How Yellow.ai CEO Raghu Ravinutala grew Yellow.ai to $79.5M revenue and 1K customers in 2024.

hey guys recording this here on what is it friday the 19th maybe you're seeing this on monday at the latest but want to let you know we are almost sold out for founder comp sorry founder 500 in austin texas here in about a week uh it's gonna be an amazing event 500 b2b sas founders i'm looking at the attendee list there's almost um there's almost 60 founders with more than six seven million bucks in arr it's an incredible group of group there's over uh there's over a hundred over 150 with more than a million uh more than a million revenue it's an incredible group you don't want to miss it uh grab your hotel grab your flight grab a ticket right now i'll put the link in the bio um in the description here on youtube and i think there's only about three tickets left okay about three tickets left i'd love to see you guys there don't be bashful grab your ticket now hey folks my guess it is ragu rabunutala he is the founder and ceo of yellow.ai an enterprise grade conversational ai platform that enables enterprises to deliver human-like interactions that boost customer satisfaction and employee engagement at scale powered by dynamic ai agents raghu you ready to take it to the top ready to start all right when you say dynamic ai agents i mean are there are these humans or these bodies or is this like machine learning ai stuff it's 100 machine learning ai uh nathan thought too it's uh absolutely cutting edge we just launched uh the dynamic nlp today out in the press as well um so this is something that gets trained over billions of conversations happening every single day and uh dynamically adapt to those metadata so we believe it's a breakthrough what was the initial training set you fed your machine learning for ai algorithm to get it up to speed quick oh over a period of time when we started in 2016 it was uh humans that were training these models uh because there weren't any conversations we were just starting off and as we started the uh platform and being used by customers we used the metadata from those conversations to uplift and train the uh models uh to upgrade them uh but it initially seeded with a lot of manual training and labeling when we started the company wow okay so give me a sense of of what customers are paying you to do so maybe a specific use case would be great oh let me give an example of a leading utility company in the united states and they use our product to automate customer service on their uh website and on their telephony lines so when somebody calls for a pickup of uh their waste etc this company just automate the entire conversation um i'll give a broad range so this company paces somewhere between uh 500 to 750k in annual uh err okay is that your largest customer that's one of our largest we have larger customers our largest customer pays us more than a million dollars uh per uh per annum and help me understand what makes that contract value so large is it seed-based upselling feature-based upselling utility-based upselling or something else it is utility-based uh upselling so this is essentially uh our pricing is directly linked to the number of conversations or interactions that are automated so the more number of phone calls that our virtual assistant answers uh the subscription price uh goes up pretty uh linearly uh i see so if i'm paying you a million a year how many phone calls are you probably handling for me okay so of course the pricing differs across countries so typically we average uh somewhere about uh 0.5 uh to a dollar per um minute uh of call handling oh wow so do you have a great utility metric it's not just like the phone call it's per minute of call handling so it could be one phone call be a lot of money that's correct interesting um i imagine but i think our platform runs on whatsapp uh google business messaging so all those are per conversation session uh so different pricing for that let me let me ask you a weird question related to your product cannibalization here if i'm if i'm paying you to handle telephony for me and i'm paying you five cents per minute of call handling but you're also trying to use a machine learning to prevent the call in the first place don't you sort of compete with yourself there oh absolutely uh nathan i think the overall objective of the company is to uh automate um the the majority or the uh overall available interactions at the company and we clearly believe that digital interactions are superior to voice interaction in many cases and we recommend customers to do that though it cannibalizes let's say a potentially higher revenue in voice handling but we know that there are 400 billion calls made every single year in the world and today less than 0.1 percent of them have any kind of automation so it will not disappear uh in a while so there's a lot of market so i don't think we need we as a company don't need to worry about uh one product cannibalizing uh that's thinking too narrow at this point got it oh what's going on there youtube good to see you guys now imagine this you love watching these interviews with sas founders but imagine if we took all of the valuation data out from over interviews i've done manually saves you a lot of time well we've done this we've built it into the beautiful interface inside of founder path check this out i'll show you how you can access this in a second but you log in you connect your stripe account you see your valuation real time you can see what it changed over the past 88 days and even set goals for valuation this year now the secret evaluation is there's many different ways to value a sas business so the reason you're going to see three or four different valuations inside of your frowner path dashboard this is all free by the way is because depending on who's doing the buying of your sas company you're going to get a different valuation a vc is going to pay a different valuation private equity firm is different if you're going to do a minority sale that's different and if you sell the whole business that's a different valuation you can see all those when i hover over here right so the teal is what a vc would pay yellow is what private equity and red is if you sold the whole thing outright now what's cool about this is this is not built off random data again you guys hear these interviews on youtube all these datas are built from real-time valuation data points founders share with us on the show so traction 1.2 million seed round 3.7 raised they sold 22 to their business go in here and filter by the event maybe you only want to see companies that have sold the whole business well here are a bunch that have been acquired the valuation and the multiple maybe you're going out right now and you're raising your seed round well go in here and look at all this recent seed deals that went down what they raised what valuation they raised at and what percent that they sold there's never been a larger data set of sas valuations than what you can get now inside of founder path and we're thrilled to bring it to you all right we're going to go back to the youtube video here in a second but if you want to check this tool out if you want to jump in and sign up you can check it out for free to get your valuation at this link this link founderpath.com forward slash products forward slash evaluations or if you go to founderpath.com and hover over products click on get your evaluation here and go ahead and sign up to give it a whirl again all that valuation data live right inside the platform i hope to see you there all right let's jump back into the interview very cool okay we talked about your biggest sort of customer but tell me what your sweet spot is what's the average customer pay you per month or a year to use the tech yeah so um since we are a company that's uh kind of born in asia pacific uh and grown into north america we have uh kind of two different go-to-market motions for these two geographies and uh typically in the asia pacific market we land our customers somewhere between 30 to 40 gain annual recurring revenue and uh in the us we land uh somewhere between 120 to 250 so average would be about 130 uh kind of error values in north america interesting i always get people that launch outside of us asking how they expanded us so i want to come back to that here in a second but first i want to get the origin story here put this on a timeline when did you launch the business oh we launched our business in 2016. 2016. wow and how did you get your first customer do you remember who it was oh yeah so it's one of the leading uh paints company in india and paint yeah paints yeah this this asia's largest paints company wow uh they just amazing yeah and so how did you go i guess that was your first customer how many customers are you serving now today uh we are overall serving about 1000 plus customers wow and when what's a split between asia pacific and us so still asia pacific dominates our uh percentage so uh in terms of number of customers it's probably 90 plus in asia pacific but in terms of ar it's somewhere between 70 to 80. uh 70 and 80. so are you more excited about the expansion in the us then absolutely it's the largest market out there nathan so yeah and we're very excited about how we've grown over the last uh two years since we since we launched in the u.s market so some of our customers uh grew from uh they landed at 30 or 40k in the us market and grew to 600 700k so uh we're just seeing uh much faster expansion rates and growth rates within companies uh in...