 First of all, I would like to convey a message on behalf of our CEO Mr. Rohit Burma, he could not make up for this event because he is not well. Let me quickly introduce ourselves. We are TORQ AI. We are a global audience infrastructure and programmatic solution company. We specialize in in-house programmatic advertising. Today we are going to be talking about, we add a new platform with a big differentiator. It's been conceptualized, developed, handled and managed by TORQ AI. So thanks Nishant for the intro. So these are some of the industry first that we brought to the digital advertising ecosystem that we're going to be talking about today. So we're going to be running through each one of these. We're talking about how VI ads bring the third party media into play, how media and data gets stapled together to offer solutions that the market really hasn't seen so far. How do we go beyond standard cohorts? And what are we really bringing to the table? There's a whole new way of looking at digital advertising which revolves around a persistent telco mobile number-based idea that we're going to be talking about today. We also are going to be talking about the kind of match rates that we bring in to campaigns for advertisers and agencies. And finally we're going to be talking about future use cases that we have that we can do audience enrichment and activation through the data clean room solutions that we have. Okay so till date within the telco ecosystem the advertisers can target the audiences within their own and operated media but with VI ads the landscape has completely changed. Now brands and marketers can target audiences on V platform not within their own and operated media but also onto the third party. And it also gives the brand and marketers to not only target the digital part but they can also target via traditional media like SMS and OVD. So what are we talking about here? When we say the platform is inventory agnostic what we really mean is that we have telco data which tells you who the user is and on top of that when we staple it with media we also know where he is which means once we arrive at a particular cohort which is required for a particular campaign we also staple it with media and we know where the user is. So brands usually spend a significantly large amount of time, effort and money experimenting with various media to try and find out which media works best for them and this usually involves very little efficacy and large budgets. So what we are able to do through VI ads is for example I can give you one example of a campaign that we ran recently it was a large music service that we all know so they were relaunching in a huge way and they wanted to spend significantly large amount of budgets across media categories. So we arrived at music affinity audiences and ran it in excess of 20 different platforms. What this means is otherwise the service would have had to run individual campaigns across each of these media categories to understand which works for them and which doesn't which involves much higher spends whereas with VI ads capability and ML capabilities what we were able to do is identify music affinity audiences and target them across various the number of third party media that we talked about and yielded fantastic results. So how did we really do that? So when we say media and data staple together this is the first time it's being done. So what we mean is we've brought in the telco data in traditional advertising which is probably which is not probably I'm sorry I shouldn't use the word probably it's the most deterministic form of data available in the market. Once we know who the user is we staple media to that ID and we also know where the user is. So this is a sea change in the way brands look at campaigns today advertising today. So we are concatenating multiple campaigns into one capability by stapling media and data together. Yeah. So the platform is not only allows the brands to target predefined cohorts like a gender socioeconomic class etc. But it also allows the brand to create its own custom cohorts and segments. It offers the market here a benefit of unique audience segmentation and interest groups and targeting parameters. So if you look at the way campaigns are being run today we talk about two behemoths where we ask for some audiences and some data gets thrown back at us in terms of affinity etc. But we really don't know the veracity nor the accuracy of the data. What happens with the ads is we process petabytes of data on a daily basis classifying and categorizing these users into targetable cohorts. And what happens now is I already talked to you about the capability of targeting these people on various third party media as well. So I can give you a very interesting example of a health insurance company. So they had internal studies done which said they need to look at, this was a particular product launch. So they needed to look at life insurance customers. They needed to look at diagnostic lab users. They needed to look at e-farmacy users. And this was the kind of audiences that they're planning to run on different platforms. So we talked to them and said that we'll be able to do that in one campaign. So we arrived at, like I said, petabytes of data, which was processed, gave us access to the kind of users that we have on each of these cohorts. And once we did that, it was a video campaign. We ran it across OTT channels and other video platforms, gave them fantastic results. So they're advertising with us regularly now. So what's the magic that really is going on in here? So the entire premise around which this platform is built is the fact that today, digital advertising runs on something called the cookie, which I'm sure you must all be familiar with, which is not necessarily the most ideal way to be looking at spending your money. So what's happening is we're sitting at a cusp where the third party cookie might get deprecated very soon. And then what happens? The ecosystem is actually spending billions of dollars in trying to find out the next way, the next ID system. So we're already, so luckily we're one step ahead of the curve. So we decide, we understand that the MSI as DN based ID system is probably the most viable alternate for digital advertising. When I say MSI as DN, it means the mobile number. Everything else is subject to change and has a finite shelf life, except the mobile number. So what an MSI as DN based persistent, the meaning of the word persistent is that it's the most stable metric around which you can build your ID system, which allows all of the other secret sources to be developed. So what happens in, what are we talking about when you're talking about the match rate? So when we said that you have the telco ID and you match its table with the media ID and you're able to target this user across third party media, what it effectively means is that for the first time a platform has the capability of matching the ID with the media and in scale, especially when you're talking about consuming large budgets, reaching out to large audiences, you need to have match rates, which means the system has to have the capability of identifying millions of users across diverse media categories, which is what we're talking about. I can take a couple of examples here. So there's a large mutual fund that advertises regularly with us. So what they did was they gave us a certain amount, a certain kind of cohorts that they wanted. They wanted frequent investors. They wanted credit card holders and P1 markets and so on. So they gave us those cohorts that we needed to identify, which we did. And then it was a video campaign, which means the inventory available to us is finite, which means all of these millions of users that we found out, now we have to identify them across just the video inventory. So we found out that almost 78% to 80% of the users that we arrived at as a cohorts where we could identify across the various OTT and media platforms. And it was a very, very successful campaign. It's opened up a whole new way of running BFSI campaigns for us. So industry today is talking about certain challenges that the brands are facing in transferring their first party data. Obviously, the concern is that what will happen to the privacy. Well, not anymore. Brands can now transfer their first party data in the most secured manner on VX platform. In the most, I would say, highly calculated ecosystem. So I can give you an example of, I can give you a use case when we talk about this particular feature. So we were talking to a bank, which had a peculiar, not very peculiar, but a standard problem. So they had pre-approved users that they were only doing MaTeX on. They were using AdTech only for acquisition. MaTeX wasn't yielding the kind of results that they were expecting. And we're talking about numbers in the millions now. So what we did was we created a secure environment where we matched their data with ours. And we found out that there were millions of users that we had in common. We used now those common users we targeted across different types of media, brought them back into the fold. The problem statement for the bank was that they were pre-approved users who were taking services from other banks, which means MaTeX was clearly not working for them, or rather they should have been trying different ways of doing this. So this opened up a whole new avenue for them to reach out to customers that were already in, but were ripe to go to competition, which changed the way they were looking at this whole MaTeX activity. Thank you very much. We are over here. In case any questions, we have a booth outside. We can connect during the day and have a conversation on the same. Thanks. Thanks a lot, everybody. We're open for questions. We're just outside. Thanks a lot. We're happy to answer any questions. Thank you.