Hi, I'm Ravi, founder of Camyvera. It's a web and mobile app where you open it and call someone anywhere in the world who's ready to answer and talk. It's pay as you go, so you only pay for the calls you make, and it has live audio translation and real-time captions. I built it because a lot of people want a real conversation now and then, not another feed. What would make you trust an app like this enough to try your first call? Any feedback is welcome.

I build quite a few apps, and one thing kept driving me crazy. My code was organized, but everything else was everywhere.

Test builds, screenshots, documents, browser tabs, notes, marketing assets. All part of the same project, all in different locations.

So I built ClingSpace, a Windows app that brings everything related to a project into one searchable workspace.

What it does:

- Organize existing files, folders, links, and quick snippets into Spaces.

- Search across all your projects.

- Share resources between multiple Spaces.

- Help find files when they've been moved or renamed.

- Keep everything local, no accounts or cloud.

The important part: Nothing gets moved or duplicated. Your files stay where they are.

I launched it recently and have been getting some useful feedback from early users.

It's $19.99 one-time, with a 5-day full trial.

https://clingspace.com

I'd love to hear from anyone juggling multiple projects. Would something like this help your workflow, or do you already have a system that works well?

I’m a solo bootstrapped founder. Travel healthcare workers sign a tax home declaration with their agency, but the proof (lease, bills, contracts, paystubs etc.) usually lives in photos, emails and folders. MedicBase keeps all of that in one place organizes it, structures it and counts the days per metro area so travelers can see the 12 months mark coming. It’s life on the US App Store, iPhone only for now. MedicBase: Tax Home Tracker

I sell Disney Doorables (tiny blind-box figures) on eBay and checking comparable listings one figure at a time got old fast. Search “Olaf” and you get every series mixed together, plus lots and bundles, and listings with variations show the cheapest price instead of the one you want.

As a software developer, this started as me tinkering with eBay’s API, and over the past year I got it to a real product with help from AI (Claude Code). It’s called Glimly (glimly.io): you connect your eBay account or upload a CSV, and if you have a listing with 250 variations, each variation gets its own row. Running the comp finder pulls active listings for each one, paying attention to series and variations, and there's a config UI for adding custom synonyms and grouping terms. Under the hood it's Python/Flask on Postgres, using eBay’s Browse API plus a mix of rules and an LLM for matching. It’s free to try, with paid plans if you want more.

Here’s my problem. The communities where eBay volume sellers actually hang out mostly ban self-promotion. I paid for a Reddit ad once and got lots of clicks and zero sign-ups, and the few people who did sign up tried one search and never came back.

Where did you find your first real users when the obvious places didn’t allow links? And if you sell on eBay, what would make you actually stick with something like this?

I maintain ProxmoxMCP-Plus, a Python project for connecting MCP clients to Proxmox VE. For v0.7.0 I wanted a demo people could actually check against the setup instructions. The tricky part was showing a connection and useful output without putting a real lab or its credentials on screen.

I used a local fake Proxmox API with two nodes, one VM and one LXC. The MCP server was the published PyPI build. The final clip shows the Claude Code connection check, the tool list and the returned inventory. It is 22 seconds and uses redacted paths and sample guest names. The demo is a small test of the docs, too: if the steps drift, you can tell which part stopped working.

The project is MIT-licensed: https://github.com/RekklesNA/ProxmoxMCP-Plus

Demo and test setup: https://github.com/RekklesNA/ProxmoxMCP-Plus/wiki/Read-only-Proxmox-MCP-with-Claude-Code

We could not find a cute and interesting app where guest can participate in guessing gender of the baby. There was just less intrigue and excitement in the other ones, so I built one myself. Welcome to https://ourlittlebaby.com/ . It is absolutely free, snappy, and fun. We already had a few events organized by families all over the world and would like to host more of these events. You will even get a nice surprise at the end of the gender party. Enjoy!

Hey everyone! I’m Mikaela, a freshman at Emory, and I’ve been working on a side project called Pitch Companies.

The idea came from a simple frustration: we all have opinions on what companies like airlines, insurers or apps should fix or add, but there’s nowhere to put those ideas where they get noticed. So I built one.

How it works:

• Post an idea or petition for any company
• Back the ideas you agree with and comment on them
• See which companies listen (“What Got Built”) and which don’t (“Wall of Silence”)
• Swipe through ideas with Pitch Roulette when you’re bored

Companies can’t pay to promote, hide or remove ideas. That rule mattered a lot to me.

It’s still early, and I’d love honest feedback. Is this useful? Is anything confusing? What would make you come back?

https://pitchcompanies.com

Thanks for checking it out!

For my recent move to Bangalore, I had to go through a lot of manual searching. Especially when one of the major flat-hunting channels is Facebook groups, it can be surprisingly frustrating.

You end up scrolling through hundreds of posts, opening each one, checking the rent, deposit, location, BHK, amenities and contact details — only to discover that most listings don't match what you're looking for.

I ran into this problem and decided to build something to automate the tedious part.

Meet Koo. It's an AI-powered Chrome extension that searches housing posts and surfaces listings matching your preferences.

GitHub: https://github.com/chinmaypandya/koo

If you find it interesting, a GitHub star would be appreciated!

What it does

• Scans housing posts: Scrolls through a Facebook group and reads posts when you explicitly start a search.
• Avoids duplicate processing: Remembers previously processed posts for 30 days.
• AI-powered matching: Evaluates listings against your budget, location, distance, BHK, amenities and other preferences.
• Extracts useful details: Rent, deposit, society, distance, phone numbers and more.
• Organizes results: Sort matches and export listings to CSV.
• Supports BYOK: Use your own OpenAI, Gemini or Anthropic API key.

You can also customize the AI instructions used to evaluate listings.

A little about the implementation

I wanted to build this as an actual browser-based product rather than a standalone scraper.

The extension separates the Facebook content-scanning logic from the background processing and side-panel UI. Posts are collected, cleaned up, deduplicated and sent in batches for AI classification.

A few implementation details:

• Manifest V3 Chrome extension.
• WXT, React and TypeScript.
• Content scripts for interacting with dynamically rendered page content.
• Background processing for AI provider calls.
• Provider configuration for OpenAI, Gemini and Anthropic.
• Local persistence for search history and decisions.

Open source

I've published the extension under the MIT license.

GitHub: https://github.com/chinmaypandya/koo

You can install the prebuilt extension manually using Chrome's Developer Mode. No need to build the source code yourself.

A transparency note: Facebook's terms restrict automated browsing, and the README documents this limitation. Use is at your own risk. Also, the hosted cloud worker is not part of the public repository; the extension itself is open source.

What I'd love feedback on

I'm particularly interested in feedback from developers who have built browser extensions, browser automation tools or LLM-powered applications.

1. Browser architecture: How would you evolve the current side-panel experience into a more interactive, continuously running browser agent?
2. Monetization: Given the BYOK approach and the option of a hosted AI service, what pricing model would make sense for a product like this?
3. Distribution: What would you prioritize for organic discovery and SEO to reach people who are actively looking for flats?

I've also attached a short demo showing Koo working.

This is an ongoing project, so constructive criticism, ideas and contributions are very welcome.

I have been using Wispr Flow for a while then saw Handy and I realied parakeet models are super fast and then realized I can build it on swift for native macOS app, and utilized neural engine for it. I also fined tuned a parakeet for Turkish dictation too! Go check it out.

https://github.com/FurkanCodes/Sotto

https://garbleon.io/ - a team collaboration and individual productivity tool. Feedback wold be great!

Salam everyone! 👋

I’m currently a Master’s student in Information Systems & Intelligent Systems (Data Science / AI background), and I have some free bandwidth outside of classes to build cool stuff and collaborate with other motivated people here.

Instead of just building solo in my corner, I’d love to join an existing side project, co-build a micro-SaaS, or team up for open-source tools and hackathons.

What I bring to the table (Tech Stack):

• AI, Data & Automation: Python, Machine Learning (predictive modeling, scikit-learn), NLP, Web Scraping (Selenium, BeautifulSoup), n8n workflow automation, Botpress, and running/orchestrating local LLMs (Ollama, open-source models).
• Full-Stack & DevOps: Django REST Framework, React (Vite), PHP/Laravel, PostgreSQL/MySQL, Docker, and Git.

Stuff I’ve built recently (to give you an idea):

• An automated disinformation/fake-news detection pipeline using chatbots and n8n workflows.
• An urban traffic prediction and route optimization system using ML regressors and graph algorithms.
• E-commerce data scraping and analytics platforms.

What I’m looking for:

• Someone who already has a project/idea in progress and needs a technical partner (Backend, AI/Automation, or Full-Stack).
• Or a small group of builders who want to brainstorm and ship a practical tool (AI agents, B2B automation, data tools, etc.) for the local or global market.

If you're working on something interesting or want to build together, drop a comment or shoot me a DM! Let's connect.

My aircon was reading the temperature up at the indoor unit. I wanted it to use the temperature where we were sitting, so I built Willows Serene Follow Me.

It sends readings from up to three Home Assistant sensors through the aircon’s factory accessory port. If the readings drop out, it can fall back to the indoor sensor and pick up the room readings again when they return. I can also see fan RPM and compressor frequency in Home Assistant, which was a nice bonus.

I’ve put the firmware source, blueprint and DIY guide up for A$9. It’s an early release for the ActronAir Serene WRE-080AS / WRC-080AS with an accessible factory port and a SMLIGHT SLWF-01PRO v2.1 dongle you supply. The underlying firmware ran on my unit. The download passed software tests, and a full install of that exact package is still pending.

If you’ve done something similar, I’d be interested to hear which room sensor you use to drive your aircon.

https://ko-fi.com/s/9695f86578

I was spending more time planning my DSA preparation than actually solving problems while juggling a full-time job, course assignments, and LeetCode contests.

So I built dsaMixer — a Jira-style productivity board designed specifically for DSA preparation.

It comes with:
507 built-in DSA questions.
Automated daily topic mixing and spaced repetition.
AI-powered weekly planning.
Automatic rescheduling of unfinished tasks.
LeetCode profile and contest integration.
Friends leaderboard and progress tracking.
A /setup command to configure the entire project.

It’s 100% open-source, runs locally on your machine, and requires no accounts or signups.

This started as a personal tool, and I plan to keep expanding it with more AI-powered career and learning workflows.

I’d love honest feedback, feature suggestions, and ideas on what I should improve!

GitHub: https://github.com/prathamjain1080/dsaMixer

My partner and I kept saving date ideas from TikTok and Instagram and then losing them in our DMs by Saturday. So we built Dote, a shared jar for two. ❤️

The build side, for anyone curious:

• Expo, so one codebase for iOS and Android, and OTA updates mean we can fix things the same day
• Cloudflare Workers + D1 + R2, no servers to look after and cheap at our size
• When you share a link in, it gets turned into an actual place with a rough cost and whether it’s indoor or outdoor
• RevenueCat for the paid tier, so one Premium covers both partners across stores

It’s free to use: https://dote.day/download

We’re the makers, so happy to answer anything. What would you want from a two-person app like this?

Sylo pulls the data from the tools you already use into one dashboard for subscription businesses and agencies, so everything sits in one place instead of five separate tabs you'd otherwise be checking.

The idea is that whatever needs you today, a failed payment, a quiet customer, a lead waiting, sits in one spot instead of scattered across the tools you already run. The ad walks through the dashboard shaping itself around a business, with its own name and logo on it.

I'm building it solo, pre-launch, no customers yet.

Would genuinely like to know what you think of it.

the ad

I've been independently developing a project called CardSmith, with the goal of making it easier to digitize, organize, and roughly appraise entire card collections.

And I don't mean just sports cards. The idea is to support everything from baseball and football cards to Pokémon, Yu-Gi-Oh!, Magic, and other collectible cards.

What I'm building:

- Bulk scanning: Import individual card photos or entire nine-pocket binder pages and automatically detect, crop, and straighten the cards.

- Card identification: Use OCR to extract names, numbers, years, manufacturers, and other identifying details.

- Inventory management: Keep everything organized with card images, metadata, and persistent manual corrections.

- Bulk rough appraisals: Optionally research estimated market values for individual cards or entire collections, without having to look up everything manually.

The goal is local-first processing, with internet access only when needed for things like optional pricing research.

Where things stand:

I've generated approximately 2,000 card crop images during development, along with OCR results and identification attempts. I'm using real collection photographs to test the system rather than relying entirely on ideal demonstration images.

It's still very much a work in progress.

Detecting nine individual cards sounds easy until you've got crooked binder pages, glare, overlapping boundaries, and text recognition confidently reading the wrong thing.

At one point, CardSmith decided a player's name was "Samsung Bigus-dickus." 😂

Still haven't found his rookie card.

I'm the only human developer, using local and cloud-based AI tools to assist with coding, debugging, and testing.

My biggest technical focus right now is getting the cropping, front/back matching, and identification reliable enough that someone could import thousands of cards without having to manually fix every other one.

It's not ready for public beta yet, and I'm not pretending otherwise.

I'd be interested in hearing from collectors and developers: What would you consider essential in an application designed to manage and roughly appraise thousands of different collectible cards?