How Vyrill CEO Ajay Bam grew Vyrill to $2.7M revenue and 7 customers in 2024.

hello everybody my guest today is AJ BAM he is currently the co-founder and CEO of viral vir I ll comm a UC Berkeley founded startup the company helps brand marketers make sense of user-generated video content on social media and leverage video intelligence for product marketing to drive product sales fit as yeah you ready to take us to the top yes and I love it alright so first off is the company a pure place ass company yes it is a company and we do some new business models as a licensing as well okay interesting so help us understand what the company does and then I want to learn more about your customers yeah so especially you know in a nutshell what the company is doing is we have trained machines to watch millions of videos on YouTube and Instagram to help brands like Revlon Porsche find the best video reviews unboxing videos and tutorials and all that for product marketing so so essentially the problem that we're trying to solve is there's massive amounts of video content being posted on social media and web from smartphones so a lot of brands the big brands are struggling with you know who's creating content for my product my brand and my competitors what are the on what platform when where and if someone made a very positive video review and unboxing video for my product I want to know first thing I want to know it happened I want to know who that person is and I really want to understand what's actually happening inside the video itself and you know whether it's positive or negative and then if there if it's a very positive review I might want to license that video for product marketing or if someone made a very negative comment I might want to mitigate that situation and we talked to that consumer and seiche and check in with them and see how I can help so essentially we're trying to help brand marketers make sense of all this massive amounts of video content on social media and web and really leverage all that for product marketing interesting okay so what's the average company paying you per year per month for the tool yeah so on average companies pay anywhere from $25,000 the I'm talking about the large fortune in thousand companies anywhere from twenty-five thousand two hundred thousand dollars a year okay and would you say the average it's fair enough say the average is on the lower and call it 25 guarantees about yeah I would say in the I would say you can say 25k for now yeah that's great and what is someone so when they sign up for some of that sends it for 25 grand a year versus a hundred grand per year what are the pricing axes your pricing against yes essentially our pricing is really tiered upon a number of products and SKUs so what makes viral very unique is that were able to map millions of videos on YouTube to product SKU category brand and competitor we then actually go inside the video itself and we analyze the video for sentiment topic scene demographic diversity brand safety product safety video stats and all that and one minute in are you using now are you basically transcribing and listening the voice of whoever's making the video are you actually looking visually using a visual API to look at the product that way program at Brookley and so we analyze video text video audio and video images and with all of these three analyzing all these three components of a video were able to filter all the content through those 9 different lenses that I mentioned before and then we're scoring the video so you know you know video is very rich right in Western accuracy rate in terms of I'm holding up a a Nike hat in this picture and I'm saying this Nike had his it ripped in the back I don't want it how many times we I correctly identify this is a Nike hat so by the way in terms of accuracy can vary anywhere from sixty percent you and somewhere in 95 percent range it really depends on how good or bad the video is depends on the volume depends on the English the transcription and all that so today we're mostly processing videos in English and the way we do that is we actually start with text because if you look at computing text is the easiest so we look at all the video metadata around the around the video you know title description comments transcribing every video as well the odd the actual audio then we look at the audio so the accuracy improves so if you can get the eye high enough accuracy from the text itself with a cat audio and then we look at images so in that order interesting you don't and by the way it's a very difficult problem to solve you can even searching massive amounts of video frames it's a very difficult problem not just for us even for YouTube yeah so I I I imagine it's a massive problem so put this on a timeline for me when you launch this company what year yes two years ago around October of 2015 and we had we did one pivot so so technically we launched our enterprise product that we have today about a year and half ago okay and how many customers have a scale to today yeah so today we have about we have two products bottle enterprises we have about seven big brands and working with us on pilots and then we have about 25 other customers on our VIP product which is the viral influence of platform and so the the VIP product so the pricing that I gave you before was for the viral enterprise and the VIP entropy the VIP is really the lighter version of the product and that goes for about $150 a month okay so a hundred fifty a month you've got 32 people on that and then you've got about seven people paying you know average a series of 25 bucks 25 grand a year all right so total right now what you're doing like north of 15 15 bucks re ten thousand bucks a month in revenue yeah I would say something yeah something in that in that range and where were you about a year ago so to be honest with you a year ago we were I would say our our Mr was somewhere in the thousand two thousand range and and honestly I think now we're at this stage you know it's taken us a while you actually build this bar it's a very difficult problem to solve but now we're finally there for ramped up so we're actually now ramping up product customers and and revenue and we're also announcing our licensing tool next month so essentially any creator will be able to log in with their and upload their video content and essentially monetize their video content through the bowel platform so our mission is we're vision is very simple we want to enable every smartphone user in the world to be able to monetize their content with brand retailers and publishers directly mm-hmm I mean it by the way this is something that YouTube should you I mean you're really playing to be bought by YouTube well we so essentially the difference is and YouTube is a very horizontal search were very vertical search so today we focus on beauty electronics automotive CPG airline media we're now expanding to other verticals fashion gaming sport and more so we do very deep vertical announces of for example we have trained the machine to recognize 50 different topics in beauty 50 different topics you know I get all that my point is though like you your system cannot get smarter without more video content to analyze that's how a machine learning and AI gets more intelligent and YouTube has the largest data set there so they will win this space the question is can you break off a chunk and get them to buy you right before they build this themselves right you could argue that or or maybe Amazon or Walmart could benefit from this - so it really depends yeah yeah yeah be bootstrap the company today - have you raised yeah so we were actually you know bootstrap for the first two years me and my co-founder dr. Barbara who I met at Berkeley and we have now raised 2.1 million dollars in in the past and we're currently doing another seed raise as well okay when did you raise the 2.1 it was end of last year okay and why is now the right time to raise another round we're launching the licensing platform and we need more sales and marketing dollars to really to start promoting that and I mean this is this is the first time video creators will be able to monetize very quickly with one plaque so it's like Airbnb for video and so we really wanna we need more sales and marketing dollars and we also need to hire more engineers as well on the team and a customer success manager yeah I'm so sorry no how much are you raising or looking to raise all right now we're raising a million dollars okay and is that gonna be on a priced rounder convertible note that's a convertible note got it did you let your first 2.1 was that a connote or equity did you let that first 2.1 roll and this one millions gonna be on the same terms really yes it made a lot of progress we have a patent as well fine now so essentially we have ramped up so the cap is higher what's the incur did you double the cap like what's the ratio but rotated to double it I would say that we increased it by 60% okay fair enough fair enough but still 20% discount 6% interest we are you doing a safe with no interest or is there interest no it's a suit convertible note it's not a safe got it so you'll have like 6 to 8% interest discount interesting and why not just do a priced round right now why do convertible note again so do honest with you like I think we can we will ramp up very quickly and shortly with as we when we launched licensing because finally we are weird actually deserving actions on insights and we truly believe that you know I think in...