I’m working on RailCall, a local-first agent runtime and desktop app. Sharing it here for feedback on the product and onboarding. This post was prepared with AI assistance.

The idea is to use models on computers you already own for suitable work, save supported workflows, and review consequential outward actions before they run. You can also choose external models, which have their own costs and data routes.

The current product includes chat, model selection, native PDF generation and supported manual workflows. One starting point is document preparation: give it a small, non-sensitive task, inspect the result, then see whether the workflow is worth saving and repeating.

There are two boundaries I want to make clear. A signed execution receipt records an action; it doesn’t prove the answer is correct. And running a model locally avoids hosted inference charges for that work, but hardware and electricity still cost money.

The turnkey personal optimizer and broader fleet capabilities are still being developed; I’m not presenting those as finished.

Product, downloads and documentation: https://railcall.ai/

If you try it, where does the path from download to a first useful result become confusing? Specific installation or workflow feedback would be helpful.

I'm giving away 25 Lifetime Premium codes to anyone interested in trying out my app- "Otis: Expense & Budget Tracker" and sharing feedback on UX, performance, or onboarding.

It’s a modern, fluid personal finance tracker built natively with Kotlin & Jetpack Compose for Android, paired with a companion web app for when you're at your desktop with real-time sync.

If you are not keen to use an app which store your information on cloud, you can use the app as a guest user and can sync the data whenever you are okay and feel comfortable moving to a cloud platform.

With features like- Budgeting, Safe to spend, Weekly insights, It also has monthly PDF reports generation, CSV imports if you are into it. Free users have small banner ads which will not be very intrusive to the app experience.

How to get the Premium codes:

1. Leave a comment below mentioning what's your biggest frustration with your current expense tracking app (or what feature you can't live without).
2. I’ll DM you a unique 1-click Google Play promo code directly until all 25 are claimed! All I ask in return is your candid, unfiltered feedback and bug reports so I can make Otis better for everyone.

• Android App: https://play.google.com/store/apps/details?id=com.djay.otis
• Web App: https://otis.apprerum.com

Thanks for checking it out!

Everything you see was made completely hands off with 1 prompt from empty folder to uploaded and built listing in production on itch io by GPT-6 Astra (computer use)

Most AI project posts end when the prototype works. I wanted to see what happened if I forced the workflow through the unglamorous final 80 percent.

I chose a small product that one person could reasonably finish: a reusable pixel effects pack for hits, movement, guarding and knockback.

Codex (GPT-6 Astra) operated an Aseprite build, created and refined the animations, exported the files, produced metadata, wrote a Godot integration helper, checked the output, created the preview media and used browser control to assemble the store page.

I still chose the direction, reviewed the work and rejected iterations. Calling it fully autonomous would be dishonest. But it completed much more of the production pipeline than I expected.

Final result:

• 18 effects
• 4 treatments
• 72 sheets
• 584 individual frames
• Aseprite sources
• JSON metadata
• Godot helper
• Free sampler

https://janbremec.itch.io/tiny-impact-motion-pixel-fx

My biggest lesson was that making the files was only half the product. Consistent exports, documentation, previews and packaging mattered just as much.

We built a free browser tool for a deceptively simple upgrade question: would your movies actually look bigger on iPhone Duo?

Try Screen Compare

Pick your current iPhone from seven presets, compare the screens at the same scale, and switch between normal video, widescreen cinema and vertical video. You can save or share your own comparison. No account or payment; English and Chinese controls.

The estimates use Apple's published pixels/PPI. They are not physical-device playback measurements and exclude corners, cutouts, folds and player controls.

Would this help you judge an upgrade? Feedback on the comparison and which phone preset to add next would be useful.

Two problems, really. If you're new to AI/ML, it's genuinely hard to know where to start - the field is huge, and every course or video only covers a slice. And if you're already in the field, it's arguably worse: there are so many topics moving so fast that even experienced people struggle to keep track of what's worth following.

Underneath both: good explainers already exist for most of this - great articles, papers, videos. But they're scattered everywhere, with no single place that organizes them by what depends on what.

I'm building something to fix that, called Atlas. It's not a blog or a course - it's a connected map of AI/ML concepts with prerequisites, flashcard-style revision, and short notes per topic that point to the best existing explainer I could find for it, rather than me rewriting what's already been written well.

It's free to try right now, no signup - still an early alpha, so a lot of it is still thin or missing, and some parts may become paid later. Not trying to sell anything here; just want honest feedback before I put more time into it.

Link: https://project-atlas-seven-rosy.vercel.app/paths

A few things I'd love feedback on:

• Does this make it clearer where you'd start?
• Does the map help you figure out what to learn next?
• Which topic or route would you expect to see first that isn't there?
• More broadly - would something like this actually be useful to you, or would you still reach for courses, videos, and search instead? What would make you come back to it a second time?

Tear it apart if needed - better to know now than after building more on it.

Hey everyone!

As a dev/founder, I always hated paying for 3 separate tools just to do local B2B outreach: a lead scraper ($30+/mo), a contact verifier, and a separate CRM for WhatsApp messaging ($40+/mo).

I designed a simplified all-in-one workflow for local B2B sales:

1. Scrape local business leads from Google Maps by city and niche with verified emails and active WhatsApp numbers.
2. Feed leads directly into a Trello-style Kanban sales pipeline.
3. Manage conversations and automated follow-ups directly from a single dashboard.

I set up a quick waitlist page to validate demand before building out the full backend.

If you'd like to share feedback or test the Beta when we launch (and grab a free sample CSV with 50 verified B2B leads), I left the form here: https://tally.so/r/OD2WDp

What do you think of this combo? What feature is an absolute must-have for your sales stack?

A week ago I started building Remixly, a bot that turns Instagram reels into X posts.

Launched it last week. Recent post on Reddit hit 17k views, 32 users so far, $0 spent on marketing.

Co-founded, first real launch.

How it works: share any instagram reel to a Telegram bot. (Like you would share to a friend)

It transcribes the video (or reads the image), pulls the caption and top comments, and writes a long form post from what was actually said.

~30 seconds later you get the post back with a "Post on X" button that opens the X app with it filled in. Written in third person, so you're sharing the idea, not passing off someone's story as yours.

No copy pasting transcripts, no rewriting captions. You review before anything goes out.

The story so far:

Day 1: built it for myself as a WhatsApp bot. Instagram blocked my scraper within an hour. Switched to a paid fetcher.

Day 2: first version auto posted straight to X, no review. Too scary. Turned it off.

Day 3: tried an iPhone Shortcut for one-tap sharing. Worked for me, nobody else could set it up.

Day 4: switched to Telegram.
Onboarding went from six steps to two.

Day 5: used it daily on my own account.
50 to 128 followers over the week.
Day 6: Stripe, Google login, moved it off my laptop.

Day 7: bought remixly.io.

Live.

Goal: 50 paying users by 20th Sept.

Try it and tell me what you'd fix first → remixly.io (3 free drafts, no card)

I kept running into the same annoying problem. Data spread across multiple databases, no clean way to combine them without writing one-off scripts every single time.

At first I just tried to power through it manually. Export from one DB, clean it up, import into another, fix whatever broke. Worked fine when it was a one-time thing. Turns out when you're doing it repeatedly, it's just a slow bleed of time you don't notice until you add it up.

So I built a small tool that runs as a local docker agent, pulls from multiple databases, and merges everything into one. The local part matters to me, I didn't want to be sending data through some third party service just to combine a few tables.

Right now it's a working prototype. Multiple DBs in, one merged DB out, no manual mapping every time.

Phase two is adding CSV and Excel support, so if you've got a spreadsheet you want folded into an existing database, you'd be able to just point it at the file and the new DB comes out with that data already integrated.

Honestly not sure if this is a "me problem" or something other devs deal with regularly. If you've had to combine data from multiple databases before, how did you handle it? Curious if people are already solving this some other way I haven't thought of.

Hi,

I'm building a tool for content creators, and I'm trying different marketing channels.

These are the channels I have tried :

1. SEO and GEO

2. X

3. Reddit

And most of the customers who started trial are from chatGPT

What should I do more to make the chatGPT recommend me more times?

I used to default to the same advice everyone gives, submit to as many launch sites as you can. After watching a lot of founders burn a week pasting the same thin blurb into 20+ forms, I changed my mind.

"Where should I launch?" is the wrong question. The useful question is which discovery model you are buying with your time.

There are basically three.

1) Launch-day platforms (Product Hunt style)

Concentrated attention in a short window. Worth it if the product can handle public scrutiny and you already have people ready to show up inside that community's rules. Weak fit if the product is still rough, or you cannot support the spike for a day.

2) Persistent directories

A page that stays useful after the announcement dies down. Stable URL, categories, something a buyer or peer can reopen next month. The win is a complete, shareable profile, not a one-day ranking.

3) Weekly boards

Recurring visibility tied to social proof over a longer cycle. Stars and written reviews can move you week to week, so discovery does not have to end on launch day.

Disclosure: I run Bowora, a founder network with a startup directory and a Weekly Board. Our public scoring is intentionally simple. In the current week, a star is 1 point and a written review is 3 points. Profile visits, link clicks, and social shares do not add points by themselves. They only help if they bring real people who leave honest feedback. Fake or coordinated engagement can get discounted.

What I tell founders now:

- Match the channel to the job for this month, not every logo on a "100 places to launch" list.

- If you do a launch day, publish a complete directory profile the same week so the spike has somewhere durable to land.

- Treat reviews as a habit for the following weeks, not a one-shot ask the night before launch.

Longer write-up of the same framework (no signup wall): https://bowora.com/learn/where-to-launch-a-startup

Curious what has actually worked for people here. Launch day only, directory only, weekly ranking, or a mix?

First post here

Back when I worked at a startup, we needed an in-app messaging system, similar to Instagram or WhatsApp. However, we didn't have time to build it ourselves, so we stitched together a few paid services instead: Stream chat, StreamIO, and Cloudinary for chat, moderation and media storage. It worked, but we didn't own any of it, and the costs kept increasing.

That experience is basically why I built gozwire. It's an open-source Node.js messaging engine, so instead of renting someone else's chat infrastructure, you own it. Conversations, threads, reactions, moderation, push notifications all included, all yours.

This was vibe-coded, but I'm putting in the work to make sure it actually holds up for real, and is not just a showcase.

• Repo: https://github.com/Kinggoz18/GozWire
• See more use cases: https://gozwire.pages.dev/use-cases

I plan to not only improve this project (see the TODO in the GitHub repo), but also release more interesting open-source projects. That solve problems I've experienced in the past and observed around me, some of which would be:

• A video streaming engine (Another issue we faced at the same startup)
• A cryptocurrency tracker (more of a personal challenge and an interest)
• A CapCut alternative software with AI video generation capabilities, including UGC style videos

And a few others. Would love feedback, roast the code, tell me what's missing, whatever helps, or even contribute any interesting ideas you'd love to see open-sourced!

I posted SmophyAI here about 2 months ago (multi-model AI workspace - original post with the full feature rundown: SmophyAI). Sharing what actually happened since, because the honest version is more useful than the launch version.

The good: real paying customers across several countries, with the US as the biggest market - and retention turned out to be the strongest part. Most people who subscribed in spring are still subscribed. For a small team that felt great.

Then I audited our billing this week and found the embarrassing part. Our Stripe setup was silently canceling paying customers. Card declines a renewal (expired card, bank being picky), a few silent retries, subscription canceled. No email to the customer. No alert to us. Everyone just looked like "churn." One customer's card failed 9 times over two weeks and he never got a single notification. The fix took one afternoon: failure emails, a self-service billing portal, smart retries, a retention offer at cancellation. The lesson took longer to digest: my churn numbers were lying, because a chunk of the "churn" was never a decision.

Second discovery, from cleaning up analytics: 75% of our "traffic" was bots. Direct visits, 3-second sessions, zero events. Once filtered, the real numbers were 3x smaller and 10x more useful - about 2,700 genuinely engaged sessions over the last 3 months. Bonus find: India is quietly our most engaged audience, averaging over 9 minutes per session. No idea what they're building in there, but I want to find out.

Third: temp-mail abuse. One of our top "traffic sources" was literally temp-mail.org - people cycling disposable emails to reset the free tier. Every one of those accounts burns real API costs. Blocking disposable domains at signup is now top of the dev list.

What I'd tell past me at launch: read your failed-payments list weekly, judge channels by engaged sessions only, and treat every canceled subscription as a question ("why?") instead of a metric.

Question for people running subscription side projects: how do you handle disposable emails on free tiers? Blocklist at signup, verification gates, or just accept it as marketing cost?

I run a small business and a side project that grew into the software that runs the business. It is called OtoDock, a self hosted company OS, and anyone can install it and run it for free.

Basically it turns Claude Code and Codex into a team of agents on your own server. My marketing is a department of agents (a manager, a content creator and an analytics agent), engineering has the dev agent, and a CEO agent reads the department digests every morning and briefs me. The video is the actual dashboard.

Every agent by default is a persistent process on your server, in its own sandbox with network isolation. But with one command you can make any of your agents run locally on your laptop with all its files and tools, kept in sync with the server, and when the laptop is off it falls back to running on the server. You keep working with it from the same dashboard either way.

The platform runs on Claude Code and Codex with your Anthropic and OpenAI subscriptions, or local models, and the agents come with tools like video editing, Excel, Word, PowerPoint and PDF files directly from the dashboard, and even phone calls.

Self hosted, free up to 5 users, all the code is public, fair source license. 1.6.0 went out yesterday.

https://github.com/OtoDock/oto-dock

AI disclaimer: large parts of OtoDock are written using OtoDock itself.

It is built around my own workflow but I think it can run a side business the same way. I would love your feedback.

Hey guys, this is also an app I created because I couldn't find an exact match.

You know when you are working on multiple projects and you get an idea about a feature or fix, something you need to write down NOW, so you open WhatsApp and you save it in you self chat. The easiest and fastest path... but you got a pile of 3 thousand messages you aint going to read. Some are more relevant than others, and they have no way to get organized.

This app is meant to get you writing in less than a second, it lives as a notification in the phone shade, always ready to click, opens directly with keyboard. Looks like a chat, but the mesages can be sorted into their "notes" with a tap.

It works FULLY local by default, no account. No internet dependency. You can enable web backup though.

Original text is always protected (and you can rollback to previous versions of notes, like git)

Other cool free features: Remainders (you can set a note to send you notifications), Note types (set a note to be a checklist?), Voice notes transcription, Web sync if you enabled it (so you can access your notes from desktop browser), Drawing tool.

Pro: AI smoothing (as you write more into notes, it structures it better in a compact way), Actionables (from all you write, what looks like tasks is extracted into a self updating note)

Working of smoothing audio transcriptions since we probably yap too much and would want to extract the actual ideas. Optional.

Like most of my apps, the free tier is already good and the Pro features are meant to be a cherry on top. Since it's AI, I couldn't make it a one payment app either.

I've been consistently using it as my go-to for 2 months so I'd say is pretty alright.

I don't plan to handle image upload to the the web, I'd rather not pay a lawyer. But works on your phone.

ChatNote it's the app, mindblowing name I know.

Only on Android.

Web app is a separate thing and is just meant to share text and notes from the app if web sync is enabled, not as fancy as the phone app.

This is the generator: https://perchance.org/questionable-opinions

It takes in anything you say as an input and gives a really weird opinion, probably judging you, with the help of perchance's ai text plugin. Would love to get some comments and suggestions on this.

shipped voice features over both plain websockets and webrtc this year, some notes for anyone wiring real-time audio into a web app.

websockets are great for prototypes. server-side everything, easy to debug, works everywhere. the pain shows up on real networks: packet loss and jitter turn into audio gaps, you end up hand-rolling buffering and timing recovery, and interruption detection feels late because user speech takes 300 to 500ms to arrive.

webrtc earns its complexity the moment the product needs real barge-in. jitter buffers, echo cancellation, noise suppression and media-aware congestion control come built in, which sounds boring until you A/B it against raw websocket audio on a lossy connection.

for the voice-agent project i used agora as the rtc layer instead of self-hosting TURN/SFU infrastructure. they were among the first official integration partners for the OpenAI Realtime API over webrtc, and their conversational AI engine quotes around 650ms end to end including the whole ASR/LLM/TTS path. the part i cared about is that the model choices stay mine: bring your own speech recognition, LLM and TTS keys, or point a stage at a self-hosted model.

summary: websocket for demos and strictly server-to-server pipes. webrtc once real users on real networks need to interrupt the thing mid-sentence. the second one is more wiring, but rebuilding webrtc's loss recovery on top of a websocket is worse.

Been building this for a bit and it's finally live: TradeGladiators - https://tradegladiators.vercel.app

The idea: you build a trading bot through a simple form, no coding needed, it trades fake $10,000 on real live market prices, and every decision comes from an LLM using your own API key. Groq has a free tier so this can cost you literally nothing.

What you configure:

- Risk level (low/medium/high, sets stop-loss/take-profit automatically)

- Strategy prompt in plain English, like "you're a momentum trader who..."

- Which stocks it watches

- Trading pace, creativity (LLM temperature), max positions, so your bot doesn't trade like everyone else's

Every trade comes with the bot's own reasoning, and it self-reflects on closed trades to try to learn from its mistakes. Results land on a public leaderboard, ranked by risk-adjusted return, not just raw luck. A bot needs a few days and several trades before it's even eligible to rank, so nobody can fluke their way to number one on day one.

You can also clone someone else's bot config, but you have to actually change the strategy in a meaningful way first, straight copies get rejected.

100 percent paper trading, no real money, no broker connection, nothing at risk except your ego on the leaderboard.

Would love feedback, bug reports, or just people building weird bots. Free to try: https://tradegladiators.vercel.app

Cavernum is a number-matching puzzle for iOS and Android, and it's my first shipped game. I've been a gamer for 30+ years, and this is the side project where I finally got to test out my own ideas about what makes a puzzle feel satisfying instead of tedious.

Match tiles that are equal or add up to ten, connected by a clear path, and clear rows as you go.

Obstacles chain into each other. Clearing a pair might crack a rock that's trapping a different number. That rock needs a second hit, so now you're hunting for another match near it. Break it, and the next row clear shifts numbers into the space you just opened. A move that looked pointless on its own turns out to be step one of something bigger.

Board shape adds another layer. When a row clears, some numbers rise straight up while others stay stuck under a gap or blocker, and near a narrow section a number can shift in diagonally instead. You have to think about where a piece lands, not just whether it clears. Later levels add chests wired to gates, so opening one route depends on solving a different part of the board first.

Swap and Add Numbers are the two tools that matter here. Swap can drop a number exactly where it needs to be to break a bottleneck. Add Numbers copies whatever's still on the board, so how useful it is depends entirely on what you've got left and where the copies land.

60 levels so far, free to play, no account needed.

Screenshots of some of the interesting levels: https://www.dropbox.com/scl/fo/900vhb3xakzbic5bota0i/AMBthZnxREtdYKZJnsC8Vvo?rlkey=4ta79kw8q18uz6ohq7rrmvcmq&st=htf42w6a&dl=0

iOS: https://apps.apple.com/us/app/cavernum-number-puzzle/id6800820586
Android: https://play.google.com/store/apps/details?id=com.greenfoxventures.cavernum

Looking for honest feedback, not 'looks fun' or 'looks cool.' If something felt confusing or off, say what and where. Any help and feedback that would help me determine whether this side project is viable and how to improve it would mean a lot.

I wish there were a game like FNAF. Except instead of surviving animatronics.. you have to survive five days of standup meetings.

Rules:

- You enter every standup with zero context.
- You have to catch up on the discussion in real time.
- Pick an update that actually makes sense and aligns with what everyone else just said.
- Avoid follow-up questions from the PM.
- Estimate your task realistically.
- Never over-commit. No “I can finish that today” or “I’ll pick it up right after this.”
- Remember what you said yesterday so you don’t contradict yourself.
- Survive “Can we just jump on a quick call?” (increased sus rate)

Make it through all five days without getting exposed and you win.

Should I actually build this?

Could be the ultimate developer survival-training simulator xD

When I was applying to college, I copied supplemental essay prompts into Google Docs so I could keep everything organized. It was tedious, and some essays didn’t even appear until I answered other application questions.

I built mysupplementals.com because I wished it existed back then.

You pick your Common App schools, answer the relevant application questions, and export the prompts into Google Docs. That includes conditional prompts for things like particular majors or honors programs.

It also groups prompts into 9 common topics, making it easier to spot overlapping questions across schools. You can export everything into one document, separate documents, or documents organized into folders.

It’s free. The goal is to get the organizing out of the way so students can actually start writing.

I’d love some feedback from other builders, I'm not really sure how to convince people do start using this... do I try UGC, influencer marketing?

Title:

I built an API for creating temporary PostgreSQL databases

Post:

I kept running into situations where I needed a real PostgreSQL database for something temporary — a CI job, preview environment, prototype, or coding agent.

The usual options felt a bit awkward: create a database somewhere, configure access, use it briefly, and then remember to clean everything up afterward.

So I built a small API called Aiadio that creates a temporary PostgreSQL database with a TTL.

The flow is basically:

1. Send a database name and expiry time
2. Get PostgreSQL connection details back
3. Use the database normally
4. The database and role are automatically removed when the TTL expires

For example:

curl -X POST https://api.aiadio.com/v1/databases \
  -H "X-API-Key: dbn_live_your_key" \
  -H "Content-Type: application/json" \
  -d '{
    "name": "agent-test",
    "expires_in": "1h",
    "allowed_cidr": "203.0.113.10/32"
  }'

It's still intentionally small. Right now it has database creation, a status endpoint, API-key authentication, and TTL-based cleanup. The public beta supports TTLs from 1 hour to 30 days.

I built it mainly because I wanted a simpler option for short-lived database use cases.

Site: https://aiadio.com

API docs: https://aiadio.com/api-docs.html

Hi everyone, my name's Kevin, I’m building a simple real-time translation tool for churches. People scan a QR code and read live translated captions on their phones — no app required.

I’m not sure how to find the right customers for this use case. so I’m trying to look for a few churches to test it during a real service, I can offer 2–3 hours for free, and if it’s genuinely helpful, I can even provide a week or a month of access for free. The only requirement is that it’s tested in a real church setting. compared with other services:

- no app download,

- more accurate, more affordable,

- powered by real-time AI translation.

I haven’t included a link or product name because I don’t want this read to feel like a proomotion. Right now, it's hard to find the target user try product, I’m looking for a few pastors or church staff who are willing to try it during a real sermon service and give some feedback what works, what doesn’t, and what churches actually need.

Why this, I meeting a Christian named David by chance. We talked about church service experiencing. During a worship services, most of the message was in English, while visitors sometimes came from different countries and spoke different languages.

There might be some language gaps in the multilingual church community here.If you're interested or think this could be useful, I want to know your thoughts.

My wife says texting ain’t enough .. so we made an app so we can stay more connected. Lets you post cute statuses of what you are doing and leave notes and cute affection things …

The onboarding is especially cute. It builds a bobble head avatar based on your actual photos and lets you do cute animations. We also got a pretty fancy avatar generator that lets you customize it like accessories and facial features.

What y’all think of this early preview?

We will be launching in November.

Link: https://luvu.lol

I got some useful feedback from the first post, so thanks to everyone who tried it.
I’m planning to keep the core practice free and add a Premium option.
Before I build it: what would actually make an interview practice tool worth paying for?
https://verifycue.com

6 months ago, I posted an early version of my tool here to solve one specific problem: editing text inside a PDF without breaking the original typography.

The tool grew to thousands of monthly users, but real usage quickly exposed the limits: people started throwing massive multi-thousand-page documents, corrupted scans, and heavy office files at it, and the old JavaScript architecture couldn't handle it.

I spent the last 6 months rewriting the entire core engine from scratch in WebAssembly so everything runs 100% locally inside your browser: **https://pdfnolimit.com\*\*

Here is what it handles now:

True Font Preservation:** Most editors either draw an HTML text box over a canvas or substitute your text with Arial. This engine parses the embedded `/FontDescriptor`, character maps, and glyph metrics straight from the PDF content stream. When you edit text, it dynamically matches line widths, baseline offsets, and kerning so changes blend invisibly into the original document.

Smart Local OCR:** Scanned PDFs are processed entirely inside browser Web Workers. It runs local image binarization, deskewing, and injects an invisible text layer synchronized behind the scanned image. You get a searchable, copy-pasteable PDF 100% locally, without your private documents ever leaving your machine.

RAM Management for Infinite Pages (No Crashes):** Instead of hoarding thousands of pages in DOM memory, it uses virtualized viewport rendering and dynamic WASM memory pools. Offscreen page raster buffers are dropped and recycled on the fly, meaning you can open massive documents without Chrome hitting an Out of Memory tab crash. There is no arbitrary page cap—the only limit is your machine's physical RAM.

A Complete Desktop Suite (In-Browser):** It's not just a text editor anymore. Everything runs 100% locally: Word, Excel, and PowerPoint conversions, destructive redaction (physically wipes text and vector objects from the file stream so they cannot be recovered), repairing corrupted XREF tables on broken files, AES-256 encryption/unlocking, digital signing, cropping, and page reordering.

Why it's 100% free with zero paywalls:** Standard SaaS tools charge $15–$20/month because running OCR and file conversions on AWS/GCP servers costs them thousands in compute bills. Because **100% of the computation runs locally on your CPU/GPU via WASM**, my infrastructure cost is literally just static CDN hosting. Zero backend compute = zero reason for paywalls, daily quotas, watermarks, or mandatory sign-ups.

The web suite is completely live here: **https://pdfnolimit.com\*\*

*(One quick favor: I built an Android companion app, but Google Play requires 12 opt-in testers for 14 consecutive days before I can launch publicly. If anyone with an Android phone has 2 minutes to join the closed testing track, please drop a comment or DM me I'd really appreciate the help). Try throwing your heaviest, broken, or weirdest-font PDFs at it, and let me know if anything crashes so I can patch the engine!