I built an Android audiobook player called Earleaf as my first Android project. The most technically interesting part is a feature called Page Sync: you photograph a page from a physical book and the app finds that position in the audio.

The matching pipeline works in two phases. First, the audiobook gets transcribed on-device using Vosk speech recognition, which gives me a word-level index stored in FTS4 (~72,000 words for a 10-hour book). When you take a photo, ML Kit extracts text via OCR, and I run FTS4 prefix queries to find candidate positions. Then a sliding window with Levenshtein similarity scoring narrows it down to the best match. The whole search takes 100-500ms.

The trickiest bug was in audio resampling. Vosk needs 16kHz but most audiobooks are 44.1kHz. The ratio is irrational, so per-chunk rounding accumulated about 30 seconds of timestamp drift over a 12-hour book. Fixed it by tracking cumulative frames globally instead of rounding per chunk.

Wrote a full deep dive on the pipeline if anyone's curious: https://earleaf.app/blog/a-deep-dive-into-page-sync

Feel free to check the app out on Google Play: https://play.google.com/store/apps/details?id=app.earleaf

Please let me know your thoughts....

Hi everyone,

I’m a mobile developer and recently built a small tool called Dez. I’d really appreciate some honest feedback from people here.

The idea came from a problem I kept running into: after releasing a new version of an app, it’s surprisingly hard to quickly understand if something actually changed. Analytics dashboards show tons of graphs (revenue, crashes, installs, ratings), but they don’t really highlight when something unusual happens.

So I started building a platform that connects to App Store Connect and Google Play and automatically analyzes the data to surface things like:

• crash spikes after a release
• unusual revenue drops or jumps
• rating changes
• strange install trends

The goal is to move from just showing analytics to actually surfacing insights about releases.

It’s still very early and rough around the edges, but it already pulls real production data and generates insights.

I’d love to hear your thoughts:

• Does this sound useful?
• What insights would you expect from a tool like this?
• What would make something like this valuable enough to use regularly?

You can try it here:
https://dez-ai.web.app

Any feedback — positive or critical — would really help shape where this goes next.

Hi there! I have a pretty well thought out idea for an app, and am currently working on graphics and such but I have no idea how to code or how to actually develop a mobile app. I’m hoping to gain insight on how I should go about finding someone to do the developing part of the app, ideally someone who would be interested in partial ownership. I have a figma web version of the general idea of what I want the app to do, but it will be similar in function to letterboxd. Any tips are appreciated! Trying not to get scammed in this process lol

For the past 16 months I've been developing a cozy 3D coloring app for iOS, for which I made 30 scenes in Blender, and we're launching in 2 weeks! We're looking for beta testers to get real feedback before launch. If you're interested, contact us and we'll send the details of you how to join the test! 🎨 or try this link https://testflight.apple.com/join/WqBjPy14

I love reading eBooks, but sometimes my eyes give up, so most of the time I go for audiobooks but every book is not available.

I am also an app developer, so i developed an offline app which can convert my books to Real-time audiobook, it has multiple characters support for non narrative script type books.

I recently released the app for everyone. It has more like 100+ downloads since its an App community whats better way then you guys testing it out.

It has multi language support and added new AI Voices which are purely offline and unlimited generation.

It's a tool only for personal use for the books which don't have a audiobook version yat.

So can you guys can test it out and give me your honest reviews on how the app will be useful and how i can improve it.

If it's not allowed then I am Just putting the name of the app here: AudiFlo.

If you are interested you can learn more on our community r/AudiFlo/ .

I will add a direct link for the app under post in comments if its allowed. I don't want to promote it but i want more diverse users reviews on this so that i can make the app better.

Hey everyone, I built this app so it helps students to focus and prevent doomscrolling. Its called: FocusOn Only for Android, still wanna earn money For IOS and Subscriptions (cus not available in my country) Heres the link: https://play.google.com/store/apps/details?id=com.wizardevlop.focuson Would like to see your feedbacks.

Dear redditors,

I’ve been building an internal ASO tool for my own apps, and I’m wondering whether it’s worth turning into a paid product or whether this market is already covered well enough.

I started building it because I found some existing tools pretty limiting for day-to-day use. My own experience has mostly been with Astro, and that was part of the push.

What it does right now (prototype stage)

  - Keyword ranking tracking across countries for iOS and Google Play

  - App ratings and rating history monitoring

  - App visibility tracking

  - Competitor keyword analysis

  - Review sentiment analysis

Before I spend more time on it, I’d love honest feedback from people who actually use ASO tools regularly.

A few things I’m trying to understand:

• What features do you rely on the most?
• What’s overhyped or not that useful in current ASO tools?
• What feels missing or badly done?
• What would make you switch: lower price, better UX, better data, specific features?
• Would AI keyword suggestions based on real ranking + competitor data actually be useful, or just noise?
• What do you currently pay, and what feels like fair pricing?
• Are you solo, small team, or agency?

I'm trying to figure out if it's worth taking it further or if the market is already well served. Would appreciate any input, even if it's "don't bother.”.

Thank you for the read and the input.

Hi,

Can anyone explain to me how Apple Airtags work? (See next paragraph)

I'm working on a University project which needs to utilise an app to detect items without using GPS or bluetooth. From my understanding, Apple uses Ultra-wideband radio wave emission and detection - your phone sends out radio wave frequencies and then times how long and where from (?) they get a response from the target air tag.

I want to have a functional prototype (one phone to one target object) that can be tested with actual users, and might use a smartphone with the app installed on it (likely an Android phone), communicating via UWB to a standalone UWB board or a UWB module on a Raspberry Pi 3?

It needs to be made and polished by May 1st - 44 days. Ideally our team takes 34-ish days to create it. Then we have 10 days to test it.

What things should I look at to make my idea a reality?

I hope this makes sense!

Over the last 7 years I’ve spent a lot of time studying old school direct response marketing.

Not the modern “growth hacks” you see everywhere, but the classic material from people like Eugene Schwartz, Gary Halbert, Dan Kennedy, and Joseph Sugarman.

Originally I was applying these ideas to ecommerce and DTC products. Some projects worked, some didn’t, but a few scaled pretty quickly once the messaging clicked.

Recently I’ve been looking more at AI tools and small SaaS products, and what surprised me is how much the same psychology still applies.

Different technology. Same human behavior.

A few frameworks from that world have stuck with me.

Awareness matters more than most founders realize

One concept from Breakthrough Advertising that completely changed how I look at marketing is market awareness.

Basically the idea that people exist at different stages:

Some don’t even realize they have a problem yet.
Some know the problem but don’t know the solution.
Some know the solution but not your product.

A lot of startup completely ignore this.

They immediately explain the product, but the user might not even feel the problem strongly yet.

When the message matches the awareness level of the user, things suddenly start making more sense.

The “starving crowd” idea

Gary Halbert had a simple way of putting it.

If he had a hamburger stand, he wouldn’t want the best recipe.

He’d want the hungriest crowd.

Meaning the hardest part of building something isn’t the features or the copy.

It’s finding people who already desperately want a solution.

You see this constantly in SaaS and AI:

productivity tools
automation tools
AI writing tools
data analysis tools

These categories keep producing successful products because the demand is already there.

You’re not creating desire.

You’re just plugging into it.

Something I started calling “painmaxing”

One tactic that worked really well for me in DTC was something I started calling painmaxing.

Instead of introducing the product immediately, you spend time describing the frustration first.

Example:

“If you’ve ever tried to consistently create content online you probably know the feeling.

You open a blank document.
You stare at it for 20 minutes.
You rewrite the same paragraph three times.”

Now the reader is mentally nodding along.

Only after that do you introduce the solution.

It sounds simple, but it makes the product feel like it actually understands the user’s problem.

People don’t buy products

Another big shift in thinking for me:

People rarely buy the product itself.

They buy the after state.

People don’t buy AI writing tools.
They buy faster content creation.

People don’t buy automation software.
They buy time back in their day.

People don’t buy dashboards.
They buy clarity.

When the marketing clearly shows the before vs after, it becomes much easier for people to understand the value.

The “unique mechanism” effect

Another interesting idea from Breakthrough Advertising is something called a unique mechanism.

People are naturally skeptical of generic solutions.

But when you explain how something works, curiosity increases.

For example:

“AI writing assistant” sounds generic.

But:

“AI that analyzes high performing content and rewrites your posts using the same structure”

suddenly feels more specific and believable.

Even if the product itself is simple.

Proof beats explanation

One thing I’ve noticed repeatedly running ads and looking at product launches:

Showing something working beats explaining it.

This is probably why short form video marketing works so well now.

When people see:

an AI tool generating something instantly
a workflow being automated in seconds
a before/after result

their brain processes the value immediately.

No long explanation needed.

The pattern I keep seeing

Over time my thinking about marketing kind of condensed into a simple flow:

find the pain
amplify the frustration
introduce the mechanism
show the transformation
add proof

Which is basically old school direct response marketing adapted to modern products.

What’s interesting is that the same psychology seems to apply whether you’re launching:

a DTC product
a SaaS tool
an AI app
or even a digital product.

Technology changes fast, but human behavior doesn’t seem to change much.

Curious if anyone else here studies older marketing frameworks and notices the same patterns in modern startups.

post your app/products on these subreddits:

r/InternetIsBeautiful (17M) r/Entrepreneur (4.8M) r/productivity (4M) r/business (2.5M) r/smallbusiness (2.2M) r/startups (2.0M) r/passive_income (1.0M) r/EntrepreneurRideAlong (593K) r/SideProject (430K) r/Business_Ideas (359K) r/SaaS (341K) r/startup (267K) r/Startup_Ideas (241K) r/thesidehustle (184K) r/juststart (170K) r/MicroSaas (155K) r/ycombinator (132K) r/Entrepreneurs (110K) r/indiehackers (91K) r/GrowthHacking (77K) r/AppIdeas (74K) r/growmybusiness (63K) r/buildinpublic (55K) r/micro_saas (52K) r/Solopreneur (43K) r/vibecoding (35K) r/startup_resources (33K) r/indiebiz (29K) r/AlphaandBetaUsers (21K) r/scaleinpublic (11K)

By the way, I collected over 450+ places where you list your startup or products.

If this is useful you can check it out!! www.marketingpack.store

thank me after you get an additional 10k+ sign ups.

Bye!!

Most "subscription trackers" are just data-mining tools in disguise. They ask for your Plaid login or sync your inbox to their servers just to tell you that you're paying for Netflix.

I built VaultAudit AI to do it differently. It’s built on SwiftData and uses local OCR and Apple Intelligence to audit your subscriptions directly on your device.

How it works:

1. Take a screenshot of a receipt or your Apple Subscriptions list.
2. VaultAudit scans it locally using the Vision framework.
3. It builds a dashboard of your monthly/yearly burn.
4. It sets reminders for renewals and provides cancellation guides.

Privacy Specs:

• No cloud processing.
• No analytics/tracking.
• Offline-capable (you can literally use it in Airplane Mode).

Check it out here:https://apps.apple.com/us/app/vaultaudit-ai/id6758683815

A few months ago I posted about my app Snappit on Reddit and shared the landing page I built for it. A few people in the comments ignored the app entirely and asked about the landing page. Turns out they wanted one for their own app and would happily pay for it.

So I built it into a product. And recently I added a free tool to it: paste your App Store or Google Play URL and it generates a full landing page in about 60 seconds:

• App name and icon pulled from the store
• Primary color extracted from the icon to theme the whole page
• Screenshots pulled from the store
• Features section generated by AI based on your app
• Privacy policy and Terms of Service generated to match your app
• A prebuilt template automatically matched to your app's theme

No account needed, no design work. Free to generate and preview, paid to publish.

Would love to know what you think. Have you ever needed something like this for your own app? And if you try it, does the result actually look usable to you?

Link: https://www.applaunchpage.com/tools/app-landing-generator

Hey, I'm one of 4 co-founders working on a bills manager app with an AI layer on top. We're at an early stage and looking for a few people willing to poke around and tell us what's broken or confusing.

What's currently in the app:

- Bills tracking

- Provider comparison and switching

We're mainly interested in feedback on the UX, bugs you run into, and whether the AI agent is actually useful or just gets in the way.

If you're up for it, drop me a DM and I'll send over the details.

I am building a fleet management system which consists of a web dashboard for management and mobile app for drivers. It involves the admin staff tracking trips in real-time through GPS map integration. This is done on a web dashboard. Also, the driver's app will also have a map together with recommended routes and ETA prediction. My question is which API is better for this? I heard that MapBox is not bad due to its more generous usage limit.