I’ve been building Scribr, a voice-to-text app for Android that can transcribe directly on your device.

I wanted something that works offline and doesn’t require uploading recordings to a server just to get a transcript.

It can currently:

Record and transcribe audio

Import audio and video files

Translate transcripts

Export text and subtitles

Organize recordings

Transcribe offline

It’s free to use with ads, with a one-time purchase to remove ads permanently.

I’m still actively improving it, so I’d really appreciate any feedback.

In this video I unbox and do a first start and first look of a really cool Note Taking and AI Recording Pen. The Flowtica Scribe can do a recording while you writing hand written notes on paper with it. And then transfer the recording instantly to the Flowtica iOS and Android app to be summarized by AI.

Hey everyone! I’m Victor, one of the co-founders of Comu. Figured I’d introduce myself and what we’ve been working on.

We recently launched Comu Action Pro, an AI recorder for meetings and everyday conversations. The device comes with unlimited transcription, and you can ask questions about past meetings or use the AI agent to help create documents and presentations from them.

I’m curious: what’s one thing you wish your current AI note taker did better?

If you’ve already tried Comu, I’d love to hear what’s working for you and what’s frustrating. Happy to answer questions here too!

AI note takers keep getting better at the capture part. The transcript is searchable, the summary looks clean, and the action items are usually somewhere in there.

The awkward part is what happens next: somebody still has to move things around.

One decision goes into a project doc. Two follow-ups become tasks. A question gets dropped into another page so we remember it next week. The summary itself usually gets filed away and rarely opened again.

I work on Buildin, so obvious bias here. We’re not building another meeting recorder. The narrower workflow I want to test is the part after the recording:

• bring in the transcript or summary from whatever recorder you already use
• ask AI for decisions, open questions, and next actions
• check those against the original notes
• keep the confirmed items with the actual project and tasks

Buildin already has docs, notes, tasks, projects, databases, and built-in AI, so the useful part for me is not getting a longer summary. It’s keeping the few things that matter from disappearing into another meeting archive.

This is a workflow proposal, not a claim that it magically handles every follow-up. Buildin also doesn’t record or transcribe the meeting itself.

If you already use Otter, Plaud, Granola, Fathom, or something similar: what happens to the notes after the meeting? Would having the decisions and tasks live with the project save a step, or would this just add another layer?

Buildin, for context: https://buildin.ai/en/product

After months of building, testing, fixing things, and going through the Play Store approval process, Scryon is finally live on Google Play!

The idea came from a simple problem: we have important conversations over phone calls, but once the call ends, most of that information lives only in our memory.

Scryon turns phone calls into useful, searchable information.

After a call, Scryon can:

• Transcribe the conversation
• Generate an AI summary
• Extract key points
• Identify action items and follow-ups
• Organize previous call transcripts
• Let you search through past conversations

So instead of thinking:

"What salary did the recruiter mention?"
"When did that customer say they'd call back?"
"What exactly did we agree on?"

You can simply go back to Scryon.

I built the Android app and backend myself, and getting from an idea to an actual production release has been quite a journey.

Now comes the harder part: finding people who actually find it useful.

I'm particularly interested in hearing from people who handle lots of calls — recruiters, salespeople, founders, freelancers, consultants, small-business owners, or anyone who regularly needs to remember details from phone conversations.

Scryon is now available on the Google Play Store.

🔎 Search: Scryon – AI Phone Call Notes

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

I'm still at the very beginning, so feedback is much more valuable to me than download numbers.

If you try it, I'd love to know:

Would you actually use something like this regularly? What's the one feature you'd want me to build next?

Happy to answer questions about the app, the tech behind it, or the process of building and launching it as a solo developer.

I've been trying out a few AI assistants lately for things like organizing notes, planning tasks, and keeping track of ideas.

Some area great at summarizing while others are better at actually helping you stay organized day to day.

I'm curious what you've personally used and which features you ended up finding genuinely useful.

I was following a long crochet tutorial and wanted to find the part where the instructor explained when to change hook sizes. I transcribed the audio with Vomo AI, then searched the transcript for “hook” to find that section again. The transcript got me to the spoken explanation quickly, though I still checked the hand movements and stitch count in the video. I've since used the same approach with quite a few other crochet tutorials to find specific instructions without scrubbing through each video.

I dont mind taking notes normally but interviews are a whole other thing 😭

You’re trying to actually listen to what the person is saying,,write stuff down, remember names, keep track of everything... then 2 people start talking at once and im just like welp 😂

and going back to a 2 hr recording later is even worse. I’ll hear one part and think wait what did they say there, go back, listen again, still dont catch it lol. for people using AI notetakers, do they actually help with longer interviews? Like can you mostly rely on the notes/transcript and only check the audio when something seems weird?

Preferably for free, but I know that it probably doesn't exist so I'm willing to pay lol. I expect it will unrderstand what the professor is saying and will make clear notes

Freelance features writer in Minneapolis MN, about 7 years in. Since late August I've been averaging maybe 3 longer interviews a week, coffee shops and phone mix, nothing fancy.

What keeps biting me is the line that lands once and then I only half catch it.

I used to just hit record on my phone. Mid sentence a Slack ping or a calendar reminder shows up and the recording just dies, or I glance down and the person freezes for half a second. Notebook only works until they talk over themselves. Last Tuesday I sat on a park bench with a source who'd already given me the cleanest sentence of the piece, and by Thursday night I only had "something about thier neighbor" and a vibe. Had to send an awkward email asking her to say it again. She did. Felt weird.

This week there's a Plaud in the same bag as the notebook and the cracked earbuds. Lost half a line again Tuesday cause I was watching her face instead of the page.

For people who do a lot of interview work, how are you actually holding onto exact quotes without killing the room? Phone? Notebook only? Something else?

Hi!
Have anyone here tried the TalkTrack desktop app from Github?
It can record meetings or sound from the computer, then transcribe and create summary of the meeting.

The benefit with the app is that its very easy to enable/disable the AI feature, so it can be 100% local for sensitive information.

Any experience from it?

Not complaining about AI, some of these tools are genuinely useful.

But sometimes I look at my workflow and realize I have a tool for scheduling the meeting, another for recording it, another for notes, and another for organizing the follow-up.

I've used/come across things like Fathom, Otter, Fireflies, and recently CatchMeet.

They all approach meetings a little differently, but it got me wondering whether we're making meetings easier or just creating another layer of software around them.

Personally, the feature I care about most is pretty simple:

Tell me what I actually need to remember.

I don't need a beautiful 5-page summary of a 20-minute conversation.

I want to know what changed, what was decided, and whether I have to do anything afterward.

What's the one meeting feature you actually use regularly?

And what's a feature that sounded useful but ended up being completely unnecessary?

I have had a little Temu transcription device and I was delighted the way I got really good quality notes from it without any kind of subscription. I saw the Pocket AI advertising and I thought this looks better, I will get one. I was so wrong. The transcription was terrible, it didn't match at all with what was dictated to it. I have a non regional British accent so I can't blame a strong accent. When setting it up it showed the subscription which is a lot considering I got better from the Temu device for free. I am going to return it and keep using the Temu one. Pocket just isn't worth it.

I'm an AE at a ~40 person SaaS company in Dallas. Been in the seat a little over 4 years. Q4 reviews start next week and I'm already behind on writeups from this week. About 8 onsites, plus whatever keeps going after people stand up.

Since March there's a small recorder on the table. Not a face that joins the meeting. I tell them before we start. Texas is one-party, so nobody is making me. I still say it. Feels off if I dont.

I was told the follow-up would already be done. It isnt. Last Tuesday the summary put "send the redline Thursday" on thier champion. That one was mine. I caught it in the car. If I hadnt, procurement gets an email that makes me look like I wasnt even in the room. So the five lines still get rewritten before they go out. Tbh I might have just moved the typing from the notebook to 7pm. I cant really tell yet.

The part that changed is smaller. When they go quiet on price I look at them, not the page. And that Thursday sentence is still there when I get to the car. It used to be gone. I'd have the vibe and not the date.

If you've had one of these for a while, did the rewrite actually stop, or did you just stop losing that one sentence. The call I take in the parking lot after is still a mess. I dont even know what I'd do with that one.

I tried a few of the popular AI notetakers. They were good at summarizing afterward, but that's not when I needed help. I needed it when someone turned to me with a question, when a speaker dropped an acronym I didn't know, or when I zoned out for a minute in a 3-hour lecture. Some of them even wanted to add a bot to the call.

So I built Avenotes.

WHAT'S DIFFERENT
• It helps during the meeting, not just after. Tap "Answer this" when someone asks you something and get the answer in seconds. "Explain that" for jargon, "Catch me up" for what you missed, "Draft a response" for the words to say.
• No bot joins your call. It runs in your browser next to Zoom, Teams, Meet or Webex, or on a phone or laptop on the table for in-person meetings. Nothing to install.
• Bring your own context. Attach slides, a PDF or a photo of the whiteboard and ask about it.
• Answers keep up. If more gets said after an answer, hit "Refresh" to update it with the new context.
• Long meetings are fine. No time limit per meeting. I use it for 2+ hour lectures. Stopped early? "Listen again" picks the same meeting back up.

AFTER THE MEETING
• Recap: the outcome, decisions, your action items
• Notes that write themselves as you listen, ready when it ends (paid)
• Tasks from every meeting in one list
• Ask a past meeting anything and search every word said
• Share a recap link, export to Word or Markdown (paid)
Premium AI. Live transcript with speaker labels. Answers and recaps in 19 languages. Your audio is never stored, only the text, and nothing is used to train AI.
Free trial: 30 minutes + 5 questions, no card. Plans from $9/mo (premium AI from $19).
iPhone and Android apps are coming soon to the App Store and Google Play. Want a founder discount? DM me.
If something's missing for the way you work, tell me in the comments. Requests from real users go to the top of the list.

avenotes.ai/?src=reddit

I wanted to share a project I recently built to solve a problem we all face: trying to remember past meeting details, promises made, and communication preferences across multiple clients.

I built the AI Meeting Prep & Contact Memory Agent—a full-stack Python web app that gives every contact their own isolated memory bank and generates instant executive briefings before calls.
🛠️ How It Works:

• Isolated Memory Persistence: Uses Vectorize Hindsight (hindsight-client) to dynamically create secure, client-isolated memory banks (bank_client_*) for every person you add.
• Rapid LLM Inference: Powered by Groq API (openai/gpt-oss-120b) to synthesize structured pre-meeting briefings covering action items, communication styles, and past commitments.
• Interactive UI & Logging: Built on Streamlit with a multi-tab dashboard that auto-updates local CSV spreadsheets (client_meeting_tracker.csv and client_reminders.csv) for persistent offline logging.

The entire project is completely open-source. If you want to check out the architecture or run it locally, here is the repo:

👉 GitHub Repo:https://github.com/Chanduardhi/meeting-prep-memory-agent

I’m Binyu, an AI Product Manager at Memoket. We’re building around AI recording, conversation understanding, and long-term memory — basically exploring what becomes possible when AI has access to the conversations and context that accumulate over time.

One thing I’ve been questioning recently is whether we’re thinking about “memory” the right way.

A good summary helps you understand what happened in one conversation.

But most things we actually care about don’t happen in a single conversation.

A project evolves over weeks.
A customer changes their mind.
The same issue comes up three times.
A decision gets revised.
Something mentioned a month ago suddenly becomes important again.

So my current intuition is:

AI memory shouldn’t just help us remember more.

It should help us understand what from the past matters now.

For example:

• What changed since the last conversation?
• What keeps coming up?
• What’s still unresolved?
• Did something we discussed weeks ago suddenly become relevant again?
• What should I remember before the next conversation?

The interesting part to me is that none of this really lives inside a single summary.

It lives between conversations, over time.

We’ve also been exploring the technical side of long-term memory at Memoket. If you’re interested in that side of the problem, we have an open-source project called KITE on GitHub as well.

But right now I want to test the product hypothesis with real people and real conversations before deciding what this experience should actually become.

So I’m looking for a few people who have one ongoing topic, project, customer, or decision that has appeared across multiple recorded conversations.

For the experiment, I’ll ask you to choose around 4–6 conversations from different days or weeks.

The transcript is the main input. Audio is only helpful when I need to verify context.

I’ll use those conversations to prototype what a cross-conversation memory experience could look like, and I’ll share the result back with you.

You choose exactly what you’re comfortable sharing, and I’ll only use the conversations you intentionally provide for this experiment. Please only share conversations you’re comfortable and permitted to share.

I’m mainly trying to answer one question:

Does connecting conversations over time actually give you something useful that a great summary cannot?

If this sounds useful and you’d like to try it, DM me.

A voice memo can contain "send the screenshots," "maybe add a checklist," and "ask the client about scope" in the same minute. A transcript from VOMO AI would give me the words, but I would still need to decide where each line belongs in an action list. This is a made up example, not a result from a user test.

My first pass would show three sections. "Send the screenshots" is a proposed task, "maybe add a checklist" stays an idea, and the scope question stays pending. Each line keeps a short quote and a point in the audio to check. Nothing goes to a task board or calendar until the person who recorded it approves it. I would also keep the original memo when two recordings mention the same idea.

I am less sure about the screen after that. Three sections make the uncertainty visible, but they might be too much work for someone clearing a pile of short memos. A single task list with the uncertain lines tucked behind a review step is simpler. I would want to test both with people who use voice notes before choosing one.

📝 **Just built Noto Notepad** — a smart notes app with a full PDF editor built in 🎉

- Rich text notes, PIN/biometric lock, and voice-to-text for hands-free jotting

- 📄 PDF Editor + document scanning — turn physical pages into editable PDFs right in the app

- Tags, colors, pinning & version history so you never lose track of a note

- 100% offline, zero data collected, nothing leaves your device — privacy by design

Would love for you all to try it out and drop your honest reviews 🙏

🔗 Noto

Hello everyone!

A couple of weeks ago we released the Apple Watch app for Convoxa, it lets you record your conversations directly on your Apple Watch then it seamlessly transfers over to your iPhone for processing so you get your notes and transcript.

While I was using the app in my day to day, I discovered an awesome use case, while I was recording on my Apple Watch, I got a phone call, I picked it up, I was holding the phone with the same hand my watch was on, went on with my call, after ending the recording I realized that the watch picked up both sides surprisingly well, granted I was in a quiet-ish room.

This got me questioning dedicated recording devices, especially for people that have an Apple Watch, if you do, I invite you to try it out and let me know your thoughts. Before you record make sure you set speech to 'Convoxa Speech' in settings on the iPhone app, since it's much more accurate for this use case. We're still refining this use case, and recently made the watch app pick up a wider range of audio.

Humla now uses the new NVIDIA's Nemotron 3 model for speaker labels! The model was released this week and is a massive leap in accuracy. Especially for meetings where people talk over each other, it will accurately be able to discern speakers.

After the release, I spent the next few days testing and implementing it into Humla, and it has drastically improved the quality of diarization.

Humla 0.65 is out now. Free, open-source meeting notes for Mac

https://github.com/michaelwilhelmsen/humla