🔺On-Demand Data Meets Web3: Turf X Avalanche

zeeve

Turf x Avalanche Talkshow | On-Demand Data Meets Web3 | Launch Your Avalanche L1 with Zeeve  Welcome to a special episode of Web3 Voice with Dr. Ravi Chamria (Co-founder & CEO, Zeeve) as he hosts an engaging talkshow on “On-Demand Data Meets Web3” featuring:  Dibyo Majumdar – Founder & CEO of Turf, building a horizontal on-demand data network for the future of AI x Web3.  Devika Mittal – Regional Head of Ava Labs (South Asia), sharing in-depth insights on Avalanche L1s and why they’re the preferred infrastructure for next-gen decentralized ecosystems.  🚀What you’ll learn in this talkshow: 🔺Turf’s evolution from gaming & esports into a robust on-demand data network powering AI and autonomous agent ecosystems. 🔺How context-rich data monetization is transforming industries like healthcare, defense AI, and more. 🔺Why Avalanche L1s are the ideal choice for sovereign appchains: offering sovereignty, scalability (up to 100K TPS), predictable gas fees, and unparalleled builder flexibility. 🔺How Zeeve empowers projects like Turf to launch, manage, and scale their Avalanche L1 networks with enterprise-grade infrastructure. 🔺Real-world use cases thriving on Avalanche, spanning RWA, DeFi, Gaming, Infrastructure & AI. 🔺Turf’s roadmap and upcoming milestones, including its beta dashboard for data agents and AI integrations.  🔥Key Takeaways: 🔺Turf is creating the context layer for the agent economy—autonomous, AI-driven, and multi-vertical. 🔺Avalanche L1s provide unmatched sovereignty, speed, and ecosystem support—beyond what Web2 or public chains can offer. 🔺With Zeeve, any project can launch its own Avalanche L1 in minutes—so builders can focus on innovation, not infrastructure.  Want to launch your own Avalanche L1 or appchain in minutes?

Transcript

00:00so hi everyone my name is ravi and i'm the co-founder ceo z and they on web3 voice we

00:23have a very exciting talk show talking about on-demand data meets web3 where we have very

00:28exciting guests dibyo majundar who is the founder of turf and devika mittal who is the regional head

00:34of ava labs so yeah so it has been you know we are very excited to partner with ava labs as well as

00:40turf and i'm very excited to delve deeper into this talk show today so first you know before getting

00:46into learning more about turf and how we have launched support builders i would request dibyo

00:52and and devika to introduce themselves starting with dibyo tell us a brief about yourself how

00:58you started your web3 journey and how your web3 journey has been so far absolutely so hi everyone

01:03this is dibyo i'm the founder and ceo of dove and yep about my journey it's some things that started

01:10in 2017 started off initially contributing to ethereum with consensus and that's where everything

01:18started i started off as a developer obviously and contributed to the protocol level stuff and

01:23taking it further i was obviously at that moment i was in college and taking it further in 2021 i

01:31started my own venture in studies that's a recent life fundraising stack and that's that's something

01:38that i have scaled to 36 million dollars so coming from that particular aspect my web3 journey boosted up

01:45and by late 2023 i started my journey with turf and that's what we are building at this moment started off

01:53with gaming now getting into the data infrastructure towards the scale so that's a very exciting journey

01:58in dibyo and i think it must be a big inspiration for a lot of budding entrepreneurs who are who are

02:03seeing this talk show so now you know a bit about yourself absolutely hi ravi thank you so much for

02:10having us very excited about talking about you know avalanche l1s and specifically about what the

02:16dibyo is building with turf here so i'm everybody i'm devika i'm the regional head as ravi said of

02:20ava labs here in south asia our job is really to find the best projects and to support them and to

02:26have them build on avalanche uh whether that's on c-chain or whether that's on their own l1 depending

02:32on the use case so i'm here today to really talk about you know what dibyo is building with turf and

02:36kind of all of the exciting pivots they've had on the way and you know why we're really excited to have

02:40them in the in the elven ecosystem no absolutely i think that's a great thought and and great

02:47execution as well so now getting on to turf debyo last when we talk you were big time into gaming and

02:54esports especially a lot to do with data analytics and and how bringing how you know analyzing the

03:00data in gaming and esports and use that for the purpose of for the gaming ecosystem but from that

03:05journey now you have pivoted into a full-fledged horizontal data network and my assumption is that

03:12you know you're learning while building the gaming and esports piece has been quite instrumental in

03:17building this data network so can you give us a bit about the story behind this evolution that happened

03:24how you pivoted into a data network and what has been your learnings that you know shaped the turf

03:29network exactly so this is something really cool that happened when we started off with gaming

03:35powering more and more engagement to games with esports and competitive gaming aspect right

03:40we were curating the competitive culture into the gaming ecosystem so from that where we have

03:45curated nearly 400 000 plus gamers distribution network to now getting into data is a very i would

03:52say a pivotal space to be in right so what happened initially was we were doing a lot of competitions

03:59but eventually in gaming space the revenue that's getting generated was not that much higher what we

04:05did is like hey what all we can do to actually bring on better revenue to our systems that's where

04:11the whole data aspect came into the picture hey we had a lot of gameplay data people competing against

04:17each other what exactly we can do with it so we looked into with more ai coming into the picture where

04:24most of these data these days are getting consumed by ai for training or post training context right so

04:30we thought like hey humans are playing these games right we have the recordings can we create embeddings

04:36which can be used in different verticals so that's where from the gameplay data we took so humans cognitive

04:44intelligence is embedded into their gameplay so we took that embeddings and then helped a robot called

04:50phantom mk1 to train their train their robots who are going to war right so this kind of data sets

04:57help them to actually train their whole models so this experimentation and at the same time the same

05:04gameplay data like when you are playing it's an action reaction time that's already already there

05:08right so that same action reaction time can create a separate embedding that can help in the healthcare

05:15industry to train like hey if a person have adhd or not you can detect it right so these kind of

05:22healthcare ai and defense care health defense care ai have different use cases but is powered through a

05:28single type of data right that was the moment for us that was the influx point for us and whenever we

05:34did all these deals this was purely one-on-one deals there was no distribution network that can facilitate it

05:41either we have to go to data brokers or there is no different options right so we thought like why

05:47don't we productize it productize the whole funnel in a way that anyone having but any kind of data can

05:55distribute it in our platform and any ai this whole agentic infrastructure right like right now web surfing

06:02is done by agents right agents are doing everything rather than humans going and doing particular things

06:08so they need an autonomous infrastructure that can actually bring context to them so that's something

06:14that actually got us the motivation and the early pmf around this data pipelines got us more conviction

06:22that hey this thing can can be productized and given my experience in the web3 space to be honest

06:28we know how to build trustless ecosystems that can actually change the change any industry by making

06:35things automatic right so bringing those experiences together we are now here with a towards a

06:41horizontal expansion in terms of not just gameplay data but also looking for forward towards e-commerce

06:47social interaction data but everything is directed towards human parameters got it no i think that

06:54sounds very interesting first i thought that you know it was still pertaining to data that you gather

06:59through gamers and then use that or expand that into various other use cases like one of the healthcare

07:04use cases you mentioned about adsg but now what yes what what i gather is it's a full-blown

07:11on-demand data network and spanning across verticals and at the same time there's a data monetization layer

07:17which again is a is something which is very exciting especially you know a lot of privacy data that is being

07:23generated not shared because there's hardly any monetization model today in the web2 space

07:28and at the same time you know this data is is very valuable for people who want who who can use it

07:33to either build something or if they are building something use it to fine tune it or make it better

07:39and and create newer products and newer models yeah i know it's it's absolutely very very interesting

07:45yeah so devika you know as we have heard from debio about the demand on demand data network

07:51and the turf has used avalanche l1 to power their decentralized network and we are you know very

07:58excited to partner with turf to as a infrastructure provider to launch this so from from the l1 stack

08:05perspective and and it's going to be helpful for other builders who are looking to launch their own

08:09decentralized networks as to what are some of the core tenets of avalanche l1 and other technology

08:16components within the avalanche ecosystem that is a great fit for launching a decentralized network

08:21like turf yeah that's a good question uh i'm going to give some answers and then debio actually i would

08:26be curious to know if there's anything that i've missed that you think was important for you

08:31so absolutely so i think the biggest one is sovereignty right i think when somebody like debio

08:37is building something like turf what they really don't want is putting that i mean they can

08:42right putting their data or like millions of you know millions of data points on a on a public

08:47chain right a there's congestion in the network b there's variable gas fee c there's a lot of like

08:52kind of competing things and you know maybe sometimes the time to finality might be slow because there's

08:55too much congestion on the network which is what can happen on public chains especially the the larger

09:00more popular kind of ethereum of the world right with an avalanche l1 you don't worry about any of that

09:06you have your own chain you own it you decide what you want to do with it if you want to have

09:12a token you can have a token if you want to be gas free you can be gas free right you can abstract

09:17away the gas layer if you want to be public or private you can do that if you want to be

09:22permissioned or permissionless you can do that if you want to allow only certain validators right

09:26as permission like you can do that if you want to have only one or one kind of product on the

09:32chain you can do that you want to have a million you can do that too right you literally have your own

09:35avalanche c chain or your own ethereum or your own solana and it's yours right and it works

09:41right it's been battle tested you're not building from scratch you're not trying to figure out all

09:46of this thing because you want this sovereignty you want to set up the chain the way you want

09:49to set it up and you a and the second thing is you want it to be able to handle your data right

09:53so a it's sovereign second can it handle my load right but then avalanche l1 you know depending on

09:58how you're setting it up you can go anywhere between 4500 transactions a second to almost

10:02100 000 transactions a second right i think it really kind of depends on how it's being set up

10:07what the tools you're using in the toolkit so so again when you're looking at something like turf

10:11you need something that can handle millions of data points right and that can actually put them

10:16on the block in real time without any congestion without any delays that's incredibly important

10:21for the network to work and for there to be you know strong trust in the data that's been put on

10:25the blockchain so i think that's the second one i think the third one and if you tell me if this

10:29isn't true i think we just make it super easy you know it's you have an l1 and you can choose

10:34you know various bass providers so blockchain service providers zeev is you know one of our

10:39favorites and my favorite so you know you work with zeev and zeev helps you set it up and essentially

10:43it's an aws model right you have blockchain but it's kind of an aws model you pay a monthly fees and

10:48everybody they run it for you they manage all of it and you can really focus on building so it's kind

10:53of like having you know microservices and gaming uh going back to the viewers kind of conversation

10:57about gaming they're all like microservices and payments right you want to build a shopify website

11:02but you don't want to build the shopify infrastructure you want to just build the website you want to

11:06sell your product and then you want to sell your product but you don't want to figure out how to

11:08do payments so then you want to use plaid right you want you want to abstract away the core of what

11:14it is that you're not building and what you're not selling when you're for example a website

11:18and when you're a business here with turf you know here turf can really focus on building what

11:24they're building right which is the platform without having to figure out how do we run il1

11:28what do we do with it what do we manage what are the validators can it handle my load will it break

11:33down will there be any network you know interruptions i think that is i think i gave a longer answer than

11:38i normally give but i think these are the really big things that i i think really make it powerful so

11:42sovereignty right handles the load and three like pretty easy so you're like correct me if i'm wrong

11:47be honest with me tell me if i'm bullshitting and tell me if i've missed something that's absolutely the

11:52scenario and one of the things that i can totally resonate with the congestion aspect that you

11:56mentioned let's say if there is an elven right and you are deploying your whole infrastructure that's

12:01very much use case specific and still your transaction that's getting submitted it's competing

12:07with the decks because just there is a huge volume that's coming in right so being use case specific i

12:13would say having the control over a network and at the same time executing things in a decentralized

12:19manual is something that we got and one of the crucial aspects i would say like in this whole funnel of

12:27having the customization that we need is what we got with avalanche elven ecosystem so we are evolving

12:34like a pre-compared distributed network state right so just like hyperliquid all the data pipeline

12:40infrastructure from int and destructuring to aggregation to transformation to loading right

12:47everything's our microservices that are pre-compiled into the virtual machine so these things are

12:53something that we need control on so so that we can make sure that the whole process is smooth and at

12:59the same time i just don't want that if there is a huge volume that's coming on to any of the decks

13:04into the network i'm facing errors for that so uh yep i totally resonate with that and love to be

13:11and obviously the end end goal the ecosystem that that's in-house right that's something that i totally

13:17vouch upon right no i think debio you and devika i think you have made excellent points about the usage

13:24of elven stack here like devika mentioned about sovereignty and then you know your choice whether you

13:29want to launch a complete permissionless chain to permission and somewhere in between and she also

13:34mentioned about high throughput low latency kind of networks which you can do tens of thousands of

13:40dps easily on avalanche elven stack and she also mentioned about how easy it is to deploy and

13:46launch and build and get to go to market and and debio as you rightly said the whole concept of

13:51launching an app chain or application specific chain is to see how you can have your own dedicated

13:56block space and you are not competing with block space on a public chain in addition to that i would

14:01love to you know because we work with so many builders who are launching their l1 with us

14:05just like to add a few more points about l1 stack one is the whole validator network so as turf is

14:13building a decentralized network of data and data being something very critical and highly valuable

14:18entity having a very decentralized network over a period of time becomes very important it's very

14:23easy to set up a validator network launch your own validator within the on the chain and and making

14:28it more and more decentralized we in fact at z you know we provide one click validator network so anyone

14:33as you know turf is going to open their network for external validators to launch their validators

14:39they can use easily use our platform in just one click without any tech knowledge to you know deploy

14:45their own validator node and strengthen the turf ecosystem then you know in your app chains and

14:50application specific blockchains you have predictable gas fee you know you can have your own

14:54configurations and one of the challenge that has been taught time and again is that how user experience

14:59is still a challenge in web3 applications now with today having account abstraction having your own

15:05dedicated app chain where you can have your own set of configurations depending on your use case

15:10i think it makes it very very easy for someone to have a chain which is very high on user experience

15:15highly configurable to their app chains and at the end of the day you know it serves the use case that

15:22the chain has been built for in addition to that you know we have 60 plus integrations whether it be

15:27interoperability with other networks or other other ecosystems whether it be account abstraction

15:32interrupt oracles or on-ramp off-ramp any kind of because each startup depending on the use case

15:39does require some external integrations from time to time as they move on and with all these

15:44integrations available for your avalanche element stack i think it makes it super super easy

15:49and to top it all i would love to mention here that avalanche ecosystem support is top notch you

15:55know once you are once you plan to build within the avalanche there's a massive ecosystem support

16:00there are grants incentives there are experts who are going to help you in your journey while building

16:05the product while taking the product to the market you know interactions with other ecosystem players

16:11everywhere i think there's a massive massive avalanche ecosystem support that you can you know lean on

16:17yeah so just to add few points to what what devika and debio mentioned now moving forward so debio we

16:23learned about turf network we also learned how you pivoted into creating an on-demand data network which

16:29is ai driven so one you know would like to understand more about your core value proposition and how

16:35it differs from a traditional data network and in addition to that you know you have you have described

16:41turf as as more of more than a product it's like a paradigm of of how agents interact with the data

16:47in the in the data network so can you give us a use case or an anecdote that illustrates you know

16:53the impact of turf when it's just working behind the scenes absolutely so this is something really cool

17:01that happened right so whenever we talk about our product right it started with a thesis of human

17:09interactions are going to change right human interactions are going to happen through agents

17:13rather than human directly going and web surfing agents are going to do that for them right so

17:19when we see the agentic infrastructure scaling right what what exactly agents do right whenever

17:26someone is developing an agent what exact two of the things two fundamental things that they need to

17:32care about is what an agent should know and what an agent can do right the intelligence operations

17:40and the context so we are the context providers so whenever an agent need any specialized data context

17:47specific data they need to rely on certain specific data sets that can be consumed to and help them to

17:55do some operations so whenever it comes to the intelligence part obviously with all these gpts into the picture

18:02right all these lms that's getting developed and any of the neural networks they got the intelligence part

18:08sorted and still from zero to till date everything in the ai space happened just because of

18:15algorithmic shifts at the same time having an abundance of compute right we all have that what

18:20we don't have is the context specific data right every time you search in claude they are search

18:27and do a deep research they are searching in 350 plus mcp servers across the internet right they have access to

18:33right or they are consuming multiple data funds from multiple data brokers to actually serve your answers

18:40so what we do is like whenever even companies like claude and open ai they are having a human team

18:48that's actually gathering data from multiple different funds for them so whenever this whole operations

18:54need to be done by ai agents if there is a human being who is bringing context specific data for them

18:59it's the biggest bottleneck right it actually hinders the operation of how an agent should work out so

19:05that's where turf comes in right turf make this whole process autonomous so what we have done is we have

19:13removed human labeling with two aspects of data transformations and models as judge these two together

19:21can benchmark different data and can create multiple set of data in brute force manner so that it can see

19:28like hey this thing process your benchmark you can actually use this data to answer or do any

19:33activity that you want right so it does with the philosophy i would say the conceptualization of

19:39bitcoin of whoever hits the hash rate first and get these many zeros they get their reward right

19:47their blog gets mined the same aspect of using compute and removing removing human power is what we are

19:54doing that makes this whole process autonomous and since we have a benchmarking service that's again

20:00powered by ai that's something we are bringing in and with every single transaction that we carry out

20:06right every time there is an aggregation transformation and loading happening right with every single

20:11transaction we are powering up our own ai code that efficiently maps and gets better and better day by day

20:18so if an agent needs very much context specific data regarding gaming right they know where to look how

20:25to bring what to transform and bring it and how to bring it so this is something that makes us super

20:32different let's say there are multiple platforms already available literally like snowflake they are

20:39biggest one of the biggest giants in web2 ecosystem scale ai having abundance of data and transforming it for

20:45open ai right these all in interactions are happening by human we don't want that so to be honest it's

20:53been we in our competitive landscape there are four quadrants and in the top right corner we were the

20:59only one who were doing this now if you recently heard about parallel ai so twitter's ex-ceo also got

21:06into data orchestration business so that got released in 15 days ago and now added to our quadrant of

21:12competitive landscape so this is something that's whole agent economy is looking forward and we are

21:17the context providers got it no i think this is super super interesting very insightful and at the

21:23same time i think you have articulated it very well really something which which i think key takeaway

21:28i would say to understand more deeply how the context specific data how it creates the whole economy

21:34whether it be on the monetization side building the context-based data structure that can be utilized in

21:41various use cases and as well as verticals no i think this is pretty cool so devika now we are

21:47seeing there's a massive demand for customizable infrastructure there are a lot of interesting use

21:52cases coming in whether it be rwa deep in we are seeing a lot of use cases within ai and battery

21:59and people are launching their own custom app chains or custom l1s in fact today morning i read the news

22:05about how google is launching their own l1 after stripe and circle announced their own fintech specific

22:12l1 so you know we would like to know you know how avalanche is is helping modular builders like turf

22:20not just with the tech stack but also in in other ways as part of the ecosystem to differentiate and

22:25scale globally and what kind of you know use cases are you seeing which are emerging who are embracing

22:30avalanche l1 yeah so i think with avalanche you know what we're what we really pride ourselves on

22:37is the fact that we try to go beyond just grant support right so yes of course for builders there

22:44may be grants there might be investments but what we really want to go beyond is actually provide them

22:48with with other support right whether that's tech support so we have a dev rel team i think i believe

22:53the bionist team are quite often in touch with our dev rel team and they're quite responsive for the

22:57most part that's something that often you know large chains like you know at the level of an avalanche

23:01often don't have right builders are kind of building in the dark and they don't really know

23:05what to do when things break the second is actually providing ecosystem support so i think this is quite

23:09important right i think for example we recently wanted to connect with a team called avalanche

23:14right so you know we we help facilitate that so if there's any point where they want to raise funds

23:21right what we do is we actually have a dedicated person on our team now brian who looks at just helping

23:25our ecosystem projects fundraise right so his entire job is helping a project like turf that

23:31has an incredible product and like has traction actually go to the right investors that we know

23:36be passionate about his kind of project and helping support that process so that's actually again a very

23:41very hands-on thing which i don't know if other ecosystems have some might have some of these i'm

23:45not sure if anybody has all of these right in terms of looking at use cases i think what's really cool

23:52about avalanche is that there is no niche segment and there is no niche industry that it specifically

23:59appeals to the way that for example in other chain might so some chains are like oh that's the gaming

24:04chain right or that's the infra chain or that's the defi chain what we're seeing now is that because you

24:09can have your own chain and it could be anything it could be the gaming chain the defi chain the

24:12infa chain the turf chain you're seeing all kinds of use cases so it really depends on what are the

24:17narratives that are driving the market at that moment and you'll see all of that on avalanche if

24:22not more but of course i think there are a couple of kind of key spaces where we see a lot of activity

24:28one is rwas so again you know when you look at rwas you know you need a very very institutional

24:34focused compliant platform right and a compliant blockchain so avalanche is very well suited specifically

24:40for something like the rwa kind of play right whether that's land tokenization in dhantivara

24:46whether that is you know putting all land records in bergen county and all sales of real estate assets

24:53in bergen county on chain whether that's california dmv right you see you see rwa is really winning

24:58gaming again it's something that needs very high throughput very low latency very quick like time to

25:02finality so you see a lot of gaming you see a lot of infra so i would actually put maybe

25:06turf in kind of ai planned or infra right so you're seeing a lot of infra you're seeing a lot of ai

25:12again because these are these are specific needs that people have that very few products that are

25:17not and one can address so so i think that's kind of the what i'm seeing it is everything there's deep

25:23there's everything but these are the ones that i really am excited about these are what i see

25:26and i believe that's kind of what we have been to the market no i think very well put you're right you

25:31know all the builders that we work with there are quite a few enterprises who are launching you are

25:36using l1 to launch a enterprise-grade network with permission set of validators privacy features

25:43compliances as you rightly said and then you know bringing all necessary critical integrations and

25:49then we have you know builders from d5 payments we have gaming a lot of startups who are working in

25:56the enterprise space with enterprise use cases whether it be dpp or supply chain traceability very very

26:01exciting use cases people are building very varied and yet the same time you know l1 makes it it's

26:07so flexible it makes it very easy you know configure customize and extend to serve various use cases

26:15no i think it's it's it's pretty uh pretty cool out there so now since we are coming to the end of our

26:20session one last question uh debio you know a bit about you know what is next but you know if you can

26:27tell us anything as part of your roadmap some of the upcoming features milestones and and second you

26:34know how various stakeholders whether it be developers creators or other b2b stakeholders who would want to

26:40be part of the turf ecosystem how they can how they can be part of debio i think you're on mute

26:46yes okay cool yeah am i audible now yes yeah yeah yeah so there have been some interesting updates from

26:55our end uh first level is we have already released our testnet with zeef and we have started operations

27:01on top of it and especially we have our beta dashboard live where people can go and create their own data

27:09agents and start monetizing their data so if you just go to beta.terf.network and obviously we are

27:15rolling out in a white listing basis if anyone is looking up to this video and need to understand this

27:21whole data infrastructure they don't have to read anything just go in beta.terf.network give us the

27:27email dms we can actually give you access and you can curate your own data segments right whenever you

27:33create your own data sets you have the ability to monetize it and at the same time anyone who is

27:38building on ai anyone who is building agentic interfaces can have context with our protocols

27:45so even if you if you know about symmetry right symmetry is one of the biggest mcp server registries

27:52100 plus data models and their registry is coming to turf for monetization so we will be launching

28:00all these things and at the same time with avalanche there is this hackathon that's coming up and we will

28:06be encouraging more builders to actually come in curate their own data agent on top of our network

28:11and start monetization if you're not a data curator you can literally go forward and use the data apis

28:19paper query and leverage this whole massive ecosystem of data for building whatever agents you want

28:26for the world of ai so yes these are the few things that we are totally up to and one of the core

28:32roadmaps that we have in terms of business is to complete 2 million gtv transacted on chain with

28:39the data that we are bringing in collaboration with a lot of companies got it no i think super interesting

28:44super interesting very exciting roadmap and we wish you all the best so you know i would like to say to

28:51all the builders who are listening to this talk show so anyone who is a data curator or building an ai

28:58agent data consumer do try the turf ecosystem connect with divio connect with their team to

29:04see how they can help you become part of this on-demand data-driven network and if you are

29:10planning to launch your own l1 do connect us at zeve we will help you not just in consulting as to

29:15how to set up your l1 based on your use case or vertical but we'll also help you deploy your network

29:21manage it and and and ongoing support and if you want to understand how avalanche is helping

29:28builders with their ecosystem support do connect with devika and she will be able to help you

29:33anything what you want you know not just from the tech perspective but beyond tech as you it said

29:38whether it be ecosystem support whether it's gtm whether it be discussions with domain experts and i

29:43can vouch for this a lot of our partners and clients have talked to various domain experts

29:49whether it be rwa or ai within the avalanche ecosystem so it's it's it's an amazing ecosystem

29:55and do try it out with that you know thanks the bureau thanks devika for joining us i think it has

30:00been a very insightful and very exciting session today to learn more about turf and how avalanche l1

30:07is making inroads into builders and making waves thank you thanks again for joining thank you so much

30:15thank you for having us thanks a lot

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