SaaS Interviews with CEOs, Startups, Founders
Coralogix Breaks $24m ARR, 2k Customers After Turning Down $40m Acquisition Offer in 2019
01 Nov 2021
Chapter 1: What is the main topic discussed in this episode?
First of all, when I said Forex, I meant our revenue more than Forex, not just the... So 12 million in ARR then? I think the... No, wait, ARR, come on. 12 million in ARR, right? That's Forex 3 million. That's roughly the number again. He won't say it. Look at this. This is great.
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Hey folks, my guest today is Ariel Asaroff. He's had a career in the Israeli intelligence unit of 8200 and later joined Variant Systems to work at the Homeland Security decision and co-founded CoreLogix in 2015 to change how companies analyze their data from index, then analyze, then analyze to index and go back and forth on what matters. Ariel, are you ready to take us to the top?
Thank you very much, Nathan. Great to be here.
As I say, ex-Israeli intelligence, you know, Monday, Roy Mann, of course, I feel like you all, you just know something we don't.
It's interesting, actually. I think there was a research now in Israel that showed where most entrepreneurs come from. I think there are three specific units. There's 8,200, there's 8,100 that came out of shadows recently, and there's pilots. So in our company, we have a mix. And in our board, we actually have 80% of the board members are pilots. pilots in their past.
So I guess there's something when everyone has to get enlisted to the army that kind of ranks people on what they like to do and should do in life when they're 18, which makes decisions easier. That's amazing.
All right. So let's jump into CoreLogix. What are folks paying you for today?
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Chapter 2: What is CoreLogix and how did it start?
So the first three or four years, the company was zero revenue, zero customers. It was almost shut down.
So we were- So hold on. So between 2014 and 2017, no revenue?
The first dollar came in October, 2017. Um, and we actually had a board on September, 2017, where there was a decision point where the board members said, you know, we like you guys. They were super nice and, and, and, uh, patient. How much have you raised to that point?
$2 million. And, um, it was, didn't you do a $5.2 million seed though in 2016? No, not $5.2 million.
It was a million, then another million. Oh, I see. Okay. And then they kind of wondered whether they should just close the company and hand out the money back to the investors, but there was so little. Not to, because it doesn't really matter.
How much was in the bank 2017 before you shut down or thought about it?
$300,000 at the end of 2017 were five people. I'm one of the co-founders, but I was not the CEO. The CEO left at that point. How much equity did you own at that point? Um, it was, you know, we just had a couple of rounds, so it was, it was still fine. And then, um, the CTO that was an employee left after him because, you know, the company kind of fell apart.
So he went to manage a group, this big company and, uh, Yoni, uh, a good friend of mine who also led a group invariant, uh, basically became the CTO became my co-founder and we restructured a company entirely. And we started running from that point onwards. And within the four or five months, we got to like 20, 25,000 of monthly recurring.
So the board was very surprised because they thought they're going to shut down. And they gave us $2.5 million more, like an extension, like a CLA. At what valuation? The valuation back then was roughly $10 million. Okay. Got it.
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Chapter 3: What challenges did CoreLogix face before gaining traction?
No one answered emails. Everyone was shocked. New York became hell. So my team, part of them were not available. It was a mess. So it took us like four or five months to get out of the shock and start growing again. But four or five months, we were literally stuck. Nothing moved, no growth.
And then- What were you stuck at? I mean, you're talking like what, eight, nine million, right? Three million. Three million still, okay.
Three million. And then what happened is that in June, I met Red Dot and OG Tech, two growth companies, growth VCs here in Israel. and told him, listen, I know the numbers don't look really well, but we're going to launch Streema. And I explained what Streema is. And that was critical because Streema is basically...
What we started working on ever since we got in that CLA beginning of 2018, which is flipping how the ingestion pipeline looks like. So everyone index all the data and then they analyze it. So they run periodic queries on the data. They run the aggregation on the storage.
They run the dashboards from the storage, which makes it expensive, slow, and limits the level of analytics that you can provide.
Mm-hmm.
And I told them we're launching Streama, which will analyze everything in real time, including stateful things. So even though it's real time without storing the data, I can tell you that something happened that didn't happen the past three months. So that is something that doesn't exist today in the market at all. It's stateful streaming.
And that will lead, what I explained, that will lead to cost reduction, better performance, easier customer acquisition, and broaden our use cases from logs to logs and metrics and security and traces in the future BI. and also decouples us from the storage so we can use any syntax, any dashboard. So CoreLogix today can use its own dashboard, but many others.
I don't know if it's very common, but Kibana, Grafana, SQL Clients, Tableau, anything can plug to CoreLogix. So now it's a data platform play. It's not just a product. And it's a hard thing to explain to an investor, not to mention when you're not growing. Um, but they, they actually believed in it. We didn't do a round. They just said, okay, we're in, we got a couple offers.
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Chapter 4: How did CoreLogix grow from zero revenue to $3 million?
How many total? 2,000 customers are paying us, but this is the current platform.
The security product has five customers. Two of them are some of the biggest companies in the world. So we are actually aiming this offering for larger companies that have bigger infrastructure or migrating to the cloud, unlike our cloud native and internet play platforms.
for the observability stack. Let me stick on this for a second, a professional services question. If you have 2,000 customers today, what are they paying you per month on average on the SaaS side? And what are the professional service like setup options? So today there's no professional services at all.
They'll only go for security. So today it's all SaaS. There's full SaaS. We have one client that is semi on-prem and And not SaaS. And it's just because the amount of data they produce is not something that any cloud can handle.
And what's the average customer paying you per month right now to use the technology, the current technology?
You know, it really ranges because there are so many zero touch customers. The top 100 are roughly at 80, 85 ACV.
What's the most, don't name the customer, but your biggest customer pays you how much? A million dollars a year. Okay. So do you have multiple accounts at a million a year or just one? We have 25 accounts over a hundred thousand and five accounts over 500,000. Okay, so 25 accounts over 100K and then five accounts over 500K and then one over a million. Yep. Okay, that's great.
Where have you had success driving the upsell? What are you upselling against to get someone to go up to a million-dollar ACV?
Yeah, so first of all, the growth of data, like I mentioned, is exponential. Even though we're super efficient, we have so many ways to reduce costs because we help customers prioritize data by use case and then they pay less and so on and so forth. There's just data growth. And we have other offerings that customers buy.
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Chapter 5: What was the decision-making process behind rejecting the acquisition offer?
So since the beginning of this year, over 130%. 130% and peel back that onion. So there's gross and then expansion. What was gross churn? And then it was expansion. Gross churn this year, less than 2%. Total. That's incredible. So expansion was like 32%, something like that. Roughly. Wow, that's pretty, okay, that's very impressive. What's the team look like today? How many people?
We're just 100 people. We just reached 100 people exactly. The interesting fact is that exactly two and a half years ago, we were eight. So the company is growing really fast. And I think a year from now, we'll cross the 200 people mark. I think this company basically is a company that started in January 2018. Think about it this way. So we had like three and a half lost years.
And then in January 2018, the company started and that gives... That's just a different life. You see the graphs of growth.
It's like this and then just boom. What's more impressive to me is that, you know, I always look at sort of economics, right? If you've got $24 million in revenue right now with 100 people, that's $240,000 in revenue per employee, which is way, it's almost triple what the average private VC-backed SaaS company has. And I'm sure you're hiring like crazy right now.
So that number will go down as you invest in growth.
We're hiring a lot more. We're doing more marketing. This is just a result of... Our history, you know, you tend to not be a huge spender when you experience four years having zero budget and almost shutting down a company.
How many engineers on the team? The largest group is engineering over, I think, almost 70 engineers. Seven engineers. Interesting. OK, so what's the next move? I mean, again, it sounds like you almost doubled over the past like four months in terms of revenue. You know, it is a fast growing company. Obviously, Salesforce failed to get the Datadog deal done.
Are you in acquisition talks right now with Salesforce? I am not.
I actually mentioned that Salesforce, I think, will get in our space some way, somehow. And I think Influent will also step into the observability space. I think also Snowflake will get there because it just makes no sense for companies that control a lot of data and charge data to not get into the space that produces the largest amount of data.
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