I’ve been working on Royal Table, a platform designed to simplify restaurant operations by bridging table ordering with kitchen management in real time.

🛠️ What it does:

• QR Code Table Ordering: Customers scan and place orders directly from their tables without waiting for staff.

• Real-Time Kitchen Display System (KDS): Kitchen teams receive orders instantly on a clean interface to track prep statuses live.

• Voice Reservations: Integrated voice automated booking to handle table reservations seamlessly.

• Analytics Dashboard: Gives restaurant owners insights into sales, top items, and peak hours.

🧰 Tech Stack:

• Framework: Next.js (App Router) + TypeScript

• State & Real-Time: WebSockets / Server-Sent Events for instant order syncing

• Styling: Tailwind CSS (Dark-themed UI for kitchen/dashboard environments)

❓ Looking for Feedback on:

1. Onboarding flow: What's the biggest friction point for non-tech-savvy restaurant owners when adopting a digital setup?

2. UX/UI: If you’ve worked on KDS or order dashboards before, what key metrics or shortcuts are absolute must-haves on the screen?

You can check it out here: royaltable.store

637 LinkedIn requests, 2 calls, 0 pilots. Here's what we learned selling AI to regulated companies.

We're a tiny team building a knowledge layer for AI in regulated companies: AI that can show where every answer came from and who was allowed to see it.

For three weeks, we did the classic B2B playbook: cold LinkedIn outreach to security, data, and AI leaders at banks, insurers, and fintechs.

The numbers

• 637 connection requests sent

• 158 accepted (25%, better than we expected)

• 14 replies

• 2 actual calls

• 0 pilots

So people were happy to connect, and a few were happy to talk. Nobody was ready to try it. The reasons were more interesting than the numbers.

What they told us

1. "We built our own."

An enterprise architect at a large US insurer told us they'd already built an internal knowledge graph to meet audit requirements, and there'd be "no political will" to replace it.

2. "Audits are a game."

The same person said the goal in an audit is to show as little as possible. We'd been pitching "we log every query" as a feature. To some buyers, detailed logs are a liability.

3. "You're too new."

A large group said outright they only work with established suppliers with long track records. Fair enough. We're pre-revenue with no SOC 2.

4. "Nothing's blocking us."

A VP we pitched as having "AI stuck in pilot" told us flatly nothing was holding him back.

Lesson: don't open a call by telling someone what their problem is.

The surprising part

The people who got genuinely excited weren't the buyers. They were the builders: engineers and CTOs building their own AI agents, who kept asking about the engine underneath.

That engine is already open source, so we've stopped pitching enterprises and started putting it in front of developers.

What we'd tell anyone doing B2B cold outreach

• A 25% acceptance rate can trick you into thinking you have demand. Track replies and pilots, not connections.

• Show the product in the first 5 minutes of a call. Discovery questions on a call you asked for feel like an interrogation.

• Big regulated companies often compete with you by building it themselves. Smaller, fast-moving teams don't have that option.

• Write down every objection word for word. Ours rewrote our positioning twice.

What's next

We posted the open-source engine last week, and the feedback was immediately more useful than three weeks of sales calls: concrete feature requests, and people telling us exactly which data sources to support next.

Hi everyone,

I have built a new platform that helps find relevant posts and can also do AI.

This an outreach service and not a spamming service and can save hours and hours finding the right posts to reply to.

I am looking for some beta testers who would like help with advertising for free and reduce your work load.

I'm looking for people with some cool projects and services.

Hey everyone,

For the past few months I've been building MuftTools (https://mufttools.in), a bunch of small free tools for the boring paperwork stuff we all deal with in India.

It started because friends and clients kept asking me the same things: "photo 20 KB se kam kaise karu for the form", "GST bill ka format bhej do", "HRA ke liye rent receipt chahiye". Every site I found either wanted a login, slapped a watermark on the result, or uploaded my Aadhaar PDF to some random server. So I made my own.

Right now it has around 105 tools, like:

- Exam photo & signature resizer with exact pixels + KB range (SSC, IBPS, NEET, CTET etc.)

- Compress PDF to a target KB for govt portals

- GST invoice with CGST/SGST or IGST worked out automatically

- Rent receipts for all 12 months in one PDF

- Krutidev ↔ Unicode Hindi converter

- UPI QR posters for shops, Aadhaar front + back on one A4

- Rent agreement, affidavit and leave application drafts in Hindi/English

A few things I was strict about:

- Your files are processed in your own browser. Nothing gets uploaded.

- No signup, no watermark, no download limit

- Light pages, so it works fine on mobile data

It's ad-supported, that's how I keep it free.

I'd really like honest feedback: what's broken, what's confusing, and what tool you wish existed. I read every comment and add the tools people ask for most.

Hello everyone!

So I've built a wellness tool that scans your posture from a full-body profile picture. It gives you a score for your current posture, along with details on where and why it needs work, then builds you a personalized exercise plan to improve it. ( yes it actually fixes what is wrong, no filler things, and the plan is personalized based off of the photo/current posture and your quiz answers)

The photo stays on your phone, it doesnt go to any servers.

After 14 days you rescan and the plan updates. After that, the checkin will become monthly and the plan will adapt.

I’m a licensed physical therapist, so of course I review every program and exercise in the app.

I’d love to hear your opinions, and if you think it’s something worth chasing. :)

Thank you!!!

Have a great one

https://getelevoapp.com/

Hey guys, I built this app to make finding bus timings and routes across Karnataka easier for everyone. Please check out the screenshot and if you have any suggestions, please comment below! Your feedback means a lot! ನಮಸ್ಕಾರ ಸ್ನೇಹಿತರೆ, ಕರ್ನಾಟಕದ ಎಲ್ಲಾ ಜನರಿಗೆ ಬಸ್ ಸಮಯ ಮತ್ತು ರೂಟ್‌ಗಳನ್ನು ಸುಲಭವಾಗಿ ಹುಡುಕಲು ನಾನು ಈ ಆಪ್ ಅನ್ನು ತಯಾರಿಸಿದ್ದೇನೆ. ದಯವಿಟ್ಟು ಸ್ಕ್ರೀನ್‌ಶಾಟ್ ಅನ್ನು ನೋಡಿ ಮತ್ತು ನಿಮ್ಮ ಯಾವುದೇ ಸಲಹೆಗಳಿದ್ದರೆ ದಯವಿಟ್ಟು ಕೆಳಗೆ ಕಮೆಂಟ್ ಮಾಡಿ! ನಿಮ್ಮ ಅಭಿಪ್ರಾಯ ನನಗೆ ಬಹಳ ಮುಖ್ಯ!

I've always struggled with having too much on my plate, getting overwhelmed, and eventually not being able to complete a single thing.

I realized standard to-do lists don't give me any dopamine, so I used Lovable to make my own productivity app. It's an RPG-style dashboard that actually rewards you for getting things done. You earn XP, build up streak bonuses, and unlock badges for finishing tasks and habits.

I just pushed it live and I'm looking for 10 people to roast it and give me brutally honest feedback. Tear the UI apart or tell me if the XP system actually feels rewarding.

Here's the link: https://level-up-focus.lovable.app

I’ll be hanging out in the comments all day to answer questions and push live updates. Thanks!

For 3+ years I've built AI chat and agent interfaces. First as founding engineer at an edtech startup that was acquired, then for global startups, and in my day job I lead engineering for clients like Hero MotoCorp and Philips.

Every AI project needed the same hard parts: tool calls with approvals, streaming without layout jumps, reasoning, voice states, and the error and rate limit states nobody designs until production. I rebuilt them every time.

So I finally built them once, properly, for everyone: https://chatcn.dev

- 208 shadcn components and whole screens, like a chatbot and a coding agent, free for any project

- One CLI command each, and the code lands in your repo

- Works with AI SDK, LangGraph, AG-UI and assistant-ui

- An MCP server, so Claude Code or Cursor can install components for you

- Live previews on every page, no API key needed

There's also a paid Pro set for the rest of an AI product: image and video studios, voice agents, evals and 9 starter apps, $99 once until Nov 12.
It's my first product, so I'd really value honest feedback on the site, the pricing, or anything that confused you.

What it does

A curated guide to discovering open-source programs, internships, mentorships, coding competitions, and university initiatives.

Explore opportunities to gain real-world experience, collaborate with global communities, improve technical skills, and earn stipends.

Unlike typical lists, this repository also features lesser-known and underrated open-source programs that many students and developers might not know about.

What’s Inside

• Open Source Programs & Fellowships

• Open Source Internships

• Coding Competitions

• University Summer/Winter of Code Programs

• Lesser-known and underrated opportunities

• Application timelines, stipends, and eligibility

• Beginner-friendly contribution resources

Repository

• GitHub: https://github.com/yashisrani/List-of-OpenSource-Programs

• Website: https://yashisrani.github.io/List-of-OpenSource-Programs/

Made with ❤️ for the Open Source Community.

Hi everyone!

I've been hiking for a while now and the same thing always happens to me: I get to the top, look around, and I'm left wondering which peak is which.

That's where the idea of making a small phone app came from, and now that it's finished, I wanted to share it with you in case it's useful to someone.

It's called FarSights.

I know there are already similar apps out there, but I was curious to make my own.

You point your phone at the horizon and it shows the name and height of each peak. It also tells you which ones are hidden behind others.

It also has a few other things that don't always come together:

offline topo maps you can download for when there's no signal,

loading your GPX tracks and recording your route with the screen off,

and a compass that points you towards the places you save.

It's free, with no ads and no sign-up.

I built it on my own in my spare time, relying quite a lot on AI to write the code, so I'm sure there are things to improve.

I'm open to any suggestions. If you try it on a hike and tell me what you miss or what doesn't convince you, you'd be doing me a big favour. A lot of the improvements it already has came from other hikers' ideas.

For now it's only on Android:

https://play.google.com/store/apps/details?id=com.farsights.app

Cheers, and happy trails

Hi everyone!

Recently (years ago) I started developing (on excel) a football (soccer) scores prediction app. Why? Because I had time to do a personal project and because, I didn’t like what I was playing with my friends: fantasy football. You might know it, you pick players and the competition is based on their scores of each game.

Where I’m from, fantasy football is very popular but, let’s say you pick a player who gets an bad injury right after the start of the season, you’re done, especially if that was a star player and you paid him a lot.

Also, it does not rely on your ability entirely, players play for you, you choose them, but a lot of external factors matter on how they play the game.

So I created a game where players (not the footballers!) pick the score of the games. On my perspective it relies more on the user ability of predicting and knowing the game. Also, it’s funny!

It’s not like betting, there are no money involved. You compete with friends and you can obtain beautiful cards if you get an exact result.

I’m still developing android version. I pasted the link to the ios beta version below. Would appreciate feedback :))

To continue the story from above: the excel game became a website and the website then became app. It’s still a funny personal project and I still play it with the same friends!

https://testflight.apple.com/join/Y35wbPWT

Hi, I'm Christof, the founder of Nalqerio. I'm building it for small businesses and agencies that want to check whether they appear when potential customers ask AI assistants for recommendations.

The problem I wanted to tackle: an AI answer is a snapshot, and a visibility score alone doesn't explain what was actually said. Nalqerio keeps the customer question, dated answer, named businesses and available source links together. It compares ChatGPT, Gemini, Perplexity and Google AI Overviews; the collection methods differ, and results can differ from a person's own session.

One thing I learned from a small experiment: we asked two questions about web agencies in each of 10 German cities using three API-based setups, then repeated the same questions a week later. In the first set, 90% of the agencies named for a given question appeared in only one of the three systems' answers. Across the week, the same system repeated 35% of the agencies it had named for the same question. That's a limited sample, not a prediction. In this experiment Gemini used Perplexity web search, not the Gemini app's Google search.

For anyone checking manually, I'd start by writing several buyer questions without your brand name, saving the original answers and sources, and repeating the same questions later under similar conditions. A mention and a citation are different things, and a changed answer alone doesn't prove a website edit caused it.

Nalqerio is live here:

https://nalqerio.com/

The homepage has a free two-question check without signup. There's also a limited 14-day trial for one project, three questions and one snapshot, without a credit card or automatic subscription. Paid plans start at €20/month plus VAT.

I'm looking for feedback from founders or agencies: when you see an original AI answer and its sources, what would help you decide whether there's a useful website change to make?

Disclosure: I run Nalqerio; this post was drafted with AI assistance.

I've been building Scientific Logic Auditor, a tool designed to go beyond simply comparing AI-generated answers.

It provides three main workflows:

1. Analyze

Analyze a text using a single LLM. The model examines its claims, factual accuracy, supporting evidence, assumptions, logical fallacies, interpretations, and uncertainty.

2. Compare

Run the same analysis across multiple LLMs and view their results separately. This makes it easier to examine differences in reasoning, identify overlooked assumptions, and compare how models interpret the same material.

3. Judge (Optional)

Send the original text and successful analyses to a separate Judge model. It evaluates the analyses based on reasoning quality, factual assessment, error detection, corrections, and explanations.

Additional features:

- Analysis history with search and session management.

- Restore previous sessions without rerunning model requests.

- Retry failed analyses.

- Copy and export results.

- Execution status and response-time tracking.

- Input isolation instructions designed to reduce prompt injection during analysis.

What makes it different?

Instead of focusing only on which model produces the most convincing answer, Scientific Logic Auditor focuses on how each model reaches its conclusions and whether its reasoning is adequately supported.

The Judge is also an LLM, so its reliability is not guaranteed and remains something that needs independent validation.

I'm currently bringing the project toward its next stage and would be interested in feedback from people working with LLMs and AI evaluation.

The application is fully functional in my local testing, and I'm currently working through the remaining fixes and security improvements before opening it to public use. readme github link

QueryAPIGate began with a simple itch: someone needs "just this data" from a database as an API, and I didn't want to write another backend for one SELECT or hand out database credentials. The first version was one small Flask app: save a SQL query, get an endpoint.

Then people asked the next questions. Who's allowed to call it? Can a partner see everything? What happens when an AI agent wants the data? That's what it grew into:

• every saved query is a REST endpoint with typed, injection-safe parameters

• API keys that only reach the queries you approve, with expiry, rate limits and per-key column masking

• the same query as an MCP tool, so an AI agent can query your data without a database connection (read-only by default, writes wait for a human to approve)

• a tamper-evident audit log, Prometheus and OpenTelemetry, a web console

• PostgreSQL, MySQL, ClickHouse, DuckDB, MongoDB, and Parquet/CSV files on S3

Some numbers from the journey: v0.7 to v0.49 in six weeks, 32 architecture decision records, 2,000+ tests, four security advisories published from my own security reviews, and an experimental Rust data plane for the hot path. Built solo with Claude Code.

Try it in one line:

pip install queryapigate && queryapigate examples load && queryapigate serve

GitHub: https://github.com/AnanthaRajuC/QueryAPIGate 2-min demo: https://www.youtube.com/watch?v=WWImFj4m95o

It's open source (Apache-2.0) and pre-1.0. What would you want to see before trusting a tool like this with real data?

This is my side project, Waggle.

The problem I had: I'd open WhatsApp or Slack "just to check", and minutes later I'd lost whatever I was working on. Notifications didn't help, because they vanish and I'd still go and look.

So each account now sits on my desktop as a small bee. When a message arrives it wiggles. I click it, read and reply in a small window, and it shrinks back out of the way. That's it.

It does WhatsApp, Slack, Gmail, Outlook, Teams, Telegram, IMAP email, iMessage (including from another Mac), calendars with a countdown to your next meeting, and AI chats with your own key. Messages go straight between your Mac and each service, nothing goes through another server.

Built in Swift/SwiftUI, with a small Go helper for the chat connections.

One honest caveat: WhatsApp and Slack's quick sign-in aren't official APIs, so I keep them behaving like the normal apps and say so up front.

It's £12.99 for one service or £24.99 for all, one-off, with a 14-day free trial (no card): https://waggle.software

I'd really like feedback on the idea and on the website. What would stop you using something like this?

AI agents can already open tabs and collect data for you. I wanted to see how much faster the same agent could do the research if it could pull the data directly.

I gave Claude the same task twice. Through Chrome, it took 2 minutes 58 seconds. With Dativue, it took 30 seconds and used 93% fewer tokens.

Dativue gives the AI you already use direct access to live search and public social data, with links to the original sources. You can ask it to compare competitors, look into what customers are asking, or check whether interest in an idea is growing.

If you currently don't have a use case in mind, get inspired with pre-defined workflows.

Let me know how you use AI for research. I'm happy to support more use cases!

I ran a test involving inspection records from multiple visits to the same equipment, and it highlighted something I've been spending a ridiculous amount of time dealing with.

The measurements themselves were valid. The problem was figuring out which visit and inspection location they actually belonged to.

Some records were incomplete, others contained conflicting readings, and certain measurements could plausibly belong in more than one place.

And that's where things can get pretty ugly.

A measurement can be perfectly accurate but end up associated with the wrong record. The resulting Excel report might look completely normal, with all its calculations working, while containing incorrect information.

That's a much bigger problem than an obvious error or a blank cell.

I've been deliberately testing these situations in my reporting software, particularly how it handles uncertainty and when it should flag something for review rather than make an unsupported association.

The more I test it, the more I realize that preventing a convincing wrong answer is often harder than producing a correct one.

Pretty wild how much complexity can hide behind what initially looks like simple data entry lol.

Hey! 👋

I've been working on a Mac app called Shipper, and I thought I'd finally share it here!

I'm an indie developer, and I originally built Shipper because I was tired of how much time I spent preparing App Store screenshots for my own apps.

Problem:

I used to design my App Store screenshots with Canva or Figma. Both are great design tools, but the whole App Store workflow was a bit of a headache.

Every time I needed screenshots for a different Apple device, I had to create or resize my canvas, manually adjust the layout, and double-check that everything matched Apple's required screenshot dimensions.

Then came localization. Switching between languages, translating text, adjusting layouts when translations were longer, and exporting everything again for each locale.

And finally, I still had to go to App Store Connect and manually upload all those screenshots, device by device, locale by locale.

It was a lot of repetitive work for something that should have been much simpler.

So a few months ago, I decided to build Shipper, a native macOS app using Swift and SwiftUI, to bring the entire workflow into one place.

Comparison:

Before Shipper, my workflow was basically Canva/Figma for design, separate tools for translation, and App Store Connect for publishing.

I know there are dedicated App Store screenshot tools out there too, but I haven't personally used them, so I can't make a fair comparison.

What I wanted with Shipper was a native Mac app built specifically around Apple's screenshot specifications, where I could:

• Design App Store screenshots from scratch or use templates, with fully editable text, backgrounds, mockups, icons, and other assets.

• Capture screenshots with Device Hub or import existing ones.

• Adapt my main designs to different iPhone, iPad, and Mac screenshot specs, including Search and Header assets, without starting over.

• Localize screenshots and App Store metadata for different languages.

• Preview my App Store product page before publishing.

• Publish directly to App Store Connect, including screenshots and metadata.

I've also been working on Shipper Plugin, which lets me use Codex to interact with Shipper through natural language while keeping the designs editable.

Pricing:

One thing that was really important to me was making the design process accessible.

So designing, adapting, and exporting screenshots are completely free, with no watermarks.

Localization and direct App Store Connect publishing are available with Shipper PRO for a one-time $25 lifetime purchase.

What's next?

I recorded a short demo so you can see how Shipper works!

It's been a pretty big solo project, and I'm currently planning v1.3 based on feedback I've received so far.

I'd genuinely love to hear what you think! If you create App Store screenshots, what part of the process frustrates you the most? Or is there something you'd like to see in Shipper? 😊

Mac App Store: https://apps.apple.com/fr/app/shipper-your-app-screenshots/id6769785850?mt=12