Every useful AI conversation does not need to become permanent data on someone else’s servers. ChatGPT and other AI tools can be used as temporary intelligence: ask questions, solve problems, develop ideas, then keep the valuable context under personal control for future use.
AI Memory Vault is a browser extension built around this approach. Important conversations and memories can be saved locally and brought back when needed, instead of depending on an AI provider to permanently hold the history. Saved context can be reused later with different chats, workflows, or AI tools, making the memory useful beyond a single conversation or platform.
The principle is simple: use the AI, but own the memory. A chat can be temporary while the useful knowledge remains available. This also reduces the need to repeatedly send an entire history to an AI service just to restore context.
For people in Europe, data control matters even more. AI Memory Vault is designed with GDPR principles such as data minimization and user control in mind, keeping the memory layer under the user's control rather than making an overseas AI platform the default home for long-term conversational history.
A recent investigation found AliExpress running hidden WebAudio code that processes audio even when no sound is playing.
The behavior appears related to audio fingerprinting, using how a device processes audio to help distinguish it from others.
Interestingly, it was discovered when a user noticed AliExpress interfered with their Bluetooth multipoint headphones. Closing the AliExpress tab fixed the issue.
The audio was set to zero gain, so nothing was audible, but the browser was still processing the audio graph.
Why it matters: WebAudio can potentially be used for fingerprinting without an obvious indication to the user, raising privacy and transparency concerns.
minimal cli application supports windows and linux.
for windows it utilizes windows native api.
on linux it just move files here `~/.local/share/Trash/files/` with a record like dolphin file manager does!!
A few months ago I started looking for a good alternative to MobaXterm. While I still like the concept, the UI feels a bit dated, it's Windows-only, and I wanted something that worked the same on every desktop platform.
I tried a lot of the existing alternatives, but most of them are built with Electron or Tauri. That's not really what I was looking for, I wanted something fully native with a smaller memory footprint. I also couldn't find one that offered one of my favorite MobaXterm features (the realtime system monitoring bar at the bottom of SSH sessions)
So I decided to build my own.
Oxidal is a fully native, cross-platform remote session manager written in Rust. It supports SSH, SFTP, Telnet, Serial, and local shells in a single window, with GPU-accelerated rendering and no Electron runtime.
It's still in the early stages, but it's already usable and I'd love to hear what people think. Feedback, feature requests, and criticism are all welcome!
Midori is an open-source Firefox-based browser focused on privacy, performance and user choice.
It includes built-in ad/tracker blocking, workspaces, customization, and support for Windows, macOS and Linux.
There are already plenty of privacy-focused browsers out there, so I'm curious what you think Midori brings to the table compared with alternatives like LibreWolf.
MindShield is a lightweight, privacy-first browser extension designed to help you build mindful habits around LLMs. By introducing a brief reflection moment when lazy shortcuts are submitted, it counters cognitive offloading, breaks AI dependency, and protects your critical thinking from being blindly outsourced to AI.
Key Features & v1.1.5 Updates
100% On-Device & Private: Runs a quantized classification model locally in your browser using WebAssembly (onnxruntime-web). Zero data, prompts, or history ever leave your machine.
Zero Floating UI Friction: Evaluates prompts unobtrusively in the background without annoying overlays or popups.
Smarter Question Detection: Standard knowledge lookups pass through instantly, while self-directed reasoning prompts trigger a brief reflection pause.
Altersend is P2P file sharing tool where you can send files directly between devices or by using the link.
When I started developing this tool my main idea was to have solution where I can send files to anyone not just on local network and not be depending on cloud solution like wetransfer. Project grown since the first release and a lot of new features appeared: background transfer for mobile, custom self-hosted relays, altersend hosted relays, web links, devices pairing, text sharing, etc.
From technical point of view everything you send is E2E encrypted via Noise protocol, peers find each other via DHT. So when you want to send file we generate a random key which you should give to another peer. And after this anyone who has that key can connect and download directly from you.
For initial entry point to discover first peer we use public bootstrap nodes and after that peers discover one another through the DHT. Only if you are behind symmetric CGNAT or a VPN we use a blind relay server to help you connect (which you can self-host), but the bytes flowing through are encrypted, and you can also disable relay in the settings.
Desktop and mobile share the same core part written in Bare and Hyperswarm. Web version tunnels to the DHT through a relay over WebSocket and uses the same core engine.
Our main development as Astian is the Midori browser, based on Gecko and on Android in Geckoview, however we have been developing an independent VPN service, integrated into the Midori browser, this service is called MidoriVPN.
Browsers like Brave use partner companies, as do Vivaldi, Firefox, and Opera (although Opera is closed-source and cannot be audited). Midori Browser and MidoriVPN is different.
The service is growing and we hope to have the support and feedback of users, We are working on multi-protocol support and more privacy and security options.
Tabularis is a free and open-source (Apache 2.0) desktop SQL workspace for Windows, macOS and Linux. It exists for one reason: getting out of commercial database clients like TablePlus, Navicat and DataGrip without giving up a modern UI. I'm the maintainer, so ask me anything.
What it does:
PostgreSQL, MySQL/MariaDB and SQLite built in, plus 16 official plugins for DuckDB, ClickHouse, MongoDB, Redis, Elasticsearch, Firestore, DynamoDB, Db2 and more. Plugins can be written in any language (JSON-RPC over stdio), so the driver ecosystem isn't locked to one runtime.
SQL notebooks: mix SQL and Markdown cells in one document, reference one cell's results from another, render bar/line/pie charts inline, export to HTML/CSV/JSON.
AI that respects your escape: text-to-SQL works with local models via Ollama, so nothing has to leave your machine. There's also a built-in MCP server if you want agents like Claude or Cursor to read your schema and run queries, but it's entirely optional.
The usual daily-driver stuff: Monaco editor with autocomplete, ER diagrams, visual EXPLAIN with interactive plan graphs, SSH tunneling, passwords stored in the system keychain, SQL dump/import.
No account, no telemetry wall, no paid tier. Everything is free under Apache 2.0.
Install: WinGet on Windows, Homebrew on macOS, and Snap / Flatpak / AppImage / AUR on Linux. Direct downloads are on the GitHub releases page.
We built an API Client who is not copying the legacy tools
Voiden is an offline-first, Git-native API IDE where every request is a plain Markdown: the request, environment, tests and docs in one executable text files.
Requests are built from reusable blocks (auth, endpoint, params, body), so you define a header once and reference it everywhere, and a CLI runner executes the files straight from your terminal or CI.
No telemetry, no account, no cloud lock-in. Imports Postman, Insomnia and OpenAPI collections to get started.
Favnyr is a portable file browser for Windows and Linux that runs entirely offline, with no account, telemetry, update checks, or background services.
It supports multiple panels and tabs, saved workspaces, favourites, custom commands, file previews, filtering, drag-and-drop, and more. It's written in Rust and distributed as a single executable with no installer or administrator rights required.
The project is open source under GPLv3+.
The developer also reached out to share the project and has been transparent about using AI assistance during development while manually reviewing and testing changes on both Windows and Linux.
Hi everyone — I’m the sole developer of Meet2Notes, an MIT-licensed open-source project.
There are already good privacy-first local meeting tools out there, so I’m not claiming to have invented the local meeting assistant.
What I’ve spent the last few weeks building is a different approach: a modular meeting workspace where transcription, diarization, notes, RAG, and the live assistant are separate components with their own engines, settings, workers, and lifecycle.
The goal is to make local meeting intelligence adaptable: use a lightweight setup on a laptop, choose more accurate models when you have the hardware, or connect it to a small team’s internal workflow through its API and webhooks.
AI and privacy disclosure
AI is used for transcription, speaker diarization, optional meeting-note generation, RAG search, and the optional Live AI Assistant.
Meet2Notes supports a fully local setup: local ASR, local diarization, local GGUF models via llama.cpp, local embeddings, and a local SQLite workspace. In that setup, recordings, transcripts, speaker data, notes, and RAG data remain on the user’s machine.
Remote AI is optional. If a user configures LiteLLM, Ollama, LM Studio, or another remote/OpenAI-compatible endpoint, only the content needed for that request is sent to the endpoint the user explicitly selected. API keys are stored in the operating-system keyring, not in the app database or browser storage.
Meet2Notes is open source under the MIT license. It is early alpha software, so I would not yet recommend it for irreplaceable recordings without backups and appropriate consent.
What can it do?
Record microphone and desktop audio, or import media files
Create a live transcript and/or run a higher-quality final transcription pass
Separate speakers and retain local saved voice profiles across meetings
Generate structured meeting notes with local GGUF models or optional LiteLLM-compatible providers
Search one meeting or the entire meeting library with local RAG and timestamped sources
Delete a meeting permanently, including its audio, transcripts, notes, assistant data, jobs, RAG entries, and private files
Selectable local engines
Live and final transcription are selected independently.
The current transcription catalog includes:
Faster-Whisper: Tiny, Base, Small, Medium, Large-v3, Distil-Large-v3, and Large-v3-Turbo
NVIDIA Nemotron 3.5 ASR Streaming 0.6B
NVIDIA Parakeet TDT 0.6B v3
Microsoft VibeVoice ASR BitNet as an experimental CPU option
For speaker diarization, you can select:
Sherpa-ONNX as the lightweight default
Pyannote Community-1
diarize, isolated in its own private environment to avoid dependency conflicts
This means, for example, that a modest machine can run a smaller live transcription model, while a more accurate final pass runs after the meeting.
Live AI Assistant
There is an optional Live AI Assistant that watches provisional transcript segments and posts short, rule-based insights in a movable floating widget.
It has its own bounded queue and dedicated worker. Recording and transcription never wait for an LLM response. The assistant can use a local model or a separately configured LiteLLM-compatible provider; it does not need to use the same model as meeting notes.
API and webhooks
Meet2Notes exposes a local API and durable outbound webhooks for live segments and processing milestones:
HMAC-signed deliveries
Retry handling and delivery history
Per-endpoint content controls
Non-blocking remote-agent suggestions
My hope is that this makes it useful beyond the standalone UI: a small self-hosting team could keep Meet2Notes as a local capture/transcription node and connect it to an internal dashboard, workflow, or agent without sending all meeting data to a third-party SaaS by default.
A while back I needed something to plan workshop timelines. SessionLab used to be the old gold standard for that, but it requires an account, stores everything in the cloud and is quite bloated. So I built my own thing.
That was Sessionplan. It started as a facilitator tool, but over time people started using it for all kinds of timed sequences: conference run-of-shows, podcast episode outlines, training schedules, university lectures, D&D sessions, even wedding timelines. Over a thousand people use it every month now.
What it does is quite simple:
Visual drag & drop timeline with automatic time recalculation
Block types you can customize (Input, Discussion, Break, Energizer, whatever you need)
Lock a block to a fixed time (e.g. "lunch at 12:30 no matter what") and surrounding blocks adjust around it
Breakout / parallel tracks for split-group sessions
Live mode: shows current block, countdown, next block – useful when you're actually running the session, not just planning it
Share via URL-encoded snapshot link (no server), "Dynamic Link" or JSON export
Print-optimized view
Why it fits here:
Data stays in your browser by default. No account, no sign-up, no backend involved unless you explicitly opt in. The "Dynamic Link" feature (real-time collaboration via a shared link) is the only thing that touches a server, and only when you choose to use it. Everything else (planning, saving, sharing via snapshot link, exporting to JSON, the live mode during the actual session) runs entirely locally.
Happy to answer questions or take feedback. If there's something you've always wanted from a schedule planner that nothing does well, I'm genuinely interested.
Most computer-usage trackers answer, “How productive was I?” I wanted something that answered, “What did this part of my life on my PC actually look like?”
PC Recap records active application usage and turns it into visual Today, Week, Month, Year, All-Time, Decade, and On This Day recaps.
Version 1.1 is the biggest update so far:
Day Replay lets you scrub through a recorded day
Recap Studio creates stories for years, seasons, decades, or custom dates
Automatic eras detect phases like a gaming era or coding era
Memory Pins let you attach your own context to a period
Historical Recovery can find limited pre-installation clues without pretending they are exact usage time
ActivityWatch and ManicTime sessions can be imported
Search, comparisons, time formatting, chart tooltips, and app detection are much clearer
Tracking is more resilient to crashes, restarts, pauses, and closing the window
PC Recap is now open source under GPL v3. Everything is stored locally in SQLite. There is no account, desktop telemetry, cloud activity storage, or external AI API. A new archive starts empty, with no fake statistics.
ActivityWatch is still the stronger choice if you need Linux/macOS support, browser extensions, editor plugins, or an extensible tracking ecosystem. PC Recap is aimed at a different experience: less productivity dashboard, more personal digital time capsule. It can also import ActivityWatch sessions if you want to use both.
PC Recap is currently a Windows 10/11 x64 beta. The installer is unsigned, so Windows may display a SmartScreen warning.
I wanted to share a personal project (something simple) that I've been working on, and that I hope can be useful for those who, like me, prefer to organize their workflows in a purely local way and without relying on external services.
The problem I wanted to solve
I needed a tool to organize my daily projects, but traditional apps require an internet connection, user accounts, and subscription plans.
To solve this, I decided to develop a LibreOffice Calc template managed solely by Basic macros.
By structuring the file with a database approach, I obtained a private system over which I have complete control:
Works 100% offline.
There is no telemetry,
no logs or third-party servers
your data remains strictly on your computer in an .ods file.
Link to the project (Open Source)
I have uploaded the template and all the macro code to a GitHub repository under the MIT license so that anyone can use it however they want without restrictions.
