Local AI Weekly #2: Agents Everywhere

Welcome back to Local AI Weekly. I promised a weekly, and then took a month to send the second one. So let's call the first one the pilot episode. From here, the show will run weekly 🤘

This issue leans heavily toward agents, because that's where most of the interesting local AI tooling is landing right now.

Before we see all that, let me thank Atomic Chat, who is supporting this edition of Local AI Weekly.

SPONSORED

Atomic Chat lets you run open-source LLMs privately on your own device, fully offline. It has Turboquant built-in providing faster local inference with longer context windows. Which means you can run bigger models smoothly, right on your device.

Explore Atomic Chat

🧪 On my bench: Unsloth

I downloaded Unsloth this week. It's an open source framework for fine-tuning and running open models faster and on far less VRAM than the usual setup. It's probably best known for its Dynamic GGUF quants, the ones that let people run 27B-class models in around 17GB of RAM, with 1-bit builds that squeeze onto 8GB.

Yeah...that's the kind of claim I don't want to repeat until I've tested it myself. So consider this a heads-up, not a review or recommendation. I'll try it on my ZimaCube (with Nvidia RTX Ada 2000) and give you the full verdict in a coming issue.

🔍 Discover AI tools

Three of this week's finds are about making your local agents "behave". tehy are smart, but they have to be accountable, too. All of these tools are open source.

The first is agent-inspect, a local-first debugger for TypeScript AI agents. It turns an agent run into a readable execution tree, so you can see every tool call, model call, and the exact point where things went wrong. It can also fail a CI check when the agent takes the wrong path, and bundle up a redacted trace to share with someone else.

Next is AutoMem, a persistent memory layer that plugs into agents over MCP. Most agents start every session from zero. AutoMem stores what matters in a graph for relationships and a vector index for meaning, so recall gives you the answer and the thread it belongs to. You can run the whole thing locally in Docker, offline, with your data staying on your machine.

The third is BrowserSkill from Tencent. It lets an AI agent use your real, already logged-in broswer instead of a fresh sandbox with throwaway accounts. The interesting part is that it runs tasks in a separate, visible Agent Window and only borrows a tab you have open when it explicitly asks, so you can keep working while it does. When it hits a captcha or a login, it hands control back to you and picks up after. Agents can still not tick all the traffic lights, it seems 😉

🖥 Which model can your hardware actually run?

This is the question I get asked the most. You see a model you want to try, but you have no idea if it can run on your system. Downloading and trying all of them is a waste of time and bandwidth.

llmfit helps you there. It's a terminal tool that detects your CPU, RAM, and GPU, then ranks open models by how well they'll actually run on your box, scoring them on size, speed, quality, and context. If you have Ollama running, you can even pull a model straight from its interface. It is open source and written in Rust (if that matters to you).

🧩 Open WebUI goes mainstream

A quick sign of the times. Open WebUI has become so popular that managed hosting providers are now offering it as a one-click service. PikaPods, for instance, now runs it for you.

Just so you know, I work with PikaPods as its growth consultant, so take the mention for what it is. But the point is that self-hosted AI front-ends have moved from hobbyists' Raspberry Pi to something people want running full time without managing a server.

🎙 Voice transcription lands on Linux

Back in issue #1 I said voice AI is shaping up to be the next big thing. LM Studio's Bionic release, v1.1.3 proves my point, as it now brings voice transcription to Linux, including on machines with NVIDIA GPUs.

LM Studio is free but closed source, so keep that in mind. If you are on Linux, you will find that the Bionic AppImage is about 1 GB. That's the biggest AppImage I ever downloaded.

📡 Open Model News

The open model space has kept up the pace since last time. Three releases stand out, and all three are MoE models, which is now clearly the direction the open world is heading.

Qwen3.8-Flash-Next from Alibaba's Qwen team. It's a 125B mixture-of-experts model that only activates 6B parameters per token, and it's an early preview of the architecture behind the upcoming Qwen4 family. Needs serious hardware power, though.

DeepSeek V4.1 Flash is here, too. On paper it's a huge 552B MoE, but it activates only 8B parameters on input and 16B on output, with a new architecture built around an aggressively compressed KV cache, roughly 890 bytes per token. Waiting for community quantization on this one.

Those two are heavyweight so the next one is "relatively affordable" by homelabbers. Ornith-1.5 from DeepReinforce comes in three sizes: a 397B MoE flagship, a 35B MoE that activates just 3B per token and runs on a single 24GB card, and a 9B dense model with a quantized build small enough for a phone. It's trained with a self-improvement loop, where the model writes its own tasks and grades its own attempts.

👀 Big Tech Watch

Two things worth your attention.

First, OpenRouter is being acquired by Stripe. OpenRouter is the big model-routing gateway, moving over 10 trillion tokens a day across 400 or so models. It says the product, name, and neutral routing won't change. Worth watching, because a lot of the local and open tooling world leans on that gateway staying neutral.

Second, the industry had a rare moment of agreement. Anthropic's Dario Amodei published an essay called "We Must Pace the Frontier," arguing that AI labs should deliberately slow down how fast they push model capabilities.

Within a couple of days, Sam Altman, Elon Musk, and Google DeepMind's Demis Hassabis all said they agreed with the core idea. The notable holdouts weren't the labs at all. The US President Trump rejected the idea flatly, saying "whoever wins AI wins."

If the frontier slows and open weights keep improving, that's a good thing for us Local AI enthusiasts.

🗂 AI Jargon: Harness

You'll have noticed the word "harness" turning up everywhere lately. Here's what it means.

Think of the LLM as the brain and the harness as the actual body. A model on its own is just a brain sitting in a jar. It reads text and predicts text. A harness is what turns it into an agent that can do things. The harness runs the loop i.e. it sends your request to the model, reads back the tool calls the model wants to make, actually runs those tools, feeds the results back in, and repeats until the job is done. It also manages memory, context, and what the model is and isn't allowed to touch.

The reason everyone is building their own harness is that the model has become the easy part. The value now sits in the harness you wrap around it: your data, your tools, your workflows, your guardrails.

Using an LLM as a glorified chat tool won't help much. Plugging the LLM into a harness tuned to your work or your company's work will let you achieve the actual AI automation.

⚡ Quick Tip: Keep your Ollama models warm

If you run Ollama and notice the first answer after a break is slow, here's why. By default, Ollama unloads a model from GPU memory after 5 minutes of no requests. I noticed this on my Zima setup. The next request then has to reload the whole model from disk into VRAM, which will delay the next response.

You can change that. Set the OLLAMA_KEEP_ALIVE environment variable on the Ollama service to a longer duration like 30m, or to -1 to keep the model pinned in memory until you restart.

My point is that free GPU memory is only useful if you're going to use it. On a single-user machine where you're the only one using the model, there is little point in freeing up the GPU every five minutes and getting slow responses as a result. However, if you use several large models on one card, the default timeout actually helps.

🎫 Events worth attending

If agents are your thing, there are two conferences coming up, and It's FOSS readers get a discount on both.

AGNTCon + MCPCon Europe is happening on September 17 and 18 in Amsterdam. Use the code ITSFOSS_50 at checkout, which brings registration to $375. It's valid right up to the event date, which is tomorrow.

AGNTCon + MCPCon North America on October 22 to 23 in San Jose, California. Use the code ITSFOSS for 20% or more off current pricing; it should be around $375 again. This offer expires on October 7.

In the end...

I hope it was not too long. Not that I was trying to compensate for the long gap between the two editions...or perhaps I was ;)

As always, some of this will be useful to you and some won't, depending on what you're building or what your interests are. Reply and tell me what you're running locally these days. I read every response.

See you next week (for real this time).

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I Spent Time With GeForce NOW to See If It's Gameable on Linux

Linux gamers are used to being treated as second-class citizens, and Ubisoft recently gave everyone a fresh reminder when they pulled Linux and Steam Deck support from For Honor.

They blamed anti-cheat limitations, even though the game's anti-cheat software had supported Linux for years.

Meanwhile, cloud gaming has been slowly building up as an alternative, even for people who can't afford to build a gaming rig thanks to inflated RAM and storage prices. While growth hasn't been anything remarkable, people who can afford a subscription have been signing up for such services.

Geforce NOW is one such name that has managed to carve out its slice of the market, recently moving its native Linux app out of beta and into general availability, officially supporting Ubuntu at launch.

🚧

This app is not FOSS; we covered it because, you guessed it, it's available for a Linux distro; Ubuntu in this case.

Geforce NOW on Linux

Instead of storing games locally, like when using a game launcher like Steam or Heroic, GeForce NOW streams them from NVIDIA's RTX GPUs in the cloud. This way, a laptop or desktop gets GeForce RTX-level rendering without needing to have any of that hardware itself.

Games come from your existing library, not NVIDIA's own store. Link Steam, Epic, GOG, or PC Game Pass, and you can launch anything you already own. All updates and installs are handled on the cloud gaming rig you get access to via the service.

Setting it up

Contrary to what the official system requirements say about using the Xorg session on NVIDIA GPUs, I managed to get the GeForce NOW client running on the Wayland session of Ubuntu 26.04 LTS.

My laptop has a GeForce RTX 3050 with 6GB of VRAM, and the system was running with NVIDIA's proprietary drivers rather than the open source Nouveau. Don't worry if you have a less powerful GPU on board, as the app only needs a local GPU to decode the incoming video stream, not render the game itself.

While I kept my testing limited to Ubuntu, I have a feeling this app can run on other Linux distros too.

💬 Why not test it and let us know in the comments below?

Before I could start playing, I ran a network test via the settings menu to see if everything was good to go. The app reported that I could face stuttering or high latency as I was connected to a wireless network, suggesting I connect an Ethernet wire instead.

You will see me facing those issues very soon. 😅

Initially, I tried using the "Free" tier to see what the native app could do on my Ubuntu setup. It was a big fail, as I was stuck in a 300+ waiting queue for access to a machine, and when I eventually did come to the front, I was kicked out because I had left my laptop idle.

I then decided to get in touch with NVIDIA, and thanks to some helpful folks, I was set with a 14-day promotional key for GeForce NOW Ultimate. Next, I had to test some games that could take advantage of a GeForce RTX cloud rig.

The titles I went for were Fortnite, as the multiplayer pick, and Ghostrunner 2, as the singleplayer pick.

Two games in the spotlight

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Fortnite

The first game I want to show you is Fortnite, the infamous battle royale game that doesn't seem to be going out of trend anytime soon. Seeing that GeForce NOW supports directly linking one's Epic Games account to the service, I was able to quickly get into the game.

I left the graphical settings untouched, noting that the display name was "NVIDIA VGX," the FPS limit set to "Unlimited," and the rendering mode was "DirectX 12."

Even the matchmaking region was correctly set, and I was getting pings in the 100-120ms range. In the first battle royale match, I noticed that the image quality was not that sharp, and the game stuttered, with GeForce NOW warning of a spotty connection.

That was a given since I was connected to my ISP's weak wireless router. 🫠

Watch until the end to see some top-tier potato aim.

Across sessions, things did improve, and I even managed to win a match. That is when I realized that I could use "Ctrl+G" to launch the GeForce NOW overlay, which gave me access to many options, such as the remaining session time, the ability to enable real-time statistics, and a few others.

Equipped with the expanded metrics, I got to know that I was on a GeForce RTX 4080-powered rig that was pushing the in-game FPS up to 160, as advertised for the Ultimate plan, while the stream was running at ~55 FPS and the server latency was at ~45ms.

I was also losing considerable amounts of frames and packets due to my network setup, which had been quite inconsistent at providing the required bandwidth to drive such a demanding multiplayer game mode that hosts up to 100 players in a single match.

Ghostrunner 2

Next up is the singleplayer pick for this review, Ghostrunner 2, which continues the story of Jack, a clank..., erm, cyborg, rebuilt by a group of human rebels after they found him in a near-destroyed state.

Before I could start playing this, I had to again link my Epic Games account to validate access to the game. This is something NVIDIA needs to work on. If they could give gamers a one-click way of validating all their owned games that are available on GeForce NOW via a specific platform, that would go a long way in ensuring a friction-less experience.

Coming back to the game, the last time I played it was when I tested the demo version in the third-party GeForce Infinity app, where it performed awfully. While there were a bunch of factors that caused those problems, this time around, it was a much better experience.

Like Fortnite earlier, I didn't change the pre-set graphical settings, keeping them at a relatively high preset without enabling any kind of upscaling via AMD FSR or NVIDIA DLSS.

Again, I faced some microstutters, but the game itself looked really good and was very responsive throughout my playthrough. Without the lag, the game felt as good as running on a similarly equipped gaming rig locally.

I fell off the platform right at the end btw.

I can now confidently say that using Geforce NOW on a wired setup or with a very capable wireless router is the way to go. As doing so ensures a consistent flow of bandwidth that is required to stream such amounts of data quickly.

Being located closer to your nearest GeForce NOW server also helps. 😉

During play, I also noticed that my laptop going into Sleep mode would automatically disconnect me from GeForce NOW, with the app notifying me of the occurrence. All the while, the gaming rig itself remains active, and I can quickly jump back in by hitting Play again.

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Some closing thoughts

At the end of my testing, I was left thinking that NVIDIA could easily bring the native client to platforms like Arch Linux and Fedora. This would help them cover a large chunk of the Linux gamer base, seeing that there are many derivatives of these distros that are quite popular among gamers.

Coming back to the question I asked in the title of this review: Is GeForce NOW gameable on Linux? On Ubuntu 26.04 LTS, yes, even without the Xorg session NVIDIA recommends. Wayland handled things fine.

While its closed-source nature and paid tiers will be dealbreakers for many of you out there, the thing it offers is convenience. You get easy access to a gaming rig without having to invest in one, and the latter's a far cry (gaming pun hehe) right now thanks to inflated prices.

Game on!

If you are looking for instructions to install GeForce NOW on your Ubuntu PC, then continue reading. First, go to the official website to fetch the .bin file; look for it under the "Linux" category.

GeForce Now

Once the file is downloaded, go to it in Files and right-click on it. Now click on "Properties," and enable "Executable as Program."

Launch the executable by either double-clicking on it or clicking "Run" from the right-click context menu. Wait for it to complete the download and installation.

Next, you will have to agree to NVIDIA's Privacy Policy and GeForce NOW's Terms of Use. Be sure to go through them, as they contain many clauses.

The app will then ask you to sign in with your NVIDIA account, for which the authentication will be carried out via the default browser on your system. And that's about it; just select a plan and start playing.

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The Simplest Method to Extract All Images from a Document in LibreOffice

Ever found yourself in a situation where you have a document with plenty of images and you need to save images from it? Maybe a selected few or all of them?

Now, manually going to each image and then right click might be the no-brainer but an extremely tedious way to achieve this.

Let me tell you the quickest way to extract all the images from a work document.

Access the menu and go to the Save As option. What you have to do here is to save it as HTML. It will create several web files inside the same folder where your document is, but it will also extract all the images. That's what you want, right?

All image files extracted at once from the document

I'll show the details steps for LibreOffice in this quick tutorial.

Extracting all images from a document in LibreOffice

🚧

Create a new folder and move the document you want to extract images from in that folder. By default, the HTML files and images are extracted in the same folder as the document. You would not want tens or hundreds of images to clutter your main document folder.

First thing first, create a new folder and move your desired document file in there. Now open the document in LibreOffice.

Click on the top file menu and then click on the Save As option. The same can be achieved with Ctrl+Shift+S keyboard shortcut.

When it gives you the option to save, make sure to change the file type to HTML like this:

There are actually a number of file format options when you click that. You will have to look for HTML here.

Now that you have ensured that it is saved as HTML, click the Save button.

And then you should see all the images and media files from the document along with a single HTML file in the folder where you saved it. The default location is the same as your original document.

All image files extracted at once from the document

As you can see in the screenshot above, it also saved GIF along with PNG images. There is HTML file and the original doc, too.

This is much better than individually right clicking images and saving them.

And what if you wanted to select only a few images, not all? Well, in that case, you could either manually save the ones you want or extract them all and then only keep the ones you want and remove the rest. It is really up to you.

Another tip, since we are here, if your doc has way too many images and you want to extract a few from the selected chapters only, you can create a new doc and copy paste the chapter in it and save it as an HTML.

Basically, you can utilize this "save as HTML" option in a variety of situations.

Works with other platforms, too

This little trick actually works with most office suites, from MS Office to ONLYOFFICE. It works in Google Docs, too. Consider it a "universal trick" for extracting all images from a document.

I hope you liked this quick little LibreOffice trick. A quick thanks, if you liked it, is always welcome 😄

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Ubuntu's Rustification Has a New Milestone! Coreutils Migration is Complete

Ubuntu has managed to do away with GNU Core Utilities in its default stack. The last three holdouts, cp, mv and rm, have moved to uutils' coreutils; the Rust reimplementation Canonical has been feeding into the distro since 2025.

They had been held back from 26.04 LTS over flaws in the uutils versions. Everything else, from ls and cat to chmod and du, made that jump in earlier releases.

This change, while big, sits hidden away in an obscure mention in Canonical's work-in-progress release notes for Ubuntu 26.10.

It's been a long road

Canonical started oxidising Ubuntu last year, and Ubuntu 25.10 became the first release to ship coreutils as the default. That release also made sudo-rs the default privilege tool, replacing a command that had been in place for decades.

26.04 was the release where the plan did slow down quite a bit, as Canonical kept cp, mv, and rm on their GNU versions due to a bunch of TOCTOU issues that were blocking the full implementation.

These were caught during an audit, when Canonical commissioned Zellic for two rounds between December 2025 and March 2026, focusing on the most security-sensitive utilities first.

Across both rounds, Zellic raised 113 issues, and 44 of them were assigned CVEs. Canonical says the vast majority have been resolved.

Getting here has had its ups and downs, and the last stretch was not clean. In July, uutils cp went back into the archive and came straight out again after it broke live image builds.

The fix was quick; as the developers marked it "Critical," the fix went upstream, and the migration landed in time for 26.10.

What changes for you?

When typing commands, nothing changes for you on the surface. uutils coreutils is designed to be a drop-in replacement for essential GNU tools, and the project treats any divergence from GNU as a bug, further pointing out that some options may still be missing or behave differently.

So if you prefer staying on the GNU version, you have the option to install the coreutils-from-gnu package that houses all the required components.

The next stage

Coreutils is one piece of a broader campaign. Earlier this year, Canonical became a Gold Sponsor of the Trifecta Tech Foundation, pitching in €40,000 a year to fund memory-safe system software.

Under this, their current target is ntpd-rs, a Rust rewrite of the tools Ubuntu uses to keep its clock in sync. While work is still ongoing, it has already arrived for testing.

Its transition to being default is targeted for Ubuntu 27.04.

What Canonical is gradually building up towards is the completion of their oxidation vision for Ubuntu, and it's not about blindly including new components. Rather, it looks like a measured approach that's being worked out a few steps at a time.

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Suggested Read 📖: Linux is getting ready to purge old 32-bit Arm platform code.

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Rune Goes Open Source, Looks to Share Revenue With Contributors

Rune has left behind its proprietary old self for a new open source identity under the GPLv3, letting you clone, read, or build off it from GitHub. The relicensing came via a string of moves, one of which was the commit that marked the project's license transition.

The developers have also decided to keep commit history mostly intact, which runs back to 2017, with some gaps here and there. I point that out because projects that go open often squash the history first, so old secrets and sensitive commits never land in the public repo.

To give you some context, Rune is an IDE for Linux and macOS that can be used for writing and debugging code, running your terminals and CLI tools in the same window, and letting a coding agent take on parts of your tasks.

It is based on Go, and the team defends its use by showcasing vtebench runs that show the Go terminal keeping pace with Alacritty, Ghostty, and Kitty on a set of terminal workloads.

Do keep in mind that these were not language benchmarks; these only show how far the IDE has come.

The Rune team is further looking to expand language support beyond Go and Python, with Rust and Zig already in beta on main and an open call for developers to steward their own language.

While the IDE itself is free to use, people can opt for paid plans to get access to the P2P Rune Network, premium support, and a separate tailored plan for enterprises with extra bells and whistles.

Going the open source route

The license, GPLV3, allows contributors to keep the copyright in what they submit, and the company (Unstable Build LLC) takes no special right to relicense their work. Earlier, the project asked contributors to sign a CLA; that's not the case anymore.

Rune's creator, Ernest Romero Climent, is not happy with what has happened elsewhere in open source, where companies build in the open, lean on the community for years, then change the license once the project is worth something.

Instead, they are looking to pay contributors via an opt-in credits program, where accepted work earns credits and a slice of eligible service revenue funds a pool, which is then split by the credits each contributor holds.

All awarded credits will be tracked in a public ledger, showing the revenue behind the pool, any deductions, the credits awarded, and how each payout is worked out.

As I said, all of that is optional. You can still send patches without joining the program.

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Suggested Read 📖: openEuler and the race to build Asia's AI infrastructure.

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openEuler and the Race to Build Asia's AI Infrastructure

When it comes to open source and AI, we almost always look West. While a lot happens in the United States and some in Europe, the East is not lagging either.

In the recently concluded LEAP East conference, several startups and enterprises came together to showcase their innovations and share what they were building.

Out of them, openEuler caught our attention for its focus on Open Source AI.

The SuperPoD

At LEAP East 2026, openEuler showcased its SuperPoD OS, which extends operating-system support for UnifiedBus-based SuperPoD computing systems.

Think of a SuperPoD as a cluster of several powerful computers that need to act like one giant machine. Running AI workloads takes computing power and doing it across hundreds of such machines is messy as they need to share memory, pass data around quickly, and not conflict with each other.

UB Service Core is the open-source software layer, part of the openEuler ecosystem, that makes coordination across those machines actually work. It provides five cluster-level system services for UnifiedBus-based SuperPoDs: Engine, Memory, Communication, I/O, and Virtualization.

The Engine pools memory and DPU resources across the cluster and schedules them dynamically. It also handles automatic failover so the system keeps running if a node goes down.

The Memory component lets machines within a UnifiedBus-based SuperPoD share and pool memory using unified-memory programming, meaning software can treat distributed memory as a single addressable space.

The Communication piece provides high-performance networking over UnifiedBus while staying compatible with standard Socket and Verbs interfaces, so existing applications don't need to be rewritten to benefit from it.

The I/O service handles global data read/write caching at a high level, which matters for workloads like AI inference that repeatedly access large shared datasets.

The Virt component covers virtualization pooling, decides live-migration policy (when and how to move a running VM to another machine), supports disaster recovery, and improves communication efficiency between VMs and containers.

Together, these five services give a SuperPoD cluster the coordination it needs to perform like a single well-organized system, with a claimed 30-50% performance gain over conventional architectures.

According to openEuler, UB Service Core can improve application performance by 30–50% by taking advantage of the peer-to-peer UnifiedBus interconnect architecture.

This SuperPod or UB Service Core is fully open source under the openEuler umbrella.

Agentic AI in the OS

openEuler is evolving toward an AgentOS model. In openEuler 24.03 LTS SP4, DevStation (desktop variant of openEuler) includes openEuler Intelligence, a desktop AI assistant that uses an agent runtime and MCP-based tools to support development and system operations.

Pre-built agent harnessing in the operating system is not uncommon these days. openEuler 24.03's built-in AI agent can be used to control the Linux system.

So, instead of doing things manually, by mouse clicks, you could just ask the agent to dim the brightness, lower the volume, or change the wallpaper. The built-in AI agent has custom skills to control the system settings in openEuler's UKUI desktop environment.

This is a work in progress. But the direction is clear. AI agent should soon be able to let you control the system instead of doing things manually.

Expanding into a community-based ecosystem

openEuler has launched openEuler Hong Kong User Group to bring together developers, researchers, and organizations in Hong Kong to connect, share experiences, and explore open-source innovation together.

openEuler is an open-source project incubated and operated by the OpenAtom Foundation. The community is expanding international collaboration through local user groups, industry partnerships, and participation in global open-source events. The Hong Kong User Group represents another step in openEuler’s efforts to encourage local participation and international collaboration.

Explore openEuler Community

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Paperweight: An Open Source App to Clean Up Your Inbox and Digital Footprint

E-mail is one of those things that get really unruly before you realize they have. You sign up everywhere with your e-mail, get lots of spam from services that you almost forget you have even heard of, and all the important things, consequently, get lost in the noise.

This is the problem Paperweight aims to solve. It is an open source application that helps you see what accounts or newsletters you subscribed to so that you can take a decision on them.

Paperweight helps you reduce your digital footprint locally

You probably already know that a digital footprint is the trail of information you leave behind when you use the internet. While it is not easy (nearly impossible) to erase the entire digital footprint, we sure can reduce it.

There are premium services like Incogni from Surfshark that does this job for a fee. They look into all the data broker databases and also send the data deletion requests on behalf of you.

Paperwight aims to help you do some of those tasks. The idea is this. You plugin your email into Paperweight. It scans all the emails and gives you:

• Accounts you signed up for or made a purchase
• Email lists (newsletters) you are on
• Personal data (like phone number, payment details) in the messages

While you can bulk unsubscribe, rest of the action needs manual action. You will have to approach the respective websites by sending them emails individually.

And here's the thing. All this processing happens locally on your system. The inbox is scanned on the system, there is no server in between, so no data collection. The source code is available so you can verify these claims.

Let's see paperweight features in detail.

Bulk Unsubscribe

All the services that send you e-mails are listed under "Mailing lists" right on the main window, and you can go in and check what e-mails you've been sent, how many, and the dates of the recent ones.

Here's the exciting part: you can select multiple services at once and unsubscribe from their e-mails without having to individually open every single service's e-mail and going through the unsubscription process, which usually takes you through a few browser hoops.

After selecting the services you wish to unsubscribe from, it becomes a simple matter of clicking the dumpster icon and confirming:

📋

Sometimes, some services require more intervention, so even if you select all the ones you wish to unsubscribe from, you might have to do a few individually. Also, some services simply cannot be unsubscribed from, such as YouTube's on Gmail. The selection box itself is grayed out for them.

Note that many email services, including the privacy-focused ProtonMail has this feature built-in.

Account Inventory

An entire "Accounts" section shows you exactly all the places where your e-mail is being used to log into other services. All the services where you did "login with Google" will also show up here if you're using a Gmail account.

There, you can see the kind of access it has to your data, including financial, identity or health information, and gives you an unsubscribe as well as a "delete all e-mails" button.

Again, the automated unsubscribe request may not always be respected by the service at the other end.

Breach Alerts

Under the banner of the same accounts inventory, Paperweight also makes an exclusive list of services on that roster that have been known to be at risk or breached. It gets the security risk data from publicly available Have I Been Pwned, and gives you the options to delete/request your data, and to delete their e-mails on your account.

GDPR Deletion Template

GDPR (General Data Protection Regulation) gives users the "right to be forgotten". As such, mostly companies have to comply with the rule and relinquish any and all data they might have regarding an individual if the individual requests so.

How does Paperweight come in? Well, they give you a template to request your data from any service you are subscribed to. Just click on the "Data requests" option down below in actions, and you'll see an almost fully written e-mail to get the company rid of your data.

It is still not fully automatic but it is still better than doing it all from scratch.

Interface

The user interface is pretty sleek and pretty simple. On the dashboard, three big blocks show the number of e-mails analyzed, mailing list subscriptions, and accounts where your e-mail is used.

On the left, there are small buttons to access pretty much the same things. There are a few "at a glance" type lines showing recent activity and highlights of the analysis of the account.

Finally, a frequency graph shows the number of e-mails you've received in the past few months.

The interface for further options are shown in the screenshots above and pretty much show you all available options right on the face. You don't have to look too far for anything at all.

Data Traffic

Just out of curiosity, I tracked the network traffic going through Paperweight and to my relief, it only seems to be talking to the e-mail service providers' servers or the servers of the services that you're trying to modify. For example, there will be traffic to and from Canva's servers if you're trying to unsubscribe from their mailing list.

Free vs Lifetime

Paperweight might be open source, but it is a freemium sort of application. There's a free version that lets you use Paperweight with one email account and 90 days of email history.

And then there is a lifetime license that costs a one-time payment of $69 and gives you the option to add multiple accounts and scans through your entire past e-mail history.

Here's the thing. The source code is available on GitHub, under the MIT license and if you want, you can fork the repo, modify the code to remove the restrictions, and use all the features. There is no constant validation for the license. However, that would be a breach of honor.

Although I feel that $69 is a bit too much, probably because I am a student. Price parity and pay-what-you-want model would have been better. But that's just my opinion.

Getting Paperweight

Paperweight is available for all of the big three operating systems Linux, MacOS and Windows.

On Linux, they provide an AppImage and a .deb package.

Get Paperweight

Conclusion

For a lot of users, Paperweight probably provides a service that you had no idea you needed. But now that you are, you can use it periodically to maintain a clean and healthy inbox. Once a month, on a weekend should be good enough.

The free version does feel limited, though, especially the 90-day history cap. I would have preferred a Melia like solution that allows full access for a single email account and lifetime license for multiple accounts.

If you give Paperweight a try, do share your experience in the comments.

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