# Higgsfield: $1B Revenue in 18 Months

**Podcast:** The Twenty Minute VC (20VC): Venture Capital | Startup Funding | The Pitch
**Published:** 2026-09-28

## Transcript

my parents told me that I must get to the United States because this is the place where technology matters.
By the age of 19, I was able to get to top three in the world in competitive programming.
Actually, it took us 18 months from 1 million to 1 billion.
For Coursor, it took 24 months.
On average at Hicksfield, a person on the team spends over $10,000 a month on various models.
So internal usage of models a month is over 4 million.
I just caught a guy who spent over 30k in a week on Astro Model.
Many people spend over 10,000 in a week.
Higgsfield.
This is the story that no one has told in startups yet.
The company has just hit a billion dollars in revenue.
It is the fastest growing company in consumer land to hit this milestone.
It even surpassed Kursa.
And guess what?
The travesty.
No one has covered this story.
This company is built with 300 people out of Kazakhstan.
It is a complete anomaly and you don't know about it.
Alex, the founder, is an incredible genius.
One of like the most talented computer programmers competing in competitions from a like super, super early age.
And then building a company that he sold to Snap for over $160 million.
Now Higgsfield, rumored to be raising at an $8 billion price, has just crossed a billion in revenue.
This is the story that you don't know that you need to know.
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Alex, I am so excited for this, dude.
We were talking downstairs and I said, I don't think the Higgs field journey has been told before.
And it's an amazing journey.
So thank you so much for joining me today.
That's a very special opportunity for us.
Thank you for having me.
Obviously, your story is inspiring as well, like how social media has become like an elevator for you, opportunity to create fund and so on.
That's very kind of you to say.
I do just want to go back though, because you're not the Stanford, Silicon Valley, born and bred engineer.
You were a competitive programmer in Kazakhstan.
Can you just take me back?
How did you first find and fall in love with computers and become a programmer so early?
So first, you need to understand where I come from.
So my father is from Uzbekistan.
Uzbekistan is a country in Central Asia where like if a family of five people makes $1,000 a month, it's considered to be wealthy.
It's like not very high standards of living, unfortunately.
But both my parents are professors of mechanical engineering.
And since I remember myself, since I was eight, my parents told me that I must get to the United States because this is the place where technology matters.
So mother had to work three jobs because basically my education was to compete in programming competitions all the time and to go to various educational camps where I could learn from the best, like certain data structures, algorithms, and so on.
Can I ask you a question?
Did you feel pressure as a child competing, being pushed into these environments when you are so young?
Absolutely.
And I'm very grateful to my parents that they showed me the path really from that early on.
Definitely, when you come from this part of the world, think about post-Soviet countries, India, China, like getting to the top.
of the rankings in any competition, in any international competition is the only way to really break out.
So by the age of 19, I was able to get to top three in the world in competitive programming.
But then instead of pursuing like an academical career, decided to do startups.
I'm sure your parents were thrilled.
Can you take me to that decision?
This is like the penultimate moment.
You've worked 19 years for, your parents have told you this is like the mother load, this is the thing.
And you're like, I'm going to go and do this really risky thing called a startup at this point.
What happens then?
So let me take you back to 2014.
I was very fortunate to work on pre-transformer architecture, neural nets, and that was primarily just...
doing optimization, make it run faster, parallel across multiple machines and so on.
And we actually build state of the art system for language translation from English to Russian and Russian to English.
Apparently, talent wars were a real thing even back then.
A lot of my teammates were hired by DeepMind and Meta.
But my passion was actually different.
I was very, very surprised to learn.
when I come to a set for the first time, how quickly Uber actually spread out.
And I was thinking if this app can take over the world so quickly and transform the whole industry, maybe what's going to happen is that mobile phones are going to become the most used devices in the world.
Maybe there is going to be a version of the future where everyone is going to be spending most of their time in their life watching AI generated videos on the phones, because who else is going to produce videos for the phones?
Maybe it's going to happen with AI.
Okay.
And so that was the company that we built before that you sold to Snap?
So, yeah.
So the company was called AI Factory.
Was fortunate to meet Mahi 2018.
He's co-founder of Hicksfield.
And he's like a veteran of Silicon Valley, went through ups and downs and sold it to Snap for $166 million.
Then I was leading Gen AI there.
Pauls, no offense, dude.
You come from a family of incredibly ambitious parents who push you to do well, and you just skip to the moment where you sell for $166 million.
That's a lot of money.
How did that feel when you did it?
We both remember these times.
where the capital for AI companies was not really that much available.
And the AI multiples were not like 200 to revenue as they are today, but closer to zero because AI was not a topic.
So there was like severe dilution dilution, which we experienced.
So just to calibrate what was around No, look, I mean, back then, rounds of like $1-$2 million, having like $1-$2 million in investments was considered to be really good.
But it was still an opportunity for me to finally go to the United States.
So after the acquisition, I permanently moved to first to LA and then to Silicon Valley, and my dream simply came true.
Was it what you thought it would be?
That's a good question.
So San Francisco is definitely a place where no one judges by race, nationality, and so on.
That's truly phenomenal.
There is definitely a meritocracy in a sense that it's possible to meet anyone.
But in the same time, what I see across Silicon Valley investors, it's extremely consensus driven.
I think that last part, I expected to be different.
But then I read the book about the law of capital and I realized this is just how the world works.
So then we have sold to Snap.
We're now in the US.
This is the moment you wanted.
How does Higgsville come to be?
Back then.
like Snapchat 2020 was really growing so quickly.
And the face filters, which my team has built, was driving most of daily new users.
What's important is that these face filters, we were able to manage to run on mobile devices.
So it was virtually for free for Snapchat.
It's not like current LLM tokens costs.
And it scaled to hundreds of millions of people throughout the world.
And it was truly phenomenal to me to build a product, which is still probably the most used consumer media AI product.
But then what happened?
I realized is that there are a lot of unmet needs on advertising sites.
Average company cannot figure out how to be relevant on social media.
And this is a major gap.
Like social media is the main media in the world.
A lot of companies are actually able to build direct response advertising so that they can actually sell more.
But in the same time, most of the companies in the world cannot simply do that.
And basically, because no one simply can keep up with the pace of production for social media, as trends change pretty much every day.
And so you were like, hang on a minute, these big brands aren't able to have media houses.
And so we need to create a tool that lets them?
That was a sell?
Yeah, absolutely.
So where it all really started is that there was a tool to upload a set of images and transform them into a slideshow with music.
It's kind of better than nothing, but still pretty bad, right?
Another solution was to take long-form video and cut them to short, vertically-oriented videos.
This was better, but still really not perfect.
And it felt to me that, especially 2023, it was absolutely clear that scaling loss finally worked.
It's not just a concept from science that scaling loss work.
Video just takes maybe two, three years longer than LLMs and coding.
But it was clear that finally scaling loss should work in video as well.
And I just decided just to take a bet.
But I just want to go back.
I get that in terms of what we see, which is, hey, we want to empower these brands and companies to create amazing media for social media.
But it wasn't a hit from day one.
And I spoke to Amy at Menlo, who mentioned like a couple of pivots before and the meandering that we had.
So what happened when we launched?
Did we have immediate product market fit?
No, actually we spent more than a year in a search of a product which could work.
We burned more than 10 million out of 16 million raised in seed fundraising.
So we felt we have just one attempt left.
And frankly, I feel I am responsible because I was focusing on the wrong things.
I think I just lost the touch with reality back then.
I was so much optimizing for what's hype today, what's the right narrative, how we can hijack the attention, all these things, really.
everything instead of building a good product.
So when we had less than 6 million left, I guess it was slightly less than five actually, I realized that the only thing which we can be focused on is to lean into the product, PLG, and just finally set belief that the best product is going to win.
And then we just started to talk to customers.
We spoke to eight creative directors about their experience with AI and what's simply missing.
Everyone told us that camera control does not exist in AI.
And camera control is so important to tell a story.
So this is a very important bottleneck to solve.
So we released our products March 31st last year.
And since then, we are really riding this crazy wave.
Was it immediate product market fit then?
Yeah, it was immediate.
Is product market fit like love?
When you know, you know.
Yes, it's definitely when you know, you know.
Like, for example, we don't do any paid.
And like we have on the team people who scaled businesses to over like billion and two billion in revenue, like other businesses with paid advertising.
At Hicksfield, we decided to really make a bet.
You don't do paid.
You don't do paid.
Is influencers not paid?
That's a good point.
So with influencers, there is typically, there are different types of influencers, but typically there is some fee for just video production and then like some.
cost per click like attribution which is like works really well on YouTube.
You guys got into some controversy for like I can't remember what it was you were like paying people to promote for you or doing something rogue with influencers.
Was that completely unfair?
Was it kind of my bad we did we did do that?
How do you respond to that?
Look, I think the main takeaway from our experience is that it's very important to own distribution.
Distribution now more important than ever.
And we basically did outsource.
We had just a team of two people on creator and customer success sides.
And we just did outsource to the agency.
And that was not a good experience.
I do just want to go back to part of the story.
Where are you at revenue-wise today?
So today is actually an exciting day.
When we record, just Bloomberg article went out, so that we crossed 1 billion in annualized revenue.
If I had a gong here, I'd be hitting the gong.
A billion in revenue.
Yes.
Actually, it took us 18 months from 1 million to 1 billion.
For Coursor, it took 24 months.
So we are probably the third after OpenAI Anthropic.
18 months from a million to a billion?
Yes.
How do you calculate revenue?
It's a controversial topic.
How do you calculate revenue?
Absolutely.
By the way, your co-host, Jason, also asked this question in May.
Luckily, the answer didn't change.
So we are at least consistent.
So let me be transparent on that.
What we do is we look at revenue over the last four weeks and multiply it by 13.
from what I know, OpenAI, Anthropic, Lavable, all of them use the same methodology.
What's very important is that we take revenue, not sales.
So if that's like annual subscription or annual enterprise contracts, we prorate this across 12 months and only take like a piece which corresponds to one month, to 28 days to be precise.
That's the first piece.
And second, it's only live revenue.
It's only live revenue.
We are not taking like three-year enterprise deals and backing into like one billion figure.
No, we don't do that.
If you were to break that billion up today into annual contracts, monthly subscriptions, and then token spend, what would that be?
So video AI is still relatively early.
It is still probably two years behind coding in terms of adoption.
So on-demand usage for leading...
coding companies could be over 50%.
And I would be honest, for video, it's substantially less than that.
In the same time, what's very interesting for us to observe in the business is that there is significant revenue expansion.
I always love to study stories of the largest customers on the platform.
So one customer started six months ago, spending just subscription $99 a month, $99 a month.
and now we just signed a deal over six million six million a year right so this level of acceleration is something which really like mind-blowing to me dude what are they getting for six million a year that's like a hollywood content team almost So there are multiple trends, and all of them, frankly, coming from Asia.
So first, we're seeing a lot of direct-to-consumer e-commerce companies rebuilding their whole go-to-market to be AI native, where they just make hundreds of ads, if not thousands a week, where they can A-B test what performs well.
But we all know about short-form dramas, right?
Short-form dramas today is an industry over 10 billion.
owned primarily by Chinese companies having huge impact both in China, United States and Europe, everywhere in the world.
And most of new shows there are made with AI end to end.
So look, I think this adoption obviously is coming like bottom up, but that's very difficult to refute this new reality.
What percent of revenue is consumer versus enterprise?
So that's a great question.
So business revenue is slightly over 50%.
Wow.
Yeah.
On the consumer side, it's also very important to break it down.
On the consumer side, out of these 50 is around like 10% is pure consumer use cases, pure consumer.
And that's roughly people who use it on mobile.
So share of our revenue from mobile is less than 10%.
We are very different from many other companies.
But there are lots of aspiring creators, like basically those people who are freelancers doing social media marketing projects and so on, who try to learn video AI so that they can make more money.
It's true that their behavior is a little churny.
Within a year, most of them actually come back to try again.
And we do believe that over the time, most of them are going to figure stuff out.
And they're just going to become this new AI native workforce.
So it's still important for us to educate them.
That's why we invest so much in like Hicksfield Academy, YouTube channel, and so on.
But we also are fully cognizant that we will never be able to win in a market of subscriptions of $20 a month.
So why?
Because like, I think like today, Google and OpenAI, they pursue like ads so much.
But fundamentally, I think they are going to completely demolish all their prosumer subscription markets, which is $20 a month subscriptions.
Oh, so you're saying that because they provide a horizontal product that's very good, you're just going to not pay for a lot of the verticalized products that you used to pay $20, $30 a month for?
Yeah, I do believe that.
That's essentially what's going to happen over the time.
I know this is a very contrarian bet, but at least we can see some of that.
You're seeing it cannibalize Canva's growth, if you're honest.
A lot of the low-hanging fruit on the consumer design side that Canva used to serve can now be done in OpenAI in particular.
Is that what you're talking about?
Yeah, and I do believe this is just the most apparent example, but there are a couple more which is already happening.
And I do believe that that's why at Higgsfield, what really matters for us is...
Even if we get someone on like $20 a month subscription, how can we show them value?
How can we make them to upgrade to spend over $1,000 a year with us?
I can't believe that's $6 million a year from $99.
That's the best ever slide on a fundraising deck.
And all of our customers are going to do the same.
Can I ask, you mentioned that kind of churn rates.
When you look at 30-day...
retention rates for consumers and 90-day retention rates.
What are yours and what is good?
So there is quite a massive drop within the first month, just simply because people don't fully realize the value.
That's a core priority for us to actually get better in that, so showcasing the value.
Is it like half?
No, it's maybe like 30% drop.
But then it's really flat after that.
We look, obviously, at logo retention.
I wouldn't say it's great, but because we all remember B2B SaaS era, like retention was expected to be logo retention.
Month one was expected to be over 80%.
So clearly, we have a lot of work to do on user education to get there.
But some things are truly phenomenal.
Like when I look at the business segments and NRR...
at month 12.
Obviously, like you're gonna argue it's like 18 months old company like what are you talking about?
But still, when I look at the numbers which I have today, and there are at month 12 is over 300%.
It just never happens in B2B SaaS, right?
So that's why I'm saying that while there is substantial churn in month zero and we have to do a better job with user education to address that.
Expansion is unprecedented.
Can we actually just unpack the two different go-to-markets?
Because you've got consumer and you've got enterprise.
And I spoke to quite a few of your competitors in all honesty before this show.
And I said, hey, you've got Alex coming on.
What should we ask him?
Everyone said the same thing, which was an admission of their respect for this particular kind of GTM.
They said, you've executed the most impressive influence on a campaign in tech.
And what I wanted to understand was when you look at the consumer growth, what worked, what didn't work, and how do you reflect on that?
That's a good question.
So first and foremost, like the goal is to make sure that the best commercial video content is generated on Hicksfield.
And we show all the workflows of how to make such professional looking videos.
And we have an in-house team of over 150 creative professionals, 150.
It's almost half of the whole workforce, frankly.
And those people, they make a product launch videos, they make tutorials.
For example, we made the first AI generated movie, which is also like, obviously, a very, very sensitive topic.
But what's important, we open sourced all of it.
And what we learned is that for 90 minutes of like, let's say TV quality content, it was over 100 hours of AI generated content.
So creative decisioning, picking the right piece is still very important.
So that's really what we are focused on.
And that's what's driving most of the most of the revenue.
So you're saying the growth in consumer subscription is through own content and distribution?
Yes, we don't do any page.
Early on, you made an interesting architectural decision to have your own models.
And then you've since walked that back.
Can you talk me through why did you choose own models and why the walk back?
Oh, yeah, obviously, this was obviously this was my mistake.
I'm gonna be I'm gonna do my best to be transparent.
What I need to admit, at some point of time, I really was thinking that chasing benchmarks is valuable.
But I don't believe this is just sort of corporate psyops, frankly.
I was part of the large organization, so I know what happens.
What happens is that everyone just thinks, like, we need to show some progress.
So we need to have some benchmark.
But then when I talk to the top researchers from these labs, especially larger companies, what happens is that they start to put test data into the training.
They start to kind of use leverage test data to use LLM as a judge for training of the models, use all the various tricks to basically gain benchmarks, get like quarterly bonuses and so on.
That's like, who cares, right?
So if I make my couple million dollars a year in one of these labs, I can move to another lab easily.
So that's unfortunately what's happening in larger organizations.
Can I just stay on that?
Yeah.
What do you mean you're saying that they are incentivized by benchmarks?
And so because of that, they are doing artificial things to improve their scoring in benchmarks, which actually don't increase output efficiently.
Yeah, look, I think let's just look at the outcomes which we have today.
Out of all the incumbents in the United States, when I look at open router data, the only company which is relevant is Google, out of all the incumbents.
When I look in China, where probably obsession with benchmarks probably is less.
We have Tencent, Xiaomi, Alibaba, three incumbents being completely relevant, and obviously like Bydance obviously trying to catch up as well.
What's your takeaway from that?
I just do believe that there is just obviously in the tech bubble, there is a strong obsession over the benchmarks, which do not necessarily represent the reality.
But I can talk specifically for video.
A lot of benchmarks today for videos really text to video, which does not represent actual workflows at all.
The way to think about video models today, it's just modern rendering engine.
Think about this as like Unreal Engine or Unity, but just different types of inputs.
And it's virtually impossible to really define a visual output and indirect the execution just through text.
If you just go and to our open source projects like this movie, which I mentioned, average prompt length is over 3000 words.
That's the first thing.
And like, look, all these benchmarks, which we're talking about, they're not like as comprehensive in terms of the details of prompts.
And people who are labeling, they obviously don't cannot read like 3000 word long prompts.
But also on average, there are at least 10 image references.
for every scene.
The reason why it's important is because it's important to define how the characters look like, how the background looks like, how actually characters are located to each other in the scene and so on.
And so that's why prompting and just the workflow is so complex.
Benchmarks just don't represent that.
Going back to the model selection, why did we decide we're going to do our own and then why walk it back?
So it's true that like with VFX and camera control, we got very, very quickly from like maybe 1 million to 20 million in ARR within maybe the first three months.
Then we released our image model, which is really good at aesthetic photo shoots and product consistency.
This is what allowed us to scale then from 20 to 100 million.
So help me understand, Alex.
Why did you decide that you were going to do your own models and why did you abandon them?
We still do them whenever we see like specific use case like these photo shoots, but as soon as this is what our customers want.
So it's all driven based on the customer feedback, not just by ambition to conquer the world and build the best model in the world.
Do you think every company will have their own models?
Like we're seeing Harvey, we're seeing Cognition, we're seeing McCaw, Ramp build their own models.
And we'll see every company have their own models with their own data, or we actually all use a series of providers.
So first of all, whenever...
to be honest, whenever someone says we build own models, very likely what they mean is something what's happened with Cursor.
We do remember, right?
A lot of companies, they actually take open weights model and just post-training on data.
And post-training can happen in two ways.
Most important is whenever you have customer data around like decisions they make, like sequence of decisions, and you can teach the model to actually take, like, learn how to compress these 10 steps into one step.
Like this type of reinforcement learning is the most valuable.
So and I think like increasingly more and more companies will have to do that.
We see this in the market as well.
So most of the companies in the world today, most of the businesses, they don't necessarily need Astra specifically.
They don't necessarily need the newest Fable model.
That's why Open Router reports that share of open source models went from below 30 to over 60 within this year.
What do you think share of open models will be in two years' time?
Look, I do believe that just because the capitalism works, I mean, open-air and anthropic still are going to have more than 50% of the markets.
In terms of the dollars generally.
In terms of the dollars, right.
And especially because for coding still remains to be a very prolific use case where coders are always jumping to the recent model.
But for our markets, we're seeing completely different dynamics.
What's actually happening in social media marketing as companies start to print hundreds of ad creatives a week?
they want to have maybe cheapest, more steerable models, because like PhD level intelligence is not necessarily needed to make viral social media video.
And that's where we actually have seen that we get 80% plus margin whenever we run open source models, like post-trained open source models, but it can be way more cost efficient for our end customer compared to the proprietary models.
What's the comparison on margins between open versus closed for you?
The margin on own models and open weights models is over 80%.
And then it almost doesn't matter.
And for closed source models, it's probably between 20% and 30%.
And then what becomes important is, can we actually steer the traffic?
What makes me excited about Higgs field is that Igentic grows so quickly.
And actually for us, As companies start to actually create those organic workflows to make more ads, we choose which model we can use.
So we choose what model to use in over than 40% cases.
In a way, model routing becomes a core feature of the business, no?
Yeah, we call it tokenomics essentially, right?
As like there is certain amounts of work customers want to do, how can we optimize number of tokens which is required and how we can pick the most efficient tokens for them?
There are actually two incumbents in the United States who figured out models.
It's not just Google, it's also NVIDIA.
Why do you think that is?
What I'm constantly seeing is that there is divergence of models.
So there are these state-of-the-art models which have to be really good in computer use, like Astra or encoding, but they can be prohibitively expensive.
And we're chatting about that.
Like on average at Hicksfield, a person on the team spends over $10,000.
Over $10,000.
dollars a month on various models.
And remember, we're split across United States and Asia.
So how much do you spend on models per month?
So internal usage of models a month is over 4 million.
Wow.
How many people do you have?
We have close to 400 people.
And just want to make sure that the math adds up.
Yes, it's definitely over $10,000 per person.
How has that changed over time?
That's the best question of the whole show, by the way, that's the best question.
What actually started to happen is the creative team started to do vibe coding.
Like this month, I was I just caught a guy who spent over 30k in a week on Astra model, because he was frankly frustrated that some like asset organization workflow.
And as you said, like basically auto editing is still not very good in production.
And he said, Oh, I'm just gonna do this myself.
And just went like five nights straight on Astra.
And it works?
We learned a lot.
I wouldn't say it was production ready, but we learned a lot.
30,000 in a week.
Yeah, yeah.
Many people spend over 10,000 in a week.
Do you mind?
Yeah, my finance team will probably say, I don't know if you ask any of them, but they will probably say that I'm being too stubborn, too relentless to control this spend because sometimes I feel it really goes out of control.
Like 30K in a week is quite a lot.
But we learned.
So this was actually a net passive experience.
Okay, so the internal spend, 4 million, about 10,000 per head.
What will that be in 12 months time, do you reckon?
So across the top engineers and across top creatives, it's going to keep growing.
And I do believe we are going to get to spend close to 50K and 100K a month for those who can call 10X engineers, 10X creatives.
Unfortunately, I also expect that these people will...
ask for a comparable salary raise as well.
So I think that's just going to correlate at some points.
But also for a lot of other jobs, let's say we take legal, finance, and so on, it really stabilizes around like $500,000 a month very, very quickly.
With those 10X engineers, the idea is they have thousands of agents running below them doing a lot of...
the difficult execution work that took time.
Do we just have dramatically smaller teams with those 10x engineers, 10x designers, 10x finance leaders?
I can definitely say that I had sort of a feeling that legal customer support is going to be mostly replaced.
And that's obviously one of the main mistakes operationally, which we have done in the company, that we didn't ramp these teams quickly.
What we're seeing today is that, like, let's say our legal team is like over 10 people.
Our customer success team is over 40 people.
All of them use AI heavily.
at these professions where I stay quite close today, I definitely can say that I don't see any elimination.
It's true that probably over 60% of customer support requests, especially the first line of defense, can be handled with AI.
But when it especially comes to B2B, AI just doesn't work.
Revolut has now over 92% resolution rate on customer support for consumers.
Pretty good.
It's pretty good, but obviously they did invest a lot into that.
A shit ton.
But also very important, the way how Nick thinks about that is in terms of the playbooks.
We launch products, new products, pretty much every week.
We have to keep up the agents with all the information and so on.
And just due to the high velocity, having extremely smart coordinated team is very important.
That's really interesting how product velocity increases, leads to harder customer support for agents.
Of course, because the agents are as good as context and rules which they have.
And if context and rules change pretty much twice a week, it gets a little difficult.
When you look at your engineering team today, what are they on?
Are they on Cursor?
Are they on Codex?
Are they on CallCode?
So from a period from March to June, everyone really moved to Claude, including the creative team.
And that's where we actually started to see creative team vibe coding functionality.
which we don't have in production.
But then we started to see that all the colors quickly moved from cloud to codex as of mid June.
Over the time, creative, especially 10x creatives, moves to codecs as well.
But look, I do believe that it's cyclical.
It's so cyclical.
My question to you is, will we continue to see the velocity of model release that we're seeing now?
In three years' time, will it be like, oh, Gemini this week, oh, Anthropoc this week, oh, OpenAI this week, or will we see a reduction in model release rate?
I don't think that's going to happen anytime soon.
I believe, for example, recently OpenAI announced that they basically built OpenAI for law, but that's only V0.
So over the time, they also are going to try to print smaller specialized models for, not exactly smaller, but really specialized model for certain use cases.
Clearly, Astra excels in long-term horizon.
Do you buy that?
I look at that GPT for law from Astra and I'm like, I'm sorry, I think it's complete bullshit.
With the greatest of respects, it is a very deep functionality required to serve some of the biggest law firms in the world.
Very, very deep and specific functionality.
It's very specific according to the different types of law as well.
Plus, if you want to sell into these law firms, it's a multi-year sales cycle with some of the stodgy old lawyers and partnerships.
You can't just say I'm open AI.
Yeah, we've just hacked into the Australian government, by the way.
But we're here to serve your law firm.
Okay.
First of all, I think definitely the ability to switch internal use just for internal teams outside of law firms.
I think that's definitely happening.
Oh, I think we both invest in a company called Solve Intelligence.
Love it.
Yeah, very specific.
Very specific.
And let me try to maybe bring a couple examples why like Solve Intelligence is so special and like where like, for example, how we learn from this.
What can happen very often is that a company wanna just control the patent workflow, even if they outsource the work.
And that's very valuable just to have one system of records.
So whoever can create AI native system of records is gonna win.
And by going back to Higgs, why it's so important for Higgs field.
There are so many systems today which are used for just to store assets.
Like some people use Dropbox, some people use Google Drive, some people are going to try to use Miro, some people are going to try to use frame.io.
Like there are many solutions.
But let's think about what people need.
What people need, they want to be able to search contents and marketers especially want to make sure that content is on brands.
In terms of the visual identity, but also like if that sort of adheres to certain brand guidelines and that's where like semantic understanding and semantic controls become finally possible it never existed before so in our space there are definitely other companies like adobe and canva who builds the best software for the pixel first era where everything was defined with pixels but that's clearly not how the world is going to work in the future what we're envisioning and that's what everyone wants they want to just be able to search and really work through the library of assets and all the knowledge through natural interfaces so being able to own this interface and build the analytics like this system of records is important that's why at hicksfield we invested so much in harness so that it improves over the time And this harness also allows, it basically learns visual style over the time, which let's say Claude and OpenAI cannot necessarily do.
Do you believe in moats anymore?
You've been around startups for a long time.
We always talk about moats and defensibility.
I largely think they're bullshit.
You know, we saw Lovable.
When I invested, everyone was like, oh, it's a rapper.
It's a rapper, you idiot, Harry.
And actually it was a rapper, but it's about...
speed of decision making, product execution, and building value over time very, very fast.
Instinct is a wrapper.
Of course it is.
It's not that difficult to do an AI assistant today, which is why there's so many, but they're building incredibly quickly, very valuable features, and you build it over time.
Do you believe that moats actually exist, really?
I think it's very difficult to figure out where the value accrues in the supply chain.
We do believe that there are only two like ways of modern value creation or mods today.
First is when you deliver the outcome.
And for us, it's allowing businesses to sell more through AI ads.
So that's the first thing.
And the second thing is network effects.
Unfortunately, AI does not replace network effects.
And when people talk about swarm of AI agents talking to each other, I'm not sure this is happening in the next five years.
That's why it's so exciting that within Hicksfield, like we really wanted to empower community to create more projects, open source, open source them to really build a snowball where people can capitalize on each other output.
This is the reason why software grows so quickly, because it's so easy just to go and fork someone's project on GitHub, we were able to scale from basically like, I don't know, 10 seeded projects, open source projects like eight weeks ago, to over 10,000 today, like seeing these type of network effects.
I believe, can become emote over the time.
When we look at your growth, fundraising is a big part of it.
It costs a lot of money to be able to spend $4 million on different aspects of inference spend.
What was the best VC meeting you've ever had?
Obviously, Yuri Milner gets it.
How was that meeting?
Was it in person?
Yeah, definitely in person.
Definitely, Yuri stays on top of all the trends.
Where was it?
Were you nervous?
I wouldn't say nervous.
It was just more to see how much of the, if we see the market the same way.
And I was truly surprised that Yuri deeply understands this transformation of content first and foremost.
Obviously, it starts with this direct-to-consumer AI ads.
It starts with short-form dramas.
All these trends come from Asia to the West.
Also, fundamentally, we believe that most of contents on social and in the world is going to be AI assisted or AI generated.
And like this multi-trillion advertisement industry, and you know, like contextual advertisement is the main business model of the internet.
It's all going to be substantially disrupted with video AI.
This industry still going to be very valuable, but it's never going to be the same.
Did you know when you left the meeting with Yuri that he was going to write the check?
You know, sophisticated investors, they can play games.
I had like so many scars.
Like people really shook hands, said we do at this price.
And next day, what I learned is that they called other investors and they pulled the syndicates to invest in 30% lower valuation compared to what we discussed.
So like, look, these things just happen.
So you never can be sure.
But it didn't happen with Yuri.
I think there's a discount placed on Higgs field because you're not Silicon Valley insider.
Do you think that's fair?
Let's be clear, you're at a billion in revenue now.
If you were a Silicon Valley company, that would easily be a $25 billion company, growing at the rate that you're growing in 18 months.
Yeah, you could also argue that's what cognition was valued at 50, right?
So there is definitely an upside.
Okay, up a bound even more, 100%.
So a couple of things which I believe are very important.
So first, we build for long term.
We have seen that direct-to-consumer space, like e-commerce can be disrupted, like Shopify is a great example.
how they have become infrastructure to build direct-to-consumer businesses, and we become infrastructure to essentially build distribution for direct-to-consumer businesses.
That's one aspiration.
And second aspiration is obviously AppleAvin.
The company is worth over $200 billion.
It's insane.
So look, and as we think long-term, just these multiples don't matter that much.
As we know, we're building long-term.
We're going to be over $100 billion.
It's true that most of the people...
don't get the opportunity that we are going after the biggest industry in the world.
But I wanted to drop another number.
So when I, and I asked the team to double check.
So it's at least four people on the team who proved, so it's not like random fact.
So I asked, when we look at public companies, and we exclude pharma and big tech, spend on sales and marketing is higher than spend on R&D.
When it comes to sales and marketing, the goal is to deliver personalized offering.
which converts the best.
A lot of that is human work, of course, but a lot of that is going to be personalized videos in some shape or form.
So that's why I'm saying that many people just, and it's good for us that many people don't understand the opportunity, this large market, which we go after.
You've mentioned Asia short-form dramas a lot.
What percent of revenue is from Asia versus the West?
So, oh, the West makes well over 70% of revenue.
Oh, wow.
But just important to say that we learn a lot from trends coming from Asia.
Hicksville does not exist in China, for example, which is massive market for AI.
The largest city by usage is Seoul in South Korea, while the largest country is obviously the United States.
What's the biggest lesson from Asia that you've learned?
There is so much IP, so many products coming from Asia.
and they all try to figure out distribution direct to consumer.
That's why they lean into the new tooling like video AI, which actually helps to achieve that.
That's just a very different mindset.
They feel that they could do way better if they could establish direct relationship with customer instead of having like some other layer.
That's why they go so much direct to consumer rather than using some resale platforms and so on.
I sacrificed a lot of life for the life that I have and the career that I have, and I love it.
Do you think you will one day regret spending a day with your son in three and a half months?
Look, this goes even beyond that, because from the age of seven to 12, my mother had to work three jobs, so I didn't see her.
My father was spending all the time with me, going to all, and it was basically minor, so he had to go to all these camps with me.
I also played checkers.
I was top three in the world.
So we went, we traveled throughout the world.
Then I did programming.
He spent all the time with me, like really dedicated his life to me.
Like he did sacrifice.
And since 21st, he has Parkinson's disease.
So even like having some ability to capital and exits cannot fully change things.
And this is something which is deeply personal, obviously.
But you don't need to do what you're doing now, Alex.
I don't need to anymore either.
I still am.
I still miss family birthdays.
I still miss weddings.
Because, like, mine's about a deep insecurity rooted in me being a fat kid.
Why are you doing it?
So I think Marc Andreessen actually described it really well.
There are, like, five archetypes.
So obviously for me, it's just huge conviction about the technology, about the markets, about the opportunity, and just huge fear of missing that.
Huge fear of missing that.
But remember that my parents really...
taught me that there is a place in the world where technology, like good technology products matter.
I remember like when I was six, there was like this, I guess, magazine about Bill Gates, like building Microsoft and not being like very like socially accepted everywhere back then.
And like my mother just told me, oh, like these examples basically happen in the world.
I think she didn't fully understand like San Francisco and Seattle are different cities, but still that's still deeply rooted in me.
Childhood shape us a lot.
What did your parents teach you?
For them, what was important is to just be in merit-based environments, sort of.
And that's why getting to California felt so important.
What's your biggest lesson on hiring, speaking of a merit-based environment?
We see a lot of focus on your cognitions of the world who hire, maths, olympiads.
Yeah.
What's your biggest lessons on hiring effectively?
I think one of the things why...
Europe thrives so much.
Like, I know that you typically say otherwise, but let me just challenge you, like, who are the most relevant NeoClouds today?
It's Nscale, IRAN, and Nobius, and Crusoe.
Crusoe, okay, is Silicon Valley story.
IRAN from Australia, Nscale from the UK, and Nobius is UK and Netherlands.
Let's talk about the companies on application layer that matter.
I know that you mentioned Mercore, And you mentioned Harvey, but Legora, 11 Labs, Lovable, they all deeply matter.
So if we just go outside of the model layer, because then I don't want to go into the mistral topic, right?
Because I think like by usage, the numbers are very strong, but people for some reason don't believe in that.
I don't know why, but public data shows that the usage is there.
But on every other layer, Europe is extremely competitive.
like asml like without asml this whole thing just wouldn't happen so i think fundamentally what matters if if like europe is going to figure out energy but that goes outside of that's above my pay grade right um so very important to say here is that now there are more opportunities to create company from different kind of cities from different parts of the world while before it all felt extremely centralized And we are obviously excited about that.
Another thing about hiring is that in Silicon Valley, unfortunately, what I'm seeing is that people just jump between jobs every two years.
That's why I think Europe can be so competitive because the sense of loyalty matters a lot.
And that goes sort of a little bit to the childhood.
We just discussed that.
Let's say if you're a Fuham fan, you are not going to root for Arsenal just because they won or played in the Champions League final.
But...
In the United States, if Lakers are on the top, people are going to say, yeah, I'm fan of Lakers because it just makes it easier to start conversation, you know.
When you think about your own CEO style, what's changed most?
In AI, it's so important to look at actual signals and actual adoption and having access to raw information.
I was obviously taught the corporate school of management in the United States.
And when I look at the CEOs whom I'm learning from is obviously Jensen, Elon, and Nick.
Those three, they completely abandon all the management principles.
They don't necessarily are like fans of like one-on-one and like soft feedback.
All of them, I think, are encouraged, like being down to the points, knowing the details.
while it would be called in like corporate America something like micromanagement.
What management principle do you disregard that many people think is important?
I do believe that it's as simple as hire the best people to do the best work and figure out how to retain them.
Everything else is frankly secondary.
And people just create so much theory around that.
And then essentially there is just so many like fake rules which are disconnected from reality.
It's really as simple as hire the best people, empower them to do the best work, and just figure out how to establish relationship and retain them.
A lot of them do see dollar signs and secondaries are a part of that.
How do you think about doing annual tenders to retain people?
Across our team, roughly 50 are in California.
We're going to get to roughly 50 remotes and over 300 in Kazakhstan.
So look, I just hope we're going to print more dollar millionaires in Kazakhstan, in Central Asia, in this part of the world than any other company.
What's the labor arbitrage on cost between Kazakhstan and the US?
I know that a lot of people, when they look at Hicksville, they think about the arbitrage.
Is that not true?
Look, like Kazakhstan is top five in the world in physics.
Like you look at the recent International Physics Olympiad for high schoolers, like they're top five in the world on pair with like the United States, China, India.
And this is also like the core of our team are people who won international competitions in math and physics.
That's the first part.
The second part is that about Kazakhstan is that they actually took the Soviet school of math, but really upgraded with Singaporean principles.
And Singaporean system of education is considered to be probably the best in the world.
At least many people in Silicon Valley believe that.
And the government basically subsidizes.
for thousands of high schoolers to study abroad.
And many of these people come back.
And so just the density of talents definitely got there.
It's like top 10 largest countries in the world, over 20 million population.
And we are also actively hiring, bringing their talents from Europe, from other countries in Asia.
And people just enjoy like some benefits, like 15% personal income tax.
Yeah, man, it's like...
Don't even get me started.
Fucking UK will tax you to breathe.
Seriously, in the UK, you get your paycheck, and then it's like, I don't know, 100,000, and then you get the end, and it's kind of like 3,500.
But it's also English common law.
So it's not like that bad as people think.
You move here.
Let's swap places.
Do you have a mega pad in Kazakhstan?
No, I don't.
I don't own any property.
What?
Why?
Remember that I come from Asian family.
Whenever we sold the company, I made over a million dollars and I spent all this money buying apartments for my parents, relatives, my wife's parents, because this is just part of the culture.
Wow.
And the extended family is not small by any means.
But look, it's just part of the culture to give back.
And then when it comes to the family, especially to my parents, they obviously sacrificed a lot.
So I felt like I had to give back at least monetary things, which I could do.
But I drive Tesla Model 3 and I sleep.
So I'm not like a guy who's going to just show up with Lamborghini or Porsche.
Do you invest?
We mentioned Solve Intelligence.
Before I did that, but now I spend roughly 90 hours a week, 80-90 hours a week on Hicksfield.
I try to spend ideally at least three hours a week with my wife, at least five hours a week with my son.
Sometimes I do the catch up because when I travel for a week, for two weeks, for three weeks, then I try to take Sunday off.
to spend the whole day with my son and over the last three months yes i was able to find one day when i spent like end-to-end with my son without emails without talking to without talking to the team members i get in trouble for this but I think there's no shortcut to hard work.
The harder I work, the luckier I get.
I meet more founders, I find more great companies, I do more shows, I have more success.
Do you buy the bullshit of the balance and the, oh, it's okay, you can leave at five and be home for bath time and crush it?
This is a good question.
So look, obviously, being an immigrant, I always have to prove.
Like that's I belong, right?
So I hope that I feel like now people accept, people recognize that Hicksfield is probably a top 10 application AI companies by revenue, probably number one.
But I think when it comes to hard work, like the people whom we know in common, like we talked about, like, let's say Peter Salis, like legend in the consumer space, obviously Jack.
I spent decent amount of time with them and other product leaders at Stamp.
The density of product talent at Stamp was unprecedented.
All of them work really hard.
All of them are smart.
None of them just checks emails for five hours a day and calls it work.
Each of them is deeply rooted into the recent trends in product, product design, activation.
They know data really well.
So yeah, I don't believe that there is any shortcut to hard work.
Three hours a week with your wife.
I don't know about you, dude.
Mine would dump me for three hours a week.
How do you make marriage work on three hours a week?
Yeah, look, I'm very grateful for my wife for being patient.
You know, it's also very different if that's like Asian culture.
It's just kind of more natural to try to do sacrifices for each other, sort of.
And I'm deeply, obviously deeply grateful for her for supporting me.
But like sometimes at this scale, I get invited to parties.
I always send her and don't show up myself.
I don't know if I piss people off, but this happens very frequently.
So wait, you say yes, and then she goes.
Yeah, I say maybe we both can come together.
Then there is always some urgent fire last minute, and my wife just goes.
What fire was most urgent?
What was the, oh, fuck.
yeah look i think obviously for all the things which we touched based earlier whenever we are not very good in communicating the features or we felt like i mean now it's like team of 40 so now the life is way better but early days obviously i was involved in all the fires i think recently all the types of like attacks on ai companies it's crazy it's like llms are being used to hack companies.
It's like new types of LLMs to do some frauds, you know, like basically bots using credits and then doing auto refunds, all of that.
Like since I have like kind of machine learning background myself, data science background, I still can move a needle substantially when it comes to statistics and data.
So yeah, I have to be involved somehow.
But like these LLMs, they amplify many types of behaviors, including various types of attacks and fraud.
But we have to fight against that.
We're going to do a quick fire round.
So I say a short statement, you give me your immediate thoughts.
What have you changed your mind on most in the last 12 months?
Oh, I was thinking that HubSpot is going to get obsolete.
Everyone is going to build their own CRM.
But when, especially when we hire and scale B2B go-to-market team, just having familiar interface matters a lot.
Wow, I would still say they're going to get fucked.
You think that just stickiness is there with SMBs?
Yeah, I do think so.
And especially I see that when I hire go-to-market talents.
Wow.
Why?
What is it about hiring them that makes you think that?
They're so used to it.
I mean, people who are very good in understanding customers and talking to customers, they may not just simply accept new interface so quickly.
And just having HubSpot as a system of records, being able, if there is any mismatch, going able to just understand where the data flow went wrong, I think that's just still very valuable, like the familiarity.
What do you believe today that everyone else thinks is fucking crazy?
I mean, look, I think people just still don't fully appreciate that most of the content on social media is going to be AI generated.
There are going to be some shows, like obviously yours, where it's like authentic content.
It's going to be 1050x higher CPM, whatever, than AI generated content.
So it's going to be way less in terms of like content created by, but it's going to create way more value than AI generated content.
But even when I look into your content specifically, like you made multiple very successful shorts, millions of views, better than anyone else in this space, and you do a lot of overlay.
While the content is authentic, I think we should do a better job so that you use Hicksfield, at least for the overlay on top of existing videos.
Dude, I would love that.
I mean, again, they take three hours.
People don't know this.
I spend two hours a day just doing Instagram now.
We decided that Instagram in short form is going to be a big new push for us.
Two hours a day just for me.
I write the scripts and then I record them.
And then it's two people, six hours per one for those three.
And that's extremely smart of you.
You know, like going back to some of the topics is like clipping is like a huge topic.
And that's like has its own.
upsides and downsides.
But obviously, everyone sees this opportunity to win, to build massive top of funnel, like hundreds of millions of views with short form contents, as long as you can have downstream monetization, like or value creation like you do.
Totally agree with you.
What job today does not exist that will be big in five years?
Okay, so in five years, people, especially in our space, creative directors, they are going to be talking to computers.
and generating stories real time and video and ai is gonna help to create multiple variations today there is no word to really describe that because there is also there are script writers then screenwriters like those who are gonna break it down shot by shot then there are people who do that storyboarding then there is like people who person who oversees all of that like movie director and so on.
So there are so many parts of that, but eventually taste is going to matter a lot and just having stories to tell.
There is no word to describe it today.
Who do you not have on your board that you would most like to have on your board?
Maybe out of like more professional CEOs, I'm definitely Frank Slootman.
Because going back to the point, I was just curious all the time.
Does no bullshit culture exist in California or not?
Can it allow to scale companies so quickly?
Is it possible to build successful enterprise go-to-market motion with no bullshit culture?
And when I read his Amp It Up book, like book called Amp It Up, I realized it's possible.
So like, I'm a huge fan.
I watched all his interviews.
The challenge with him, he's amazing, he's the best leader by far, but the challenge is you can sometimes do it at the sacrifice of product advancement.
And so he built a GTM machine at Snowflake, but Databricks wiped the floor because they move product as the priority, not GTM.
And that was dangerous.
I prefer Chad Peets.
Do you know Chad Peets?
Nah.
Oh, dude, this guy is no bullshit.
I'll introduce you afterwards.
He's the best sales leader in the world.
And he is no fucking bullshit.
Unbelievable.
And we probably should have him on board.
Oh, my God.
I can find any way to have him on board.
He is terrifyingly good.
So what's the biggest lesson from Snap?
The momentum doesn't last forever.
Like today, Snap market cap is below 15 billion.
There are lots of memes on the internet, but this is a great company.
It cares so much about trust and safety and experience, and it puts it first.
Do you think it is a great company?
No offense.
It's been mismanaged to shit.
It's SBC is through the roof.
It's tough to say it's a good company.
That's why I say that momentum doesn't last forever.
When Snapchat was worth $80 billion, and the gap with meta was less than 10x, then it felt, oh, we just go explore, we just really must lean in, but momentum doesn't last forever.
And that's my core learning.
So that's why, like, while we do have the positive momentum, we do not take this for granted.
Clearly, like, the nature of capitalism is there are ups and downs.
And since we're building long term, we just should capitalize on the opportunity, like with the fundraising, and just keep pushing progress every day.
What is the reason why the divergence between Meta's market cap and Snap's market cap has increased so significantly, if there was one reason?
Just maybe saying this straight, a lot of public companies did not figure out their AI story.
Snap, unfortunately, is part of that.
We have seen other great companies like Figma.
trying to tell their story you mentioned canva it's not necessarily easy to be successful in private markets and public markets and zach is one of the best ceos of all time because he managed that such a beast he's such a beast you watch him last night with the event and you're just like ah now i get it like that totally makes sense and you know what scale with alex wang i was one who was like really like what's gonna he basically acquired a second ceo you know alex is now the ceo of muse and he's crushed it crushed it what an effective buy for 0.5 of your market cap do you know what i mean yeah look but this happens with instagram with whatsapp that's why i'm saying that we just maybe should put meta a little bit in its own league yeah but he got rid of system and trigger Here, he's been like, no, no, no, you, Alex Wang, are my guy.
Do you see what I mean?
Yeah, look, I do believe that it's a little bit early to look at whole Meta AI initiatives.
We probably need to see like a year of like successful launches and so on.
And then we can look back and see what was good, what was not good.
But at least the consistency of storytelling and explaining what he is doing to public investors, being able to articulate why Muse is so different is phenomenal.
Okay.
Revenues say are a billion.
What are the revenues in 12 months' time?
Our current business model projects 4.5.
It is by the end of the next year, but this basically involves substantial deceleration.
And that's what just my finance team, there are a couple of strong quant people, they told me that's just how the business works.
But look, we are still pushing to grow at least 30% month over month.
What do you think it is?
They said 4.5.
What do you think it is?
This is me to you, not me to your finance team.
Over 10.
Over 10.
Let me tell you why.
In a lot of adoption and creative AI space is driven by monetization, like all these direct-to-consumer brands making more ads, and also having the aspirational cinematic AI content as this inspires creatives to explore the tooling.
It feels to me that Hollywood starts to embrace AI mostly today as a tool for hybrid production, as a just new form of CGI.
But the sentiment really shifted from like strictly negative to neutral to slightly negative.
And in private conversations, yes, there are maybe more than half of STR talents who is going to say we're anti-AI forever.
But increasingly, there are more and more people who are actually asking a question, can we tell more stories with AI?
Can we overcome certain budget limitations which existed before?
And maybe AI can help to tell new stories which we couldn't tell before.
And I do believe this just change in perception that at least comes from my conversations is extremely positive.
If you are at a billion today, 10 billion in 12 months, why do you peg the next fundraise?
If you're in a billion, say, a conservative multiple, you'd be like 15.
But if you're hitting 10 next year, you're like paying end of year 80.
Look, we're not chasing just the valuation.
Because again, the goal is just to make sure that the company can be sustainable over the time in public markets.
So there is a lot of company building to be done beyond just chasing the revenue.
But I just do believe- Do you want to be public at some point?
Yeah, I do believe that Hicksville has great potential to be bigger than AppleAveen and Shopify.
Because fundamentally, like building is one part of that.
Shopify, one layer of infrastructure.
Then for coding, there is obviously like a cloud.
There is codex.
But what matters is distribution over the time.
Distribution matters.
You know that this better than any other PC, right?
Dude, it's my business.
That's why we do what we do.
Yeah, exactly.
Dude, I cannot thank you enough for being so amazing on the show.
You've been fantastic.
I've loved doing it, you can tell.
And you've been an amazing guest.
So I really appreciate you joining me today.
Thank you so much.
It's a pleasure.
But before we leave you today, founders face a different set of challenges at every stage of growth.
For Sid Shait, co-founder and CEO of Dematrix, JPMorgan delivered the guidance and expertise to help navigate what came next.
He credits JPMorgan's high-touch approach with supporting Dematrix as it grew and expanded internationally.
Whether you're in the early days or expanding into new markets, JPMorgan helps startups navigate complexity with real confidence, offering personalized guidance and deep sector expertise.
Find out how JPMorgan helped founders at jpmorgan.com forward slash grow without limits.
JPMorgan is the bank of the innovation economy.
While JPMorgan supports growth, Corgi protects it.
My word, what an arresting first line.
Get your ass covered with Corgi insurance, and I'll tell you why.
If you're running a business right now, you already know this pain all too well.
Getting insurance, it's really slow, it's confusing, and my word, it's full of paperwork.
Well, that's exactly why Corgi is here to change the game.
Corgi is the first and only insurance carrier designed specifically for tech companies, allowing you to get covered in minutes instead of days.
Corgi provides essential coverages for all growth stages, such as...
DNO, E&O liability, cyber, commercial, general liability, and more.
Get your ass covered.
I love the way we say ass with Corgi Insurance alongside thousands of other startups at corgi.com forward slash 20VC today.
That's corgi.com forward slash 20VC.
You won't regret it.
While Corgi covers risk, Flex gives you room to move.
Business owners run their whole financial life on Flex.
One platform from business revenue to their personal spend.
Float every purchase for 60 days.
Tap capital that grows with your revenue and pay vendors in 170 countries across 32 currencies.
Plus, the whole back office, bills, expenses, accounting, all in one place.
So you spend less time reconciling and more time growing.
That's why thousands of owners use Flex, named one of Fast Company's most innovative companies of 2026.
Visit flex.one, that's F-L-E-X dot O-N-E and use the code 20VC.