How Archii CEO Rene Munk grew to $20.2K revenue and 28 customers in 2018.

hello everyone my guest today is soren monk hanson he's the founder of our key he's also an entrepreneur ceo m a lawyer with a twin and a twin girl dad he's a graduated law so he graduated law school with highest point grade average tried out for traditional law for seven years and then quit to disrupt legal business processes and now is the co-founder and ceo of a 27-person company of lawyers data scientists and developers on a quest to remove manual document handling soren are you ready to take us to the top yeah great thanks sounds great you've been impressed about that introduction good well hey i i appreciate that am i hired yes i get it all right tell me about archie what's the company doing how do you make money so aki is an ai based company secretary that automatically finds reads and organizes companies financial and legal documents so the problem today is that most businesses have their documents scattered across different drives in dropbox g drive email attachments etc and the reason for this is usually that i mean document organization no matter how cool the system you got it ultimately relies on human behavior so your own preference for file names folder names taxonomy etc dictates where the documents end up and most people are just a bit lazy when it comes to actually filing correctly meaning that everything ends up everywhere that is the problem we're targeting what we what we look into here is the company waste uh an average employee waste 3.5 hours per week on actually organizing and looking for documents there is a risk of not having control of your legal and financial documents obviously and lastly there is the compliance issue that even though you don't like to you actually have to get the control of your legal financial documents and we sold that by uh applying machine learning to actually look through your drives the drives did you invite us into you're obviously in full control here and say hey aki please take a look at my email attachment please look at my dropbox please look at my g drive please look at my desktop anarchy will run through this destination find find relevant documents and then label them in uniform taxonomies by actually producing its own label using machine learning by analyzing every last syllable of the document so we don't care whether the document is called nathan's cool document if it's in fact an employment agreement we'll read every last syllable and tell you what it is got it you're actually reading a document not just the name of the file yeah very good and what and what and sort of what do people pay on average for this per month so an average user per user you pay about 40 days per that corresponds to 6.25 us dollars per month okay and i assume i assume you're not selling each individual c you're kind of selling group plans at a time so what's the when the average customer signs up for you how many seats are they typically buying usually they're buying in between 10 and 20 see okay we're we're pretty early stage right now in terms of putting product in market so uh so we just launched our first paid module and right now our main focus is actually user engagement and proving a willingness to pay rather than proving a certain amount we want to prove that people are willing to pay for this service and we'd rather focus on making them fall in love and engage with the product than right now i'm taking the payment even the end of the day we obviously want them to pay of course just to be clear though so each customer right now you know 10 to 20 seats at six bucks a pop so each new customer pays between 60 and 120 bucks per month is that about right yes it sounds right okay and so and so put this on time on for me when did you guys launch the company so actually this is built on top of the consultancy me myself i'm a lawyer so i had no obvious way into tech uh but i just saw that that the companies we helped with the law firm i used to work with uh documents were a huge mess so we wanted to do something about it we just didn't we just thought we had to go out in the traditional way of a law firm to help this out so we started a consultancy a document handling consultancy and what we saw that was still like close to it was 99 analog i think we applied an excel spreadsheet so we thought we were more digital than the law firms which we probably were uh and what we did at the first two years we basically helped the companies identify and then organize them so sorry what was the first year when did you launch the first year was five years ago for the consultancy what we saw was that uh people actually we usually solve their problems on a use case basis so usually if you want to get your company sold you want to implement a contract management system you call us to actually find your documents to put into those systems put into a data room for due diligence what we saw was there was actually we asked our customers i mean on a use case basis we can help you out but why are you such a mess i mean whether your contracts are not based on for use cases they're actually based for you on a day-to-day basis to do whatever the contract was aimed for and we asked so don't you need like a daily daily use case here and basically all of them all of our customers asked said yes we would love to and i had like dollar signs in my eyes i thought this is going to be a great consultancy however we think we weren't able to meet demand for the consultancy we needed something automatic here so yeah i was gonna say so when did you launch the software it was two years ago or three years ago so we started building the software three years ago getting our first machine learning data scientist on board and we just launched we just lost launched the software into beta uh late last year got some visa feedback uh israelite feedback and then we launched our first paying module four months ago okay and did you did you fund you know the first two three years of development there before there was a dollar a revenue did you just fund it with the consultancy revenue exactly so then last summer we got some investors on board but it's primarily funded through consultancy i see okay so how much how much have you raised to date funding yes uh close to 500k u.s okay not that much funded and was that and how do you how do you structure that when you reach out to investors were they investing in both the agency and the software or just the software well they de facto invested in both but obviously wanted to invest in software the reasoning for the consultancy here is that it actually gives us access to know-how of the companies and data working with machine learning requires a lot of heavy training to deliver the algorithms plug-and-play to our customers uh so that was to start that was our starting point we actually got data from our customers for some of them we got allowed to use them for trading purposes allowing us to to deliver plug-and-play software instead of yet another ai platform got it and okay so you launched it in beta about a year ago you launched paid module four months ago now what do you have today in terms of total customers paying you sorry coming in so what do you have you launched the paying module about four months ago my question is what do you have today in total in terms of total customers paying you so right now we we just got 28 customers by doing uh some very very early funnel metrics just to prove that we could do some online marketing to onboard customers uh and then we just wanted to actually shut down the funnel to make sure that we got all those 20 28 customers a great onboarding experience by learning as much as possible so right now revenues are rather low i think in software this year we're going to make like 12 to 15 us dollars uh which is not the focus right now the focus is actually giving customers a great experience yeah i know i get it everyone has to start from from scratch so i appreciate you being so transparent here as you're just launching um so 28 customers you know 10 seats on average six bucks a seat you said 60 bucks a month on the low end so i mean that would put you at about 1600 bucks us dollars right now per month in revenue is that about right yeah okay sounds about right and about in a year ago obviously there was none right because you hadn't launched a paid module that's correct also yeah it's a soaring that's infinite growth right that's what you want exactly so looking at my budgets i've hoped i i kind of continue making finished growth but i'm hoping for in absolute figures a whole lot more right now yeah right now we're learning a lot uh we've not been as focused on just getting we'd rather prove that people want to pay and they want to engage and then from there upsell actually a business model is to make sure that we uh we clean up companies document miss by giving them that one access point for their financial illegal documents from there we're going to upsell to even more modules like a contract management module telling you when all your contracts expire and so on yeah no that makes good sense you mentioned that you've tested some paid stuff to get these first 20 or so customers what what is your cac what are you paying to acquire customers so right now we paid the first fund we uh we ran we pay about 222 u.s dollars okay well that's good i mean if they're paying 60 bucks a month you get paid back in what three or four months exactly so well we just wanted to prove that the funnel sort of makes sense to the target pricing and then from up and then upsell from there but basically without any upsell it actually makes sense yeah and what's your team size today how many folks are just on the software 27. okay 202 are running the consultancy yeah so i mean just just to be clear i mean since you raised so literally about 27 on software the consultancy must be generating a ton of free cash flow to pay all these salaries right well you would think so otherwise which is really really good at hiring people that want to engage in the team and the latter is actually the truth so people are on board and animation here so yeah but just to be just to be clear though come on i mean data scientists can easily go out anywhere and command 170 180 000 salaries i get that you're probably a convincing guy and you're really smart and there's a big mission but these people aren't working for free to be to be the truth is actually they're working for close to free right now so our burn rate right now in us dollars is still below 100k okay monthly okay yeah that's i mean that's if you take 27 multiply times for you know grand a month right that that obviously keeps you under or around that 100 grand mark but i mean when you walk me through how you're incentivizing these people because other early founders always wonder how to incentivize people to do work for free so why how are you able to get a data scientist someone who's high you know extremely smart not pay them not give them equity and just convince them to work for free like so equity is of course part of it but the other part is that making sure that they can actually work with what they love so take for instance data sciences data scientists usually spend half of this day annotating data instead of writing the clever algorithms that that what they that is what they really want to do so what we did was that we built a team of librarians we named them data island and then we made sure that they were the ones we're going to label and annotate the data delivering to the machine learning team to make sure that every data scientist could actually spend the time on what they love the most writing algorithms so we we make sure that that not only do we uh have an efficient allocation of work we also make sure that people get to work with what they love yeah that's part of it and where's everyone based are they all in sweden uh they're all based in copenhagen okay very good very good um good but so everyone in denmark though yes true i would actually have one guy in new york right now he just moved over there as we launched product to do some early market penetration just spoke to the market uh talk about partnerships looking at early distribution aki works actually better in english than it does in danish we've known from the very beginning that we look outside denmark oh good all right very good let's wrap up your sworn with the famous five number one what's the last business book that you read the last business book i read um the lean startup i think it's quite a lot better actually number two is there a ceo you're following or studying honestly no okay i do i do spend a lot of time i do spend a lot of time with my peers in the copenhagen machine learning society to learn a lot from them but they probably wouldn't be ceos know number three what is your favorite online tool for building your business um right now we use the most probably slack okay and number four how many hours i sleep to get every night good question i work a lot and i have twin girls five six maybe six i'm bad all right so you said married and two girls yes okay and how old are you soren i'm 34 34. last question what do you wish your 20 year old self knew um i started to know when one thing i learned by building styles one of the things i wanted to be cool is that rebel that made all his own decisions which is also pretty cool but sometimes it's really really nice to just go ask people to get some decent advice people who actually know stuff yep guys use advice use it to your advantage going from soarin launched a very successful agency now as data scientist lawyers building r key they launched and started coding about three years ago they just launched a paid module less than five months ago today they've got about 20 to 28 folks paying 60 bucks a month doing about 1600 per month in revenue obviously hoping to scale that they've got 500 000 bucks in funding as they look to scale with their team of 27 folks based mainly in denmark and one in new york sauron thanks for taking us to the top