So, let's give a round of applause to Yos.
Thank you.
So, we're going to misread the clock officially.
And, of course, we're at Phos Dems.
I'm going to obviously talk about something completely open source, with no shenanigans there.
How many of you, like, know next lap quite well, and are here for an update, okay?
That's pretty much everyone.
And, how many really are like next lap next lap?
I guess I'd like to know more, okay?
That's really just a few.
Oh, class, even, yeah.
I'm happy to give you a one-on-one, even.
Yeah, it's essentially at a placement for Microsoft 365.
So, teams office, one drive, the whole shebang.
But open source and running on your own server.
That's a short of it.
And you're going to see much of the features in the next, you know, 30-ish minutes.
One thing I want to talk about very shortly is, so two features.
I want to quickly talk about in general on this Federation.
So, as next out is designed to Southhouse, that would mean you're all on your own.
You're on little server with the 5, 10 or 5 million users, in some cases,
that you have on the server.
But thanks for Federation.
Similar to what E-mail does, and also must've done these days,
and a bunch of other tools.
You can work between people from different next-out servers.
So, you can share files to people on the other server.
You can have a video call with people from another server,
or a chat with people from another server, and all feels like a single installation.
So, there's pretty neat.
And the second thing, of course, security, which is always important
with these kind of things.
Next out has, well, the basic HCTPS, so when you go from your server to your client,
I mean, you can say, well, it's a trade-off.
There's still a performance impact, and sure there is, but I don't think anybody wants to
center stuff without any protection anymore over the internet.
So, find the amazing that that was still a thing 10 years ago.
On top of that, you can encrypt your data on storage.
In case you're, for example, afraid somebody comes in and steals your server at night,
with Raspberry Pi that's relatively easy with a big server,
a data center.
It's a little bit less likely, but there's, of course, still a risk somebody breaks in.
So, it's the data's encrypted at rest that works when they break in.
But, of course, if they're in, you don't notice,
and they can observe what's happening after a while,
encryption at rest is not good enough.
I mean, it's an encryption for that, which means encrypting on the client.
Turn what off.
There's still one, there's a case you can do that.
Oh, sorry. Please do.
So, if you're running an XOT server, and you have maybe a subset of data that you want to protect,
even in case some of the breaks into the server, or maybe you don't trust the server admin,
and actually you can run this at home, but you can also run this as a service provider,
then you can use the antenna encryption, which basically encrypts the files on the client,
mobile, or desktop, so that then on the server, they cannot be read at all.
The keys are encrypted, also locally, and not, well, they're only encrypted sent to the server,
and you have to exchange passwords manually between the clients,
to be able to have everything only locally accessible.
Anyhow, what are we doing, all this effort for?
Of course, because we don't want to live in a world where these companies,
basically, control our entire digital lives.
I heard yesterday, people saying that Europe is now a digital colony.
It's not a really nice thing to say, but the Broly Garkey is definitely in charge,
I would say, that's just a reality.
If an American president would want to shut down the European economy,
because Europe doesn't, I don't know, lower its tariffs, or stop selling cars,
or whatever it is, they won't.
They can actually do that.
And they might not do it, but that will then be because Europe gave in, because of the threat.
And that's, I think, not a healthy situation to be in as Europe.
And obviously, on the personal level, I don't want these guys to have my data period,
so that's that as well.
So me, yours, was already mentioned, so I'm just going to move on here.
And the thing is, I'm going to talk about the releases we did last year,
and you know, we always do these release videos.
They are one and a half, two hours long.
We did about three releases.
You can do the math.
I have to do this in 30 minutes, so I'm going to go pretty quick.
And I'm skipping a ton of stuff.
So if you say at some point, like, hey, I'd like to learn more about XY or Z,
you can also just wave at me, and if I'm paying attention, which isn't always a given,
I will try and, you know, help you out there.
All right.
So I have tried to group it a little bit, so that everything is grouped by feature,
not so much by release.
But I'm still going to start with things from XY8,
and then mix in XY9.
And of course, there'll be also our special talk release we did.
But let's start with XY8 files.
So that's the file sink and share.
With a desktop client, mobile clients,
the document photos, videos live there.
Yeah, easy to use.
Of course, if you have, well, normal user these days,
have thousands, tens of thousands, hundreds of thousands of files,
that can get a little overwhelming.
The next set has a ton of ways to help you.
For example, we will recommend some files.
For example, that we're recently edited or recently shared with you,
just to help you find these files quicker.
We keep track of relations between data.
So if you have files that you're working on with a group of people,
then when you click on one of these files, you will see the other files.
But you will also see a chatroom, you will see maybe a task
that is related with the files, et cetera.
So the different content between the different next cloud components
will all then be visible there.
And you can say, oh, you know, we have a calendar together.
We have a meeting room together.
And that is all that related to these files.
In the left side bar, you have your favorites.
You recently changed files, another quick filters.
And new and up eight was the personal file field that just sees the files
that are completely yours and not shared by others.
Because, you know, especially if you live in the company,
you have tons of data that is actually shared by colleagues
and not really yours only.
It can sometimes be helpful to quickly see that stuff.
Now, there's, of course, another way to find files.
That's a search.
And you can there find, again, content from all over next cloud
through emails, chat messages, well, and your files.
And of course, those files might even be shared in the chat room.
And next, let's have a video chat application, right?
Next, I'll talk.
And that's deeply integrated with the rest of next cloud.
So if you share a document, you can just edit the document and view it right there
in the chat.
There's no need to navigate away open a tab or download it and edit it on your desktop.
You can just go and work on your files.
And this also works during a video call.
So it can be, well, a quick way to edit something.
Obviously, this is not where you write your presentations or big documents.
But for that, you can open it and separate tab as well.
You can also insert files in deck.
Is it playing?
No, it is not.
So you can insert all kinds of content.
It is our lightweight project management app.
And again, you can just insert the document there.
And you can edit it right in there.
You can choose to view it as a link or you want to see the full file.
You can scroll and see the button and then go and edit away.
So this tool that you just saw the slash and then it gives you a bunch of choices.
This lets you also do other stuff.
Besides inserting files, you can insert the link to a location or a street map.
You can insert an image.
You can insert a video.
You can insert tasks.
You can insert calendars.
You can insert chat rooms.
Basically all kinds of content from all over next cloud.
It can be inserted in any of the places.
So this works in chat.
This works in the task.
This works.
Basically anywhere.
And that's all.
This is our notes app.
But again, when you have text input fields, you can put all kinds of content there.
That works all over next cloud.
Now sharing, of course, a pretty core part of next cloud files.
When you share, you have a bunch of options.
You can add a note.
You can hide the download option.
You can limit downloads.
It was new in Hub8.
You can also show a QR code.
I never really understand why you want to have it on your screen.
If you want to share it.
But I'm guessing you can send the QR code to people.
Or print it.
Now, these were all things that changed in Hub8.
And I promised that I would mix in Hub9.
But the thing is Hub9 made design chains.
So it would have been quite visible when it was Hub9.
So I thought that first show that design.
So with Hub9, we had a new background.
And we changed button and border radius, basically,
to take a little bit less space, make the interface more efficient.
And that denser interface is very visible, especially in talk.
Because you can noticeably add more chats in the room and have so more messages visible.
Yeah.
This is an exit files where we also updated a lot of icons.
I made a sidebar a lot more compact.
And the breadcrumbs is more compact, etc.
So I think this is nice for people who like to have a little bit of a denser interface.
Oh, that was an exit mail.
And I'm going a little quick.
So there everything closer together in collectives and knowledge management app.
Also improve the layout of the pages a bit.
And of course, for those with a dark soul, like me, a preferred dark mode.
Then, well, this is of course also available in the next slide.
All right.
One of the new things that we did are filters.
I, yes, exactly, it does play.
So you can quickly filter for specific file types.
There's also on the top left I search.
So you can also search, of course, by the words.
And find a file that you're looking for specifically.
A lot of people have also been asking about a folder preview on the sidebar,
which we introduce now.
So you can navigate your files a folder faster.
Another cool thing.
You can also upload folders, not just files.
And we added a folder quest feature.
You could, of course, always send a folder to people where they can upload files to.
But with a further quest.
Come on.
Go play.
We created a nice dialogue where, well, a non technical person who find this whole, like,
create a public link and then make it possible to upload files, etc.
Who finds it complicated.
You can just answer a couple of simple questions.
Who do you want to send it to given email address.
And then they will get an email with a nice request that says, please upload the files here.
And then later, of course, you will get notified when the files are uploaded, etc.
It just makes the same thing a little easier to use.
Tons of other improvements.
But I don't have time for that.
I need to get a group error.
So mail app is, of course, designed to make your life easier.
So you can do things, etc.
A minor for a mail.
We have a AI inbox.
We actually had that already four years ago or something.
Before the LLM-Crisse, this is just a locally running neural network that gets trained on
your emails and what you click and what subjects you like or people you mail with.
But we do use the LLM-Crisse as well.
So you can summarize emails.
It will put little summaries in there.
If you have a long email thread, it will summarize it.
It can suggest replies, you know, and we have a pretty cool feature.
And I think that's in the next slide.
I'll wait with that.
We have, as my signatures and encryption, all this stuff.
And shared mailboxes as well.
Now, yeah.
So one cool thing we did for hub nine is that we created an urgent thing on top, which
the LLM actually reads the email and decides if it might be urgent or not.
Again, this stuff has a perfect, as lots of online videos about all kinds of stuff show.
But it can help you, you know, make sure.
And this also helps you with reminders.
So it basically, when it sees like, oh, get back to me next week,
then the week after this email has put on top of your inbox.
So it'll automatically decide when emails need to need to follow up.
While, of course, if the email is just like, okay, thank you.
Then you don't need to follow up.
So it basically filters out the emails, what you need to do something with.
Rather than emails that are maybe, yeah, just for your information or newsletter, etc.
All right.
Well, we're at the calendar app.
And this is connected with NexatTalk.
So you can, for example, insert calendar invitations and also see them in talk.
Another cool thing is that if you create a calendar invite in the calendar app,
you can add a talk room and then in the talk room, you can see when the upcoming call is, for example.
So this is also nicely integrated.
But this is where you can share, you know, schedules and stuff.
We improved the filtering and search email a lot.
It now supports C filters.
So that means the filters actually run on the server instead of on the client,
which means if you use multiple email clients, including the Nexat webmail client,
you will have the same filters everywhere because they're processed on the server automatically.
The mail server itself.
Well, back to the calendar again.
We worked a lot on the availability few resource booking that went a little too quick.
Room search and so you can put in resources and then book a room or a book, you know,
a projector and these kind of things quite nice in the company.
And I already mentioned NexatTalk. You can see upcoming meetings.
With Hub8, we included a global out of office.
So there's a fact, of course, your email.
But people who try to chat with you also will see a message that you're out of office until a certain date.
And if you try to book a calendar meeting with you, then the calendar will also say you're out of office.
So you don't need to put a blocker in, do your calendar manually.
And your status also shows that you're out of office.
So you only need to set this once.
There's a ton more that happened, and I really couldn't make it very readable.
But there a lot of work that was done last year in group air.
Office, I'm going to keep even shorter than the other stuff.
We developed this together with Klebera.
Michael Meeks is not in the room, but at some point I'm sure you can follow the talker.
He talks about a lot of the improvements they did.
Of course, a number of things is done specifically for NexCloud.
The general performance and security work, etc.
You can then get for Michael Meeks.
One cool thing that we did in NexCloud itself is support for filling forms.
So if you have a document with forms, you can use the NexCloud interface to fill in the form.
And then you get the document, you can then sell mic changes.
Or you just got a PDF out of it that you can immediately send out to other people.
So that kind of integration is quite nice.
Now, I already talked a little bit about talk.
I'm going to dive into it a little deeper now.
So this is for online meetings, video conferencing and chat.
It's effectively Zoom and Slack into one.
So think of mics of teams.
That's effectively, of course, what it aims to replace.
Scales to hundreds of participants, a call with 500 people.
That's a reasonable amount of problem.
You have mobile interfaces, Android, iOS, desktop interface.
Feet is like breakout rooms.
Federation that I mentioned earlier is available for talk as well.
Yeah, essentially complete mics of team replacement.
We've had nine interviews tonight's whiteboard.
We in December are desktop clients became 1.0.
So that is now officially shouldn't just be playing officially stable.
A ton of other new features.
For example, you can now save a poll as a draft.
You can even export it as a file.
So if you do webinars a lot, my team does a lot of webinars.
And then you can create polls, save them into a file.
And then when you create a new webinar, you just upload the file.
With the polls and then you can, you know, you have them all the drafts.
And you can just one by one just click.
Publish publish publish.
You don't need to manually work on that.
So that kind of stuff is quite nice, I think.
You can also invite people by mail or by public links.
You can send people a public link and they can share it with others.
But if you invite them by mail, you can see that that person with that specific email address actually joined.
So again, for webinars, you want to track which of the people that got invited.
Join.
So you can upload the spreadsheet with email addresses.
And then all these people will get a unique link.
And then when they're joined, you can see you can also in advance already make some of the moderator for example.
I have their speaker, if they're a participant.
You can then set the permissions for that already.
Yeah, and then later you can export the people who joined.
So that you can see from the people who you invited, which ones showed up.
Now, thinking about it, I could have put this in the section completely at the beginning.
I already mentioned a bunch of LLM things.
There's quite a bit of AI features in the Naround next slide that we've been implementing.
But of course, you know, we're making an on-prem open source self hosted privacy solution.
And so integrating said GPT was an exactly like top on our agenda as you can imagine.
So instead, we talked actually at the first time a couple of years ago about AI and where we want to go.
Because on one hand, it can be helpful for some things, especially summaries.
It doesn't hallucinate too much in summaries.
And we thought, well, we want to bring those benefits to users.
But again, we don't want to give up on their privacy.
But the thing is, of course, you don't have a lot of options with everything.
I have for speeds to text, there are quite decent on-premises models.
And already four years ago, we integrated recognized, which will automatically tag your photos with faces,
and with objects so you can search through them.
And there was a completely on-premise running model.
It was a gigabyte, it was pretty big, but it worked on a CPU.
And so, that was nice.
But when all the LLM came out, we were like, okay, we need to think about how we're going to do this.
So, we came up with what we call our ethical AI approach.
It's fairly simple.
The idea is that each of the AI options that you have,
I think of CHGPT or locally running Lama, et cetera, and everything in between,
gets a rating, and the rating goes from all, rather green.
And it depends on these three factors.
So first is the code that you need to run the LLM and to train the LLM open source.
Second, if the model is available, that means you can run it on-premises, if these two are true.
And then last but not least, is a training data completely open and available.
So if all these three conditions are met, the AI solution is green.
If one of them is not met, orange and fury can figure out the rest, where it goes from there.
So the idea from us is to bring transparency and to give you as user a choice.
So this choice is quite literal.
In the interface, you will be able to choose which AI model, if you have a bunch on the locally,
or which remote service, et cetera, you want to use.
And then in our app store, you see the rating.
We try to make sure that they're all transparent there, and you can then choose.
Yeah, if you have a big BFGPU and you have a nice local model, you can use that.
And if you're not handling any critical data and you're happy sponsoring Microsoft,
you can send your data to chatGPT.
So this way, there's choice.
So we integrate in tonal place.
I already showed you a few things in our summaries in mail, for example,
but there are lots of other places.
We already were using neural network things,
or experimenting with that, as I mentioned,
our smart inbox that is already downloaded before the LLM crash.
We also did a suspicious log and detection,
so we're training on your server neural network on your logins.
And if you normally log in from 9 to 5 from the office,
and suddenly, there's a tree.
A.M. in the morning, a log in from another continent,
then you will get a warning, and maybe we will block the log in,
depending on your settings.
Cold transcripts, so if you have a call in Excel talk,
you can have it if you have the recording on.
After the call, you will get a transcript,
you will even get a summary that there's new in Excel to have nine.
And then, yeah, we'll save you some time, of course.
And you can search through your calls, basically, this way.
And there's, of course, a text generation,
you know, translate translation, dictation, all these features.
So, this is all under the name of the next other system,
also the old features.
And the next other system is, well, obviously,
then a large language model, based mostly,
at least 100% open source and on-premise,
so no data sent.
If you use the local LLM, as I said,
this is a choice, this is transparent.
Last year, we basically introduced version 2.0,
so that came with a complete overhaul of the interface.
A lot of work on the back end, so you can now have a separate server,
dedicated for AI, so maybe with a GPU, right?
So, you split it up from your normal application server.
The difference and performance between a GPU or a CPU for AI is,
well, I'm sure I don't need to tell most of you,
it's absolutely insane, so this is quite helpful.
Yeah, they came then with the summarizing of email transfer example.
You also introduced two features, context, right, and context yet.
The context, right, allows you to basically give the LLM an example document.
You can say, like, hey, here's an environmental responsibility report.
If you want to write one yourself for your organization,
you give it to your responsibility report from another organization,
then you give it the notes from a meeting that you had to discuss,
the state of environmental policies and your organization,
and you say, use the meeting notes to write a report similar to the other one,
and you have a pretty good start to get going.
The second thing we did is context yet.
So, cause I can write right for you, context yet,
allows you to ask questions about your own data.
So, basically, all your documents, all your chats, all your data,
in-next loud, is put into a vector database,
and you can ask questions, you can say, like, hey, you know,
what is our internal process for organizing an event,
and it will look through your documentation and make a summary of that.
Yeah, another thing, it's not only able to look through your documents,
it's also able to look for data in other applications.
So, for example, the next other application, called analytics,
and in there, you can, while either via spreadsheet or via an API,
upload all kinds of analytical data.
For example, whether data, if you're tracking whether data,
for you at home, you can hook this into the analytics app.
And the nice thing is, the analytics app can then let this get indexed
by the vector database.
So, you can then go and actually ask a question from the LLM,
and you can say to the LLM, like, hey, what was the warmest month last year,
and then look in the data and answer your question.
So, that's pretty neat.
Also available on your phone, as I already showed twice now.
So, for the last 20 minutes, I've been showing you all kinds of features,
and abilities of next loud.
Everything, you know, connected from apps in next other itself.
Of course, we're a very big ecosystem with lots of other applications
that we are integrated with.
So, if you say, hey, the next I talk, so fine,
I don't need to be able to edit documents in the chat.
I'm using element, for example, or, you know, hack.
Maybe you're using a proprietary solution, like WebEx, for example.
That's fine.
You can connect this to next loud.
We have tons of integrations with these other solutions.
And always working with good friends, like XWiki, you know, project,
and the intervention lots of other cool projects together to make these integrations
better and make it easier for you.
And, of course, because many of you are still stuck to this company,
we also have integrations with Microsoft.
I hope that this helps you migrate away from it, but still,
it is necessary in many cases.
So, the apps for next loud can be built as part of the core.
Next loud is written in PHP with components in Rust and go in other pieces.
But you don't have to build an XWTP.
You can build an XWTP and go in Ruby and Python, whatever language you want.
These apps would then run as part of a Microsoft's architecture.
They use Docker deployment, so you get distributed compute.
And, of course, this also can be a security benefit.
So, if you want to build an XWTP in other languages, this is possible as well.
Now, last year, we introduced one more big thing.
I want to talk about it for a minute, and that's an XWTP flow.
Next up is essentially a business process automation engine.
Honestly, quite boring for a home user.
We have some automation features for private users too.
But for businesses, this can be quite helpful.
It can do a ton of things like connecting, basically,
the different functions between next loud and executing actions on it.
So, the reason we developed this was in Germany, like in many other countries,
they're trying to automate processes as government.
So, that, for example, if you want to request a password,
sorry, passports, not a password.
That is handled in an efficient way at the government.
And to automate these processes, to be able to request this via the internet
rather than having to physically go to an office and give all your papers in current passports,
etc.
Well, they need to make a lot of changes in improvements.
And Germany is really lagging behind in this.
So, are several other European countries.
And all the automation tools for this are proprietary.
So, basically, as your government, if you want to automate these things,
you either have to build something yourself or you buy from a proprietary vendor.
And that's not great.
So, we thought, well, if you already have a ton of your data in next loud,
wouldn't be nice if you can then use that data, just directly from within next loud
to automate these processes.
And that is what the integration of flow was designed to help with.
So, you can connect pieces from next loud.
I like, I don't know, in next, that forms app.
People fill in the form.
And then that goes into the next autables app.
Maybe your notification is sent to somebody to check if, you know, the content of the
form is correct.
You will touch a file, etc.
It can also handle, like, an incoming email.
If there's PDF attached to that email, it can take the PDF parse it.
Put the content in the table.
Let the human double check it.
You can even run it through an LLM for certain operations if you want.
I would then definitely let the human check it.
And then, for example, send an email back or send a ping to a payment system.
And then handle the payment generated PDF and set it out again.
So, all these things are possible within next loud, using flow.
All connected.
Do you have enough government sets and nice things about that?
Which I think is really cool.
And I'm going to close it here so that you also have some time for questions if there are any.
Of course, all of this, we're 130 people at next loud.
That's just a small part of our entire community of thousands of people.
So, for those of you who are contributing to next loud one way or another.
Thank you.
You might all of this stuff possible.
In our next release, which is coming quite soon,
there's really a ton of contributions, including some features.
I'm personally very happy with from community members.
So, this is not just a community, but actually just a company doing itself.
And throwing the code over the wall occasionally.
We're a bottom up community where community members have real impact.
And personally, that makes me quite happy.
I think it also shows from the full bedroom every year here.
So, yeah, thank you.
Come to our conference, by the way.
We will announce the dates.
Hopefully, the coming week.
It'll be in September, in Berlin.
And yeah, we'd be really cool to see you there.
And of course, as I mentioned, soon, this is coming in just a few weeks.
And there'll be a ton of good stuff there as well.
That's the end of the show.
Any questions?
Thank you.
I don't think that they do.
So, now I can repeat the question.
I think that's easiest.
So, yes.
All right.
Yes, question.
So, the question is, can you talk a little bit more about the technical part of the Federation
feature?
Yeah, a tiny bit.
But I think the techie is, from our team, can go a little deeper.
But basically, it depends on what you're federating.
So, I think it's a little bit more about the technical part of the Federation
feature.
Yeah, a tiny bit.
But I think the techie is, from our team, can go a little deeper.
So, basically, it depends on what you're federating.
So, for files, this is using WebDev and the Open Collaboration Services.
So, that's an Open API.
I think it also uses Open Cloud Mesh API.
So, this is standardized.
For next time, talk.
It's effectively using also the Open Collaboration Services API,
mounting the room in the other instance.
So, you will get the room locally, but you're actually on the room of the other server.
So, the way we do Federation, by principle, is both for the files, as well as for talk,
is that the data stays on the owner's server as much as possible.
So, when you share a file with Federation in X-Loud,
the recipient gets access to the file.
But the file is not sent to them and stored on their server.
Only when they click on download, they don't sync it, et cetera.
So, the file stays where it is, and the moment you un-share it,
then they don't have access to it anymore.
I think that's better modeling some ways for,
at least from a privacy point of view, and a control point of view.
Then, like, syncing all the data to all the servers,
as a site from the overhead that causes, of course.
It's the same with the chat room effectively.
Yes?
At the land, it's very, you know, health value condition.
For details about the rat spiked of the next cloud,
on modular reviews, and how it's built,
and how to restrict knowledge of use,
like databases, and kind of bugs.
So, the LLM part of it.
Well, we're pretty simple.
So, the question is, can you share more details?
Thank you.
I have the memory of a squirrel.
Can you share more details about, like, the AI,
basically, the integration with that?
So, yeah.
We're essentially not, we're not building our own LLM, right?
I think for the speech to text engine,
we did build a model using some universe of Helsinki data.
But, of course, an LLM running is not really a feasible thing.
So, we're basically supporting pretty much all of the models out there.
I don't know exactly how this works on the back end,
but we're nearly any model, basically, that you will find on hugging phase.
You can run locally, and who can to next cloud.
I think the best answer I can give you.
I'm sorry.
Yeah. Next question. Yes?
Yes.
Welcome to your favorite, sir.
I'm sorry.
Ah, my favorite feature, I have done.
All right. All right.
All right. One hint.
I use talk all day, because I'm, I'm, you know,
chatting with my team, et cetera.
And while the universal search is really nice,
it immediately searches in all chat rooms, documents, chats, emails.
It's a bit much.
And a community member actually basically build a very simple,
there's a little search clause in the top right now,
and you click it, and you just search, you filter in this single chat.
So, tiny thing maybe, but it makes your life sometimes a lot easier
that it just searches and won't chat.
And again, you can use it to the universal search.
You can just say, only this chat, but that is still three more clicks.
And, you know, it's little things that make the difference sometimes.
Yes.
So, so, you mean the Federation part?
No, I mean the Federation part.
The single part is fairly good.
You have to sort of drive up to take care of it.
Right. So, basically, the question is, how can you run
next to an higher availability environment?
Yes. Yes, absolutely.
Yes. Because it's in the core, although, as I said,
there are some components in, in, in, in, in, in,
rust and go, et cetera.
And, call a borough, of course, a C++.
So, not all components scale exactly the same,
but the basics of it is largely still very easy horizontal scaling,
because it's a PHP web app.
And PHP means that every request that goes to the servers is almost completely independent.
So, if one of the application servers goes down, you're good.
If you run multiples, so that's pretty easy to do.
Data bases can be done redundant.
These data file systems can be done redundant.
So, it's not really something that happens at an exot layer,
but running a high scale, highly redundant.
Nexot instance is not terribly difficult.
Our largest instance has over 20 million users.
They're not running it on a single-est Raspberry Pi.
Let me put it that way.
This is spread across data centers, across continents, even,
and yet it feels as a single instance to the users.
So, Nexot is, well, scaling is a solved problem in that regard.
More questions.
Yes, in the back.
So, our engineers have a lot of, like, decision-powered themselves.
That, I mean, we structure a company very much like an outsource community.
So, a lot of the decisions are low.
So, yeah, the question is, how do you balance features for sustainability?
And, et cetera.
And, of course, there is a grey area there, of course,
when is it polishing and existing feature?
When is it completely new, et cetera?
By and large, often big features don't need a ton of people.
For example, AI team is less, about two FTE.
So, all the AI stuff that you've seen is two people.
Yeah, and we're a company with 130 people.
So, but this is very fancy.
And we talk about a lot because we're actually competing
and a lot of these capabilities with, well, Apple, Google, Microsoft,
and, as a functionality, you can do that with Nexot.
Of course, we're not building our own LLMs.
That's not possible with two people.
But we're using, we're standing on the shoulders of giants here, right?
We're using all the technology that the people here at Foss Dam,
and many other people all over the world are building.
And we're taking advantage of it.
We don't do office ourselves.
We integrate what our friend said, call a board at us, et cetera.
So, that's one part of the answer where you think, like,
oh, they are spending all over their time of features.
Yeah, we do features, but this is not always as resource
intensive as you might think.
And we're using a lot of tech.
Now, the priorities that the engineers got,
we try to basically just say these are priorities.
And the first is basically fixing issues, mostly for customers,
but also from the community.
So, backfixing is the number one priority.
And I would say 70% of the time is actually spend on that.
Yeah.
Optimization performance.
I mean, do you call that a feature?
I didn't really talk about performance at all,
but each of the releases had a ton of performance work.
And that's always very important, of course.
It needs to be fast and stay fast.
The second priority is then features,
because we need, you know, our customers ask for things.
There are tenders that have certain requirements, et cetera.
So, if you want to keep hiring people and grow,
then you need to also develop the features that are needed for new customers.
And the third priority is, of course, working with the community,
getting features from the community merge, reviewed, et cetera.
So, bug fixing is priority number one, effectively.
But, of course, I'm not going to list here,
the 6,845 bugs we fixed because nobody gives you shit.
At least, I don't think most of you want to hear that, right?
So, I talk about the features.
Doesn't mean most of the work goes in that.
Any more questions?
Yes?
You're talking about governments integration.
How much adaption is there already going on?
Is it like, did you cut some or just try to build a future political government?
Or are they already using it?
So, tons of governments are using it.
For example, and I always love this example.
The European data protection supervisor,
so the organization that, as in your EU level,
supervisors, all the local data protection authorities,
they're using next slide.
And they're recommending everybody to do so.
So, listen to your data protection supervisor, please.
Europe, there will be nice.
But, I don't know.
Many of them I cannot talk about.
I mean, a lot of customers are twitchy about, I don't know.
There's probably a lot of lobbying.
There's a certain company from Redmont that has more lobbyist and Brussels than we have employees.
So, I cannot always name the names,
but the European Court of Auditors, there are several parlaments.
Half a dozen ministries are foreign affairs.
Hundreds of cities in Europe use next slide.
But again, they don't make noise about it because, oh my God,
if something breaks, then you have Munich all over.
So, a lot of it is under the radar,
but we have thousands of customers,
and we don't sell anything under a few hundred users.
So, they're all on the bigger side, so to say.
And that's federal government,
state, strategic whole-stein.
Thankfully, it's very willing to talk about the use of next slide,
and open-source, etc.
So, they use next slide all over the state,
and there are many other places.
Yeah.
Yes, next question.
Yeah, so we don't have any repeat the question.
Sorry, squirrel.
The question is, how do you manage this community versus company balance?
Yeah, it's a tricky one.
So, we don't have any formal things,
at least not like on the outside in.
We have a, what's it named?
The name relates, well, there's a Frank, of course.
But, no, there's a group of people who handle,
like, conflicts and such.
I kind of think of the name.
There's some kind of complaining,
board thing.
But otherwise, like, our approach is simply to work in the open.
So, like, if you want to know our roadmap for the next release,
I mean, there are boards that are in GitHub,
that are completely open.
All the issues are in the open.
All the pull-to-quest are open.
And we treat community pull-to-quest equal to employee pull-to-quest,
at least mostly.
And I think, by and large, that has resulted in fairly little,
you know, friction, at least on a development level.
Of course, when you say, well, how do you treat future requests from home users,
versus businesses, that's a different thing.
I mean, the businesses pay as money in the home users, of course,
don't.
So, as management, we have to make sure that every, you know,
release, there is at least a number of things done for private users,
as well, because, after all, back in the day,
we started next slide.
It's, we personally care about privacy.
And privacy, as I think, people have not companies.
So, if we want to succeed in a mission,
we actually have to build features for home users,
because you're the ones who we do all of this for,
fundamentally.
Yeah, all personal level.
I hope that answers the question and times up.
I have to leave it here.
Thank you all very much.
APPLAUSE