juggling multiple apps

- Anyone who wants a simple portfolio overview

### 🔗 Try it: https://arthavi.com

Would love feedback from the community 🙌

I have an android app named all in one AI in which users get multiple AI tools at one place, which has crossed 5000 downloads in just 10 months with 100s of DAUs. If you have an ai webapp and are not getting initial users then I can help you getting AI focussed users by putting your app in my all in one AI app and giving you a platform in front of daily multiple AI users. Here is my app -

https://play.google.com/store/apps/details?id=com.shlok.allinoneai

If you are interested in putting your app in All in one AI, you can DM me.

We spent years heads-down building HasData, and today's the day we go live on Product Hunt. Before we find out how it goes, wanted to share where we actually landed.

40+ APIs, 20+ no-code scrapers, an MCP server, an AI agent, a CLI, and agent skills. That's the product surface.

Under the hood: Node handles backend logic and parsing (libxml). All outbound traffic runs through a Go-based proxy service we built ourselves. TLS fingerprinting, multiplexing across multiple proxy providers plus our own dedicated pools, connection management. This keeps median response time at ~1.5s.

Everything runs on a self-managed, self-hosted RKE2 cluster. We run synthetic tests several times per day, each API gets hit with at least 10 parameter variations. For Google SERP, a healthy response for `q=coffee` should have 7+ organic results, a knowledge graph, a local pack, related questions, pagination and we validate each block individually. If something breaks, Slack gets it before any customer does.

Today we find out if all that actually matters to people outside our team. Interesting what your launch days looked like.

Here is our PH page, if you want to support us and all the work we did: https://www.producthunt.com/posts/hasdata

Hi ! i’m an indie dev and I wanted to share the journey of building my app, Keyri — a strict local-first digital vault for Android.

The Problem: Privacy vs Convenience

I’ve always been pretty paranoid about privacy. For years, I refused to use cloud-based password managers (and seeing breaches at major companies didn’t exactly help).

So my solution was… honestly terrible.

I kept all my passwords inside a password-protected zipped Word document stored only on my PC.

And because I was also terrified of losing everything, I kept a backup copy on a USB drive too.

This made the whole process even more painful:
every password update had to be manually synchronized between the PC copy and the USB backup.

Every time I needed to log into something on my phone or update a password, I had to:

- boot up my PC

- unzip the file

- enter the master password

- search for the entry

- update it manually

- remember to update the USB backup too.

At some point I realized I desperately needed a mobile solution, but I still didn’t want my sensitive data sitting on someone else’s servers.

The Journey: From Python Script to Flutter App

I’ve always loved coding, but never really had the time to go deep into app development. So I used this problem as an excuse to finally learn.

The first version of Keyri was actually just a local Python script running on my PC. It worked, but it obviously didn’t solve the mobile problem.

That’s when I decided to learn Flutter.

I spent months rebuilding the logic into a proper Android app during evenings and weekends. As I kept adding features for myself, I realized there were probably other privacy-focused people looking for a completely local alternative too.

So eventually I polished it up and published it on the Play Store.

Technical Challenges & Lessons Learned

here are a few interesting problems I had to solve without relying on a backend:

Handling images locally
I wanted users to store ID cards, receipts, and sensitive documents. Images are compressed on-device, encrypted locally using ChaCha20, and stored entirely inside the app sandbox.

Password breach checks without exposing passwords
I integrated the HaveIBeenPwned API using k-anonymity. Passwords are hashed locally and only the first 5 hash characters are sent. The real password never leaves the device.

Barcode & QR scanning
I used Google ML Kit for barcode scanning while ensuring image processing stays entirely on-device.

Data migration without cloud sync
Since there’s no traditional cloud account system, I built encrypted JSON backup/import support and CSV import tools to migrate from browsers like Chrome.

Backup experimentation
I’m currently testing optional encrypted backup integrations with Google Drive while trying to keep the app’s local-first philosophy intact.

What the app does today

Keyri (formerly SilentSaver) is now a full local-first digital vault for:

- passwords

- payment cards

- secure notes

- encrypted images/documents

It also includes:

- biometric unlock

- Android Autofill integration

- local breach checks

- encrypted backups

- zero ads

- zero tracking

- zero mandatory accounts

Play Store Link:
https://play.google.com/store/apps/details?id=com.nick.applab.silentsaver

I’d genuinely love to hear your feedback, especially from people who care about privacy, security, or local-first software.

Thanks for reading!

I have a problem with **social media**. Uninstalling never worked, I'd always come back. So I built Retakr: an app + URL blocker that **locks social media** during work hours and sets daily time limits. It also has a strict mode that makes it **impossible to bypass**, that part really made the difference for me.

What bothered me about existing solutions: most are subscription-based (stressful), and the free ones are too easy to bypass. Retakr is a one-time purchase, works offline, **no account, no data collection.**

It's working for me. Hope it helps someone else too.

Would love honest feedback, features, UX, anything.

**Play Store**: https://play.google.com/store/apps/details?id=com.jozaforge.retakr

When I posted the beta of Cloakly, half the comments loved the idea and the other half were convinced I’d built the ultimate tool for cheating.

The drama actually helped. After 200+ beta users stress-tested it, it turns out people just want to hide their messy Slack DMs, banking apps and other sensitive apps during screen shares on Teams or Zoom calls. Because no one likes "presentation anxiety."

What’s new for the production build:

• Pin on Top: Keep your hidden notes/windows always visible to you while you present.
• Window Transparency: You can now see "through" your private windows to the shared content behind them.
• Taskbar Stealth: Hide the icons of your private apps from the taskbar so the audience sees a completely clean desktop.
• And lastly new Fresh look to the website and application

I’m moving out of beta today. If you want to stop the panic of accidentally flashing your private data to coworkers, give it a look.

Live at: https://www.getcloakly.com/

I got tired of sounding like a robot.

Every time I used ChatGPT for an email, I’d spend the next 10 minutes editing it back into my own voice. Which kind of defeated the point.

So I built StyloMac a native Mac app that learns how you write and helps you sound like you, not like an LLM.

How it works:

1. Paste in a few emails or messages you’ve written or just rewrite exisiting

2. Hit ⌃⌥H from anywhere on your Mac

3. Get a version that sounds like you wrote it

It gets better as you use it. Every edit you make teaches it more about your voice.

Native Swift app. Not Electron. Sits in your menu bar. Uses ~30MB RAM idle.

peerhop.in
Download from Microsoft Store

Honestly I got tired of sending files through WhatsApp or using web based apps like Snapdrop.

Big files on WhatsApp were especially annoying because everything goes through their servers first, so larger transfers felt slower sometimes.

Other issues I had:
- browser based apps using too much RAM
- some apps needing complicated setup before devices connect
- inconsistent transfer speeds

LocalSend was good but setup/discovery sometimes felt a bit confusing for non technical users

So with PeerHop I tried keeping things really simple.
Just:
- open PeerHop on Windows
- scan QR from another device
- transfer directly over same network

That’s it.

Second device doesnt even need PeerHop installed.
No login/account needed either.

Reached around 65 MB/s during local testing which was honestly pretty satisfying

Share feedback or feature ideas

If you are launching today, share your link below. Let’s support fellow builders by checking out each other’s launches and leaving feedback.

https://www.producthunt.com/products/code-2041

All the best!!

The week is moving fast.

• Pitch your startup in one line.
• Drop a link if you’re live.

✨ Boost your visibility and get some fresh backlinks today.

We’re building PrettyFluent, a fast language learning app for expats, nomads, and travelers who want to speak naturally in real-life situations.

Building an AI agent is the easy part now. Anyone can do it in an afternoon. But the moment you want it running permanently in the background, actually connected to your stack, doing real work while you sleep, that's where everything falls apart. You end up spending more time on the microservice hosting the agent than on the agent itself. The logic takes a day. The plumbing takes a week and then breaks on a Tuesday for no reason.

I kept hitting that same wall. Eventually I stopped complaining about it and started building https://fleeks.ai/.

You build your agent locally, test it, make sure it behaves the way you want. Then you run fleeks promote. It goes live on Fleeks infrastructure and runs 24/7. No server to spin up, no containers to manage, no babysitting.

The other thing that makes this different is native MCP support, which means your agents connect to AWS, Kubernetes, GitHub, Postgres, PagerDuty without you writing a single integration. The agent figures out the API calls itself based on what you tell it to do.

We use it internally for autonomous incident response. A deployment fails, the agent catches it, traces the root cause, patches the config, and opens a PR before anyone gets paged. That loop runs without us.

Fleeks is fully open-source. You can audit everything it does locally before you promote anything to the cloud, and you can run the whole engine inside your own VPC if you need full control.

Would love feedback from anyone who's tried to solve this hosting problem themselves. What did your setup look like before?

I noticed a lot of people use VPNs but don’t really know how much speed they’re losing after connecting.

So I built a simple VPN speed test tool that helps check connection speed, performance impact, and whether your VPN is affecting browsing or streaming.

It’s quick, simple, and made for everyday users—not just technical people.

👉 beingoptimist.com/tools/vpn-speed-test/

Would love feedback—especially from people who use VPNs daily.

The number of ads I see on the internet is really annoying, and the problem is that they succeed in distracting me from my work.

So, I made FocusRead Reader Mode to help myself and others like me read content better online. It is a one-stop reading mode extension that works on most websites and provides all the personalisation options you need.

If there are features that you want to see on FocusRead Reader Mode next, please let me know, I intend to build them out and keep updating this extension to be as efficient as possible.

I hope you give it a try and let me know what you think!

Wanted to share what finally worked for me after a couple of false starts.

I started out trying to self-host Hermes Agent on a Jetson Orin Nano. Cute little box, but the practical reality is it tops out around 7B-class models locally. For an agent that is supposed to learn from you, build skills, search past sessions, and call tools across messaging apps, 7B was just not enough. The reasoning fell apart on anything multi-step and the skill-creation loop produced more noise than signal.

So I moved Hermes off the Jetson and onto a small Hetzner VPS instead. Inference goes out to a hosted provider (OpenRouter in my case, so one key gets me Claude, DeepSeek, Gemini, and the rest), and the VPS just runs the agent process, the memory store, and the gateway. Total cost: about €5 to €10 a month for the box plus $5 to $20 for API calls depending on how much you talk to it.

A few things that made the Hetzner setup actually pleasant:

• CX22 / CPX21 is enough. 2 vCPU, 4 GB RAM, no GPU. The agent itself is light.
• Telegram + allow-list. With TELEGRAM_ALLOWED_USERS set to my numeric ID, the bot is locked to me. Always-on agent in your pocket without exposing it to randos.
• systemd via the built-in gateway. hermes gateway install then systemctl --user enable --now hermes-gateway and it survives reboots cleanly.
• Approval mode ask. Keeps the destructive stuff manual until you trust a given workflow.
• Backups in cron. hermes backup once a day.

Honestly the biggest unlock was just getting it onto a server that does not sleep. The learning loop only really pays off when the agent is actually running long enough to accumulate skills, and that does not happen on a laptop.

Wrote up the full setup as a step-by-step (provisioning, hardening, install, model provider, Telegram, systemd, backups, troubleshooting):

Self-Host Hermes Agent on a Hetzner VPS, Practical Guide

Curious if anyone else tried the Jetson route and got further with it, or what providers people are settling on for the inference side. I am running Sonnet for general work and dropping to a cheaper model for routine cron jobs.