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How AnyLog and Akave are Redefining Web3 Data Infra with Filecoin
Recorded: March 17, 2026 Duration: 0:48:10Space Recording
Full Transcription
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Music Music Music Music Music Music Music Music Music Music Music Oh The Music Oh I'm going to go to the next video. Music Thank you. I'm going to go to the next video. Music Thank you. I'm going to go to the next video. Hi Daniel, Hi Roy.
Hey. Hey, how's it going?
Yeah, we don't for only 2 hours.
We're going to have the hour moderator.
So, just waiting for several seconds. Oh Hey, Rony.
Hi, Rony.
Hey, Rony.
Hey.
I'm just hearing the music.
Hi Oli, do you think we can start?
Uh, me too. Uh, me first, I'm interested interested in music.
Sounds like the background music is still going.
Sounds like the background music is still going.
Ok, let me install the background music.
I can hear you.
So let's make a good system happen. I Okay, nice. Good morning, everyone, and welcome. Today, we are diving into something that's becoming increasingly important for Web3, I would say, and how real data actually makes its way from the edge into decentralized
systems without relying on centralized cloud or providers.
Because the reality is most applications still depend on AWS or Google Cloud somewhere in
the stack, and that creates a gap between what web3 promises
and how it actually runs uh today's conversation i would say is about closing this gap so we are
joined by two teams working directly on this problem daniel from akawe and aka is building
s3 compatible cloud infrastructure on top of the centralized storage,
making it easy for developers to use Filecoin without changing how they are built.
And Roy from Anylog, focused on connecting devices, sensors, industrial data source
into a queryable data layer that can operate across distributed environments.
So I would say that the most important things as of today are the reliability,
sovereignty with Filecoin as the underlying layer.
So I'll let both of you briefly introduce yourselves and then we'll jump into it.
So yeah, Daniel, could you please introduce yourself and tell us about Akave, what's the role,
why it's important as of today, especially in this era of enterprise adoption of crypto and overall market conditions and how it fits.
Yeah, of course. Daniel here, CRO and co-founder of Akape. We built out Akape Cloud
as our first product offering. It's our flagship product, and it's an S3 compatible object storage
solution that provides data first teams with data infrastructure meant for the modern day.
So although it has an S3 compatible interface that allows it to look and feel like you're
interfacing with Amazon, it's actually fully decentralized on the backend and comes with all the advantages
of the blockchain primitives that are built in. We have an integration with Filecoin. I used to
work at Protocol Labs on Filecoin network growth. And that integration with Filecoin gives us an
added layer of redundancy and durability. And it comes with all the proofs that both Filecoin PDP and Filecoin ProRep
provide to anyone that's looking to store in decentralized storage.
And so what Akave allows for people to do is store in a really easy way.
It has been historically difficult at times to work with Web3 technologies, and we make
that really easy.
We come from enterprise backgrounds.
We try to make it so that it's a seamless experience.
We actually just released our GUI a few months ago.
So you actually have a console now
that you can interface with
where there's a drag and drop solution
and you can see the proofs right there in the console
that are tied to your data.
And so it allows you to have full control of your data all the advantages of the blockchain parameters but with the ease of use
of some of the historical web2 companies out there
great thanks for this introduction and how would you describe
And how would you describe why Kava Cloud is important, especially today for enterprises?
Yeah, so there's a few different reasons that customers switch to us.
One is the cost.
So we're able to reduce infrastructure costs by 50 to 80% compared to Amazon S3.
We also provide no egress fees.
So you actually have full control over your data.
You can, because we're not a central cloud
and we are inherently distributed,
we're not locking you in to a single provider.
And so if you wanna move your data around, you are're able to do that you can share your data easily you're not charged exorbitant egress fees
for that data movement and we also come with security guarantees that you wouldn't get from
a traditional cloud so the proofs that i mentioned before with filecoin we also have them with a cafe
and so you have these guarantees around your data being stored in an immutable way.
All of the metadata that gets stored with Akave and Filecoin, all of that gets brought on chain.
And so you have a immutable ledger that's tracking every single file, every single transaction, every single time someone accesses your data.
You can see that on chain.
And so it allows you to have peace of mind.
And also if you're in compliance heavy industries,
you can prove that there's these audit trails
that are tied to your data.
And so depending on your industry,
you might have the advantage because of costs.
It might be an advantage because of compliance.
It might be an advantage because of ease of portability.
And so it really depends on what you're looking at
there but for all those three reasons we've seen a number of customers switch to Acabe and we're
excited about all three of those use cases as well. Okay thanks a lot and as well as for Roy from Anylog, could you please introduce yourself and tell us about why Anylog, what it is, and why people should care?
Yeah, so I'm Roy Shadman. I'm a system architect at Anylog.
I lead all initiatives related to our AI enablement, our blockchain security integrations,
and a lot more. And a quick overview of what Anylog does is that we develop software that
lets you query and interact with distributed data, whether it's telemetry data generated by sensors or
video files and images generated by cameras, as if the data is stored in one logical system.
And so the value proposition here is that rather than building these complicated pipelines
that move the data from the edge where the sensors are generating data and where the
cameras are generating video streams all the way to the cloud and building these complicated,
expensive pipelines, our software allows you to keep the data on localized edge nodes.
And when you want to query that data,
you don't need to know where that data is.
All you do is execute your traditional SQL query to an AnyLog node,
and we provide you a unified interface
so that you get the unified results that you're expecting.
And so the advantage here is that when you transition
from your typical Amazon-based or Google Cloud-based solution, your traditional queries
and infrastructure are existing and they still persist. But instead of pointing your queries to
a database in the cloud, you point your queries to an Anylock node and our software satisfies
the queries
as if all the data was in the unified database
without having to physically move the raw data
to a centralized location.
Impressive, thanks a lot.
For anyone who is new,
why you decided to partner with or collaborate with Akave?
you decided to partner with or collaborate with Akave?
So I can start. So at the edge, you are obviously wanting to push data to edge nodes and the edge
isn't the cloud. You don't have unlimited resources. And so over time, the amount of
capacity the data is taking up slowly starts filling up the capacity of the edge node.
And so there's limited storage.
And one of the things we wanted to enable was to provide these retention policies that let users define when the data is five days old.
it doesn't need to be at the edge because it's not being used for real-time operation.
It doesn't need to be at the edge because it's not being used for real-time operation.
And so we can define an Anylock retention policies that dynamically offload the data to
external storage provider. And in this case, Akave plays a really nice role of being a provider
that can be hosted anywhere. And we can interface with Akave as if they're just a standard S3 bucket for us.
And then the second goal was we didn't want to just push data to an S3 bucket in Akave.
We wanted to also continue being able to access that data via the rich metadata that the data has.
So, for example, if there's a video and in that video there's an inference of
maybe 50 cars and 10 people and or maybe a user now a person not wearing a hard hat
at a facility, we can also push one row into a SQL database that summarizes with the contents
of the video files. And so when we want to query, give me all the videos where someone wasn't wearing a hard hat,
we can still satisfy that query
and pull that specific video file, not all the files,
but just that specific video file that satisfies the query
and give a seamless unified view of all the data
while keeping some of the data at the edge
and offloading older data to a copy.
I appreciate it so much.
So, yeah, that's a really great point.
And, yeah, I completely agree.
And a lot of Web3 teams still default with centralized clouds, right?
Sometimes out of convenience, sometimes because there isn't a clear alternative.
However, I would say that aka
completely changes this and we've seen that if any outages like aws cloud player
uh they uh affect uh a lot of web3 companies and what's breaking in that model and why does it become
a problem at scale?
Do you think it's becoming unsustainable and how does your joint solution fix it?
Thanks. Yeah. And just to also add to what Roy was saying, our focus has always been primarily on the
storage infrastructure.
So for us to have a solution like Anylog that allows for the end-to-end pipeline to run
at the edge without touching a central cloud location is pretty powerful. And what Anylog allows for users to do
that are querying into Akave
is getting those insights from data stored on Akave
that Akave might not be focused on immediately.
So the storage is where we spend the majority of our time,
the compute and the insights that you can gain at the edge,
that is where any log comes in
and is able to provide what Roy was mentioning
about the seamless SQL queries
as if you're querying into a central location,
but it's really fully distributed.
So that's, I guess, why it's such a complementary solution.
But why, I guess, why it's such a complementary solution. But why, I guess, to your question about not wanting to store in a central cloud location, I think there's a number of reasons.
You mentioned downtimes.
I think that's a good point.
With central clouds, you're limited to certain regions and availability zones.
So whatever regions that AWS operates in, for example, those are the only places that you're able to store your data.
And if anything happens to those locations, I mean, you're seeing it with some of the conflicts right now in the Middle East.
There's certain locations that are being targeted.
And if any of those go down, then the whole region is out of power, doesn't have any sort of data center infrastructure to back that up.
And so there is an inherent advantage to having a decentralized system that has different data centers and data infrastructure not tied to a single provider
that allows you to make sure that when something happens, whether it's a power outage or if there's a conflict
or if there's maybe even a certain entity or government
that's targeting your own infrastructure,
that there's going to be other options for keeping that data available.
And with a decentralized approach,
you actually have multiple data centers
that are able to serve that data
that come from separate providers.
So the uptime and availability, I think is a big piece.
The other piece is really the restriction that you feel
when you store your data
in some of these traditional providers.
They make it really easy to move your data in.
That's always been the case.
Easy to store all of your data with a certain provider. But as soon as you want to take your
data out or move your data or share it with anyone, then you hit those egress fees. And so
even, you know, we talked about S3 being $23 per tip per month. We can come in at 50% cost.
And on top of that, when you add in the egress fees, that $23 per tip per month goes up to $90 per tip per month.
So if you're moving around hundreds of terabytes or petabytes of data, it almost becomes impossible to get that data out. And that's more or less by design
so that they can kind of lock you into a single vendor.
So there's a few different reasons
why you might not want to store in a central cloud location.
For the most part, that was the only option that was out there
when people were moving from on-prem to a cloud-based system.
But now there are other modern solutions out there
that don't lock you into a single vendor
that provide you with the same kind of advantages
of a private cloud.
We actually have full control of your data
and you retain the keys and you don't have to worry
about being locked into a single vendor.
Amazing, yeah.
That's, I think, a cover is a really impressive solution in such turbulent times
and with, especially for anyone who is seeking compliance.
Thanks, Daniel.
That means a lot.
Yeah, and Roy, I would say that could you please walk us through the actual data flow?
A sensor wakes up in a remote location.
What happens next?
Yeah, so when a sensor wakes up, it starts producing data,
and that data is typically sent to some edge node or hub near the sensor.
The typical workflow would be that people use today
is the data sensor generates data, it goes to an edge node,
and maybe there's 100 or 1,000 sensors and many edge nodes.
If we want to access that data today,
people typically will move that data to another hub,
and it'll slowly make its way all the way to the cloud.
When it reaches the cloud, it's processed and organized in a centralized database.
And then we start interacting with that data.
But the issue with that is that if the data latency of moving data all the way to the cloud.
And with any log, the sensor data is moved to the edge node and that's it.
That's where the data stops moving.
where the data stops moving.
From there, you can query your data that spans
across multiple edge nodes as if the data is
in a centralized database without needing to physically
move the data to the cloud.
And so that's what Anylog lets you do.
You deploy your software or Anylog on the edge node,
move the data to the edge node, and that's it. When, because of the capacity, again, retention policies let you offload
aggregates of the data to the cloud.
So you don't have to move all the data, just what's important to the cloud or
to Akave, but needless to say is the key advantage here is that you get immediate
access once the data is pushed to the first edge node, you get access to that data, and you can query that data
and bring it to your application.
Thanks for this really illustrative example.
And building on that, what does Filecoin enable here
that a traditional Edge and cloud setups simply can't
so for us for yeah this is maybe for us we interact we take the data and our customer
will define retention policies that say i only want this data for five days or 30 days or 60
days on the edge node.
Afterwards, that data is not necessary and I just want to store it for compliance.
And so our, so any log pushes the data to Akave and then Akave handles the file coin integration from there.
I appreciate it.
And Daniel, would you please probably stand this with your expertise?
So it would be great to hear from your point of view.
Yeah, yeah. So maybe to continue that flow that Roy was mentioning, when the data gets to Akave,
we obviously we have this S3 compatible interface. We have an SDK that transforms those API calls into something that
our blockchain can read. And so all of the data gets chunked into one megabyte pieces,
encrypted and erasure coded across 32 nodes, all the metadata gets brought on chain. And those,
that erasure coding schema allows for 60 nodes to go down and you'd still be able
to get your data back seamlessly so there is a level of redundancy and durability durability
that's built in just to just in the akave storage itself but then you also have on top of that the
integration with filecoin that allows you to have another tier that provides added redundancy, added durability.
And with Filecoin, there are proofs
that are tied into proof of replication
and proof of data possession,
sometimes referred to as Porep or PDP.
Both of them allow you as a customer or a user
to not have to trust the provider that's storing your
data and just have trust in the proof in the actual technology. And so you're able to see
with these content identifiers, these CIDs, where your data is being stored, that it's still stored
with a certain provider that it hasn't been tampered with.
And so you get all of these guarantees that are visible to the user, whereas sometimes in traditional clouds, it's a bit of a black box. With Akava and Filecoin, you have very clear
visibility into your data being tamper-proof. And so for certain use cases, it's very, it's a it's a very good value prop,
both on the compliance side and on the security side, you get these guarantees around your data,
having been the same data that you put in there. And then when you want it back, you can you can
obviously get it back with the guarantee that you have the CID that's bringing the data back to the user.
So you know that whatever piece of content
that you're retrieving is tied to that content identifier.
And that means that you know that that piece of content
is exactly the same piece of content
that you put in originally.
Yeah, I appreciate it.
Yeah, I agree it. Yeah, I agree.
That's really important, especially as of today.
So, yeah, could you please give us, like, real-world examples that people can picture?
What do I mean by this?
Something that makes it clear why this matters beyond just infrastructure.
this meant there are matters beyond just infrastructure.
So because people are probably who are not aware
of infrastructure or not that deep.
So maybe something like more high ground
or just beyond infrastructure.
For us with Anylog, a really clear example are IoT companies.
So companies that are generating a lot of data at the edge, they might have videos or
sensors or geospatial data that they're generating in edge locations.
And they're spread out.
Where that data is being generated is not in one place. And so to send
all that data to one central location is inefficient. And what Anylog allows you to do is
capture that data at the edge and then query that data at the edge as if it was a central location.
So the performance is still the same. It looks and feels the same
way as if you were querying into a central database, but it's completely distributed.
And then because Kaveh is obviously not in one location, you also get the advantages of having
the persistent storage stored closer at the edge. And so for these IoT companies,
they get added performance, they don't
have to do the round trip that they would normally have to do to one location, and they can gain
insights at the edge quickly without having to pull from some central location. And so there's
performance improvements, there's efficiency guarantees, and that obviously will inherently lower your cost.
And so for any IoT companies that are operating with a lot of data at the edge, this is a great
use case and a great joint solution that any login at Kaveh can provide you.
Impressive. And I also want to add something on top of Daniel's as well.
So the other big advantage here is the simplicity.
So rather than, again, building these complicated pipelines that moves the data to the cloud,
the data just stays on the edge node.
And all you need to do is deploy Anylog and push your data to the edge node running the
Anylog software agent.
And that's all you need to do.
And that's, and you get the entire basically cloud-like data services at
the edge without having to pay for the cost of the cloud.
The other advantage that I'll point out is that it scales horizontally.
So typically as your systems grow and you have more and more data and more data
sources, generating data, you typically need larger cloud infrastructure, which
obviously can increase your cost exponentially.
With any log, you just deploy another node with the software agent on it and start
pushing the new data sources to that new edge node.
And so as your system grows, the way you scale is just by deploying more nodes, not completely
changing your infrastructure.
So you get this added benefit of simplicity.
You just deploy the edge node and push data to that edge node.
And as you grow, you just deploy more edge nodes to satisfy the capacity that you need.
Great. Thanks a lot.
And yeah, Roy, that was really great.
Would you please also maybe expand with more possible use cases that everyone could explore
or something like this that people can use beyond this simple infrastructure.
Yeah.
So I think in a dare to, I think we're releasing a video of example with security cameras and video and live video streaming.
So it'll be posted on YouTube.
I think maybe Falcon, you can share the youtube clip as well but basically what we're showing is that with any log you deploy edge nodes you stream video
cameras to any log any log can handle any kinds of data whether it's telemetry or video files blobs
etc but in this case video is being streamed into an into any nodes. There's an AI model, so we're using the YOLO v5 model,
it's sitting on the same edge node. That AI model can also sit on a dedicated edge node as well,
but in the example it's on the same edge node. So video is being streamed into anylog. For every
frame, anylog is pushing the frame to the AI model and retrieving the inference. And we log every inference result to a SQL table, to a SQL database.
And essentially what happens is every one minute clip of the video stream is also being stored and being pushed to a COVID.
So we're recording two things.
We're recording the metadata.
So what was in the video?
And we're also recording the
physical video clip as well so the metadata isn't being stored in a sql database the video um video
is being stored in akave and you can interact with this video files with sql whereas today you would
have you would be limited to prefix driven search You would have to do use specific file names to search for the videos.
Whereas with any log, you can say, I want to know how many, I want to know
all the video files where five cars were in them.
And any log will give you a unified view and actually a GUI interface to query
all the video files and watch them as if the video files are stored in a centralized database,
but really the video files are being stored in Akave cloud and the SQL metadata is being stored in a SQL database on the edge node itself.
Yeah, that's really impressive.
And I would like to mention that Anylock is a proud partner of the Linux Foundation.
That's really amazing.
And I know that you help industries like smart cities, industrial energy, oil and gas.
So if you could put in a few words, why would anyone choose you?
What's your edge?
So I think people choose us for the simplicity and the scalability.
The way our software works is you just deploy our containerized software, and that's it.
We don't need to have these complicated pipelines.
With our new MCP server service offering that is now,
so an MCP server now runs on every single AnyLog or Edge Lake instance.
Edge Lake is the open source version.
You don't need to have BI engineers,
so you don't need business intelligence engineers.
You don't need BI tools or pipelines.
You can just query your data.
Your data remains in place, is distributed.
It's more secure.
You own the data.
You don't have to pay for the egress costs.
And you can create dashboards using any LLM of your choice
by pointing queries towards an Anylog MCP server.
And you can do anything you want with your data
without all the exorbitant costs
of the cloud yeah that's spot on that's what we are here for for this decentralized system
that's really great so now as the question about compliance I would say that compliance is a huge pain point.
For example, this is the things that everyone worries about,
GDPR, AI Act, and data residencies, and sovereignty itself.
So a question for Daniel.
How does your approach change the conversation for builders?
I think you're seeing this
very common theme in the EU
of companies not wanting to store with American companies,
European companies not wanting to store with data infrastructure companies
that are only
mainly operating in the US, but have infrastructure in Europe. And so there's been this
kind of shift in data sovereignty requirements and the EU AI Act, where there's people taking back their data and putting it into European companies.
But for Akava and for Filecoin and Anylog, that's not necessary.
So you can actually have, because of the inherent decentralization aspect,
a provider that is operating, it's a global set of providers,
a provider that's operating in the EU that has all of the advantages of running the software
of a Convair, Anylog or Filecoin and be able to keep that data within country, within region
to meet compliance requirements. And so there is not this, you know, central company in the U.S.
that's pulling the strings that might take your data back,
that might, you know, get insights from the models that you've stored with them.
And so these GDPR requirements and the data sovereignty laws
that are coming out in the EU, they're really kind of
the way that they're structured, make it so that the value prop of decentralized infrastructure
becomes really obvious for them. And so from a compliance perspective, there is a big advantage
to being able to know where your data is being stored, that you have this immutable audit trail, that you're not tied to a company that's in the U.S. that might take advantage of that data that's being stored with you.
fit really well, especially in the EU. I think there are some instances also outside of the EU
where compliance does really well with decentralized technologies that are bringing
the metadata associated with that data on chain. And because all of the metadata is tied to this
immutable ledger, if you are in a legal hold use case, for example, and you need
to ensure that the data that's being stored with a particular company, it's there for seven years,
sometimes we see that seven years is the rule, then you have guarantees that your data will be
stored for that amount of time. And those guarantees are visible and they can be seen through the technology on chain.
And so it depends on the use case.
EU is the most prevalent one and the most obvious one right now.
But there's other, obviously, compliance requirements that the bringing of the metadata on chain helps tremendously
because you have that kind of traceability
and data provenance that you wouldn't have
with other solutions.
Yeah, really that's, I think really helpful.
And the same question for Roy,
if you have any experience with compliance, the things that GDPR, AI, data, residency, et cetera, if you have this, could you please share it with us and maybe how Anylock can help with this?
Yeah. So one of the biggest concerns is when you move your data to another company's infrastructure,
you have to ask the question, well, where is my data being stored? Who's managing it? And how do
I know it's secured and not being accessed by people that I don't want to access that data?
And I think that's obviously a very important thing to be worried about.
But with any log, the difference is you don't give your data to someone you don't trust.
You manage the edge nodes or you use edge nodes that you trust and you push your data
to the edge nodes that are within your infrastructure and within your network.
So typically our customers are managing their own infrastructure.
They have their own sensor networks and they have their own networks.
And so by allowing them to keep the data within their infrastructure and within their networks, they don't need to move the data anywhere and they can satisfy the sovereignty requirements of no one can see my data but me and also still get the full
data services that you would need in the cloud, but now is being provided entirely by
AnyLog without actually needing to move the data outside of the edge infrastructure.
actually needing to move the data outside of the edge infrastructure.
Thanks a lot.
And probably the last question, let's start from Daniel.
Where do you see this technology, your collaboration
heading in the next 12, 18 months?
Yeah, maybe two things one um just because of this trend we're talking about compliance i think there's generally this um cloud repatriation happening where people are taking
back control of their data they see that there's other options outside of just storing your
data with a one company and so there's other options outside of just storing your data with one company.
And so there's this movement that you're starting to see, especially with all of the AI
companies that are popping up where their most valuable asset is their data, where they're
taking back control and starting to look at alternative solutions and you can do on-prem that's an option
you can also do a private cloud with any log in akava we kind of enable both so either way you
have the ability to not rely on just the the the big three and so i think because of that movement
and because you're starting to see this trend of repatriation,
there's going to be increased adoption and an increased search for alternatives out there on the data side.
And so that, I guess, poises us to be in a very good place for providing an alternative solution over the next six to 12 months.
And then I think just generally speaking,
the technology continues to get better.
It continues to get faster, easier to use.
The frictions that existed before,
you're not really seeing as much of those anymore.
And you're seeing actually in some cases
that the performance is better than what you would see with the traditional options out there. So I think between the general
trend of people wanting to take control back their data and the trend of the technology
improving quickly over the past 12 months and continuing to improve over the next 12 months. I see there's going to be a lot of
adoption coming for and just general interest in alternative solutions out there.
I appreciate it. And the same question for Roy. Where do you see, and like looking ahead, over the next 12 to 18 months, what do you
think changes, what becomes possible that is not today?
Your view on perspective or perspective on partnership or collaboration with Akave and
your, of course, personal project, Akave, oh, sorry, Anylog and your collaboration with Akave?
Yeah, I think there's two big things that we'll see a big paradigm shift in the industry,
and that's related to AI.
So I think the software, both Akave and Anylog will become major AI enablers for training and also servicing real-time inference.
So on the training side, these models need a lot of data.
Most of the data is generated outside of the cloud than it is in the cloud today.
And rather than having to centralize all that data, whether to the cloud or data center, which has enormous costs.
We can just use AnyLog and Akave as the infrastructure solution to first, to use AnyLog to query the
data that we want to bring to the training, and also use Akave as one of the data sources to
enable the training as well. So the key idea with our co-solution is that
we only need to bring the relevant data, not all the data, to the training infrastructure.
And on the inference side, it's about making inference more real-time. So for example,
if we have autonomous robots or some autonomous system, that system doesn't just want to operate on its own data, but it wants to operate on the data of the adjacent robots or the entire world.
And so we can't have a dependency where we move all the data in this world or across all the robots to a centralized location and only from there
bring it to the inference endpoint to make a decision.
And primarily we can't do that because it's not real time.
But with any log, robots can query their data
and the data of other robots and the data stored in Akave
as if the data is in one logical system.
And the key idea here is that the raw data never needs to move on the network.
Only the queries and results that need to move.
And this can actually deliver a true real time operational view.
Well, that's was, that's what's a really, really impressive.
So yeah, that's a great place to wrap.
And thank you both for joining.
It was really insightful conversation.
And for everyone listening, if this space is interesting to you, and it actually was really impressive to me.
Definitely follow Filecoin for more discussions like this around decentralized data infrastructure.
And of course, absolutely check out Akave and Enelo.
Both are building key pieces of what this future looks like.
And really, thanks, everyone.
Thanks, Daniel, thank Roy, and everyone, essentially, who has joined today.
Thank you, Ollie, for moderating this. Thanks for having us. Yeah. Great questions.
We will see you in next Falcon Space. Have a good day everyone. Thanks everyone. Bye. .
