Keystrokedna revenue, CEO Jeff Gawley, team size, customer count, churn, and more in 2022.

hello everyone my guest today is jeff golly he's an ex-patriot american residing 22 years in estonia with 15 plus years international experience in investment and retail banking and specialization in secondary market creation funding mechanisms he completed the first ever mortgage securitization in cee co-founded a successful startup studio in 2015 that led the creation of keystroke dna his current project all right jeff you're ready to take us to the top yup i am all right so what is dave you bet what's keystroke doing what's the revenue model are you guys sas sure we are a sas player uh keystroke dna is uh uses machine learning to provide behavioral biometric authentication based on keto dynamics so what we do is we analyze typing patterns and we use that information to identify and protect you it's a second essentially a second factor authentication or third factor but we also provide identity confirmation so who are you selling to so in fact there's really three distinct target markets for us uh bfsi and is is probably the first where we started the wait jeff what is what is bfsi uh banks financial supervisory and uh insurance companies but in fact the the first target market for us is virtually any business that seeks to strengthen access security and that uh we are an invisible uh second factor as a biometric so really any and virtually any global business that wants to increase access security is a target market for us so let me give an example let me give an example here you might sell this to a bank and they will know that when my father who's 85 is logging into his bb t bank account he plucks and it takes him about 13 seconds to type his password if i log in i do it in like .2 seconds and i'm trying to log onto his account that might be a red flag because you know it's not the normal pattern exactly you won't have a match to the biometric profile we create and we'll know it's a distinctly different person so that has several different use cases not the least of which is a security aspect for logins there's nothing on my dad's computer or my computer right it's all web-based all web-based there's a small script that we embed with the client side in the web page typically a username and that's all that's needed it's much like embedding google analytics in terms of the timing the javascript javascript embed exactly yeah exactly that okay help me understand kind of target here so the average customer that pays you to use this i mean incredible technology what are they going to pay you per year to use it right so we we're we are pre-revenue if i'm to be blunt at this point uh we've been at this almost a year and a half now uh we are now on boarding our first customers and the revenue model that were put forth is based on authentication volumes and the price point we're looking at is 1.9 cents per authentication call and that's kind of an important number for us it does put us as the most cost effective in these types of service providers in the market compared to it's also uh bio catch compared to uh uh they par they charge per user uh they charge something in the range of six seven euros per month but over a thousand authentications per month they start to charge ten so i should be ten cents for authentication at them okay but that's way cheaper than 1.90 yeah it's we are considerably cheaper exactly no no they're cheaper at 10 cents if you're a dollar ninety per authenticated no no no we are 1.9 euro cents got authentication calls so we're significantly cheaper and it also puts us more cost-effective than an sms with which we indirectly compete in the 2fa market got it okay so so um it makes sense you have a cost arbitrage here you're onboarding your first customer here today if this first customer onboards how you expect them to are are you kind of going after i mean it's a 100 000 acb account a million dollar acb account 10 grand it would be about a quarter million okay so you're just going to go direct for enterprise why would enterprise trust a startup well it's not just enterprise this is educational which is a slightly different use case for us so in addition to providing security we also confirm identities in real time so you're looking at any of the moocs universities we just built what's called a shibboleth plug-in so that they can adapt our technology into their single sign-on procedure and use us very easily in a very familiar way so let me make that actually let me give a real example there jeff just to make sure my audience understands this right if i am giving an sat test of the at virginia tech and students can take it online to make sure they are the ones actually taking you might watch their keystroke data and make sure that they are they indeed the student exactly exactly that and typically just a username or an email address is all we need to authenticate it's actually one of the things that differentiates us we need just eight characters to create a biometric profile and identify based off of what though what do you learn from jose carr is it timing between when the characters are typed is it it's called dwell time and flight time of the key metric since how long you're on one key in milliseconds to the next and from an eight character sequence we get at least 30 odd data points and that's where the magic is inside the algorithm we use machine learning to create a biometric profile and then use that it's actually quite reliable we're more accurate than voice recognition and face recognition but if virginia tech is installing this on their website again to make sure sct tests are taken by the people they should be taken by how are you how are you measuring just from the website data how long my finger is on the t button how it's you're able to get that data through we we get user agent data and we get the keystroke data you get that data in real time in milliseconds to create a biometric profile yeah but but like how do you get the actual like what i'm asking is it feels like you have to have something on my personal computer right now to know how long i push down the t button right now that's what i'm asking is how do you get that data nothing on your computer whatsoever in fact we're not even interested in the characters that you're typing we're just interested in the dynamics the keystroke rhythms and patterns and that information is available through the integration on the client side through any web-based browser any platform any device in any business can use this as long as it's web sheets that's why it's a sas model how much money have you sunk into the product so far we've bootstrapped uh close to 200k and uh have raised another 150 in pre-seed funding is it all spent no no no we still have at least six six months plus a runway so how about yeah that's what i'm asking how much have you spent so far on the mvp uh on the mvp itself was was just over 200 grand okay you got about 150 still in the bank yeah yeah what is it so uh you raise capital and is that all today you've raised 150 from kind of traditional angels yeah their angels and accelerator program that we were working with they're they're not quite in an accelerator they're a specialized fintech insurance company so it's yeah basically an angel i guess and what's your team size today how many people just two of you guys we have six actually three data scientists yeah two data scientists a principal engineer full stack developer and my partner and co-founder cto that sounds expensive i mean were you burning 10 grand a month 100 a month uh under 10 under 10k a month how can you hire all those smart people and burn less than 10 grand a month well they're they're based my team is based actually in the ukraine although the company is based here in town estonia where i reside i see so there's just arbitrage there on talent yeah it's it's not just that there there's contractual basis as well so it is it is a better tax regime for sure in uh in ukraine at the moment yeah interesting okay what do you hope to hit by the end of this year in terms of revenue and customers boy by the end of this year if we could have our first two or three customers onboarded in the education sector where it seems we're going to have a quarter million to a half million in revenue would be fantastic but there you go guys let's wrap up here jeff with the famous five number one what's your favorite business book uh favorite book i just finished reading the four uh the hidden dna of amazon google and what so i don't know scott galloway it's a good one number two is there a ceo you're following or studying honestly not in particular no okay number three what's your favorite online tool for building your company i guess for me personally i've been using pipedrive a lot which is another estonian startup here number four how many hours of sleep to get every night uh i guess about at least seven and uh how old are you i'm 50. 50. in situation married single kids married with two kids okay last question what do you wish your 20 year old self knew to invest more sooner and to be an entrepreneur sooner guys keystroke dna basically biometric data confirmations all based off keystroke data all web-based nothing installed on physical computers which is great pre-revenue today they've spent 200 grand on the mvp still 150 grand in the bank burning about 10 grand a month with their team of six as looked on were the first three customers here by the end of 2019 targeting 250 grand in arr jeff thank you for taking us to the top thank you nathan