Seventy Percent Agencies

Like, what would it cost for me to build a video?

让我自己做一条视频要花多少钱?

Like, without skills and people, I mean, infinity.

没手艺、没人手的话——无穷大。

I'd have to hire an agency.

我得去请一家代理商。

It would come back 2 weeks later.

两周之后东西才交回来。

It would be terrible.

而且做得很烂。

They would charge me thousands of dollars, and I would delete it because I would never use it.

他们收我几千美元,我看完直接删掉,因为根本用不上。

Instead, I can do this in 60 seconds.

而现在,这事我 60 秒就能做完。

And so, it's just it's a visceral example that Alex is able to get five times the ACV up Canva, but even though Canva has mass scale

所以这是个特别直观的例子:Alex 能拿到 Canva 五倍的 ACV,哪怕 Canva 的体量大得多——

Yes.

是的。

by having an intelligent workflow that that replaces humans.

——靠的是一套替代人力的智能工作流。

And honestly, for me, it replaces contractor and agency that I don't have the patience to hire anyway, right?

说实话,对我来说,它替掉的是我本来就没耐心去找的外包和代理商。

Rather than just be helping me create an asset manually.

而不只是帮我手工做一个素材。

All right, everybody.

好了各位。

Special guest moderator, me.

特邀主持人,就是我。

I think Alex is going to join.

Alex 待会儿上台。

We're going to have some fun.

我们会聊得挺尽兴的。

So, Alex is co-founder of one of the most explosive video marketing and other apps, Higgsfield.

Alex 是 Higgsfield 的联合创始人——目前增长最猛的视频营销类应用之一。

You guys should use it.

你们都该用一下。

So, Higgsfield AI, while you're on site, use it.

Higgsfield AI,趁着在会场,就用起来。

And it's changed a lot, but if you look at any of the SaaStr videos that I create, if you watch the Agents, the intro of me and Milly, it's all built on Higgsfield.

它变化很大,但我做的所有 SaaStr 视频——比如《The Agents》里我和 Milly 的片头——全是用 Higgsfield 做的。

And I've been using Higgsfield basically, I think, since it launched or something like that, right?

而且我基本上从它上线那会儿就开始用了,对吧?

For all of our stuff.

我们所有内容都靠它。

Close, right?

差不多是这样吧?

Yeah.

是的。

I mean, and and that means a lot to us.

这对我们来说意义很大。

I think it was August, September.

应该是八九月份。

It was the first time when we started to evolve just from like on the social pure social media play to professional creation tooling.

那是我们第一次从纯粹的社交媒体玩法,转向专业创作工具。

Yeah.

嗯。

And you were the first to spot us.

而你是最早发现我们的人。

So, I love it.

我真的很喜欢它。

I use it all the time.

我天天在用。

If If we have time, we can even log into my account and I can show you all the stuff we're building.

时间够的话,我们甚至可以登录我的账号,给你们看看我们在做的东西。

But, it's real for all of us just trying to learn, I mean, and I'm going to ask a lot of questions.

对我们这些想学的人来说,这些都是实打实的东西,我会问很多问题。

Alex is going to present, and I'm going to pepper a few questions.

Alex 先讲,我中间插几个问题。

Now, they're 300 million in a year, 15 months, or what How quickly?

他们一年做到 3 亿,还是 15 个月?到底多快?

Yes.

是这样。

It took us maybe 11 months to get to 300.

我们大概用了 11 个月做到 3 亿。

Now, it's bigger than that.

现在已经不止这个数了。

Pretty pretty good, right?

挺猛的吧?

So, Alex is going to explain to you and they're going.

接下来 Alex 会讲讲他们是怎么走过来的。

Like, we hear these stories, you know, how did Higgsfield and Lovable and Replicate and it get to hundreds of millions in months and now actually someone's going to be honest and tell us the real story behind the story.

我们总听到这类故事:Higgsfield、Lovable、Replicate 是怎么在几个月里做到几亿的?今天终于有人愿意老实讲讲故事背后的真相。

I'll pepper with some questions, so I'll hand it off to Alex, but I'm a super fan and if you guys watch any of our little short videos, it's all built on Higgsfield.

我会插几个问题。先交给 Alex——我是它的铁粉,你们看到我们那些短视频,全是 Higgsfield 做的。

You're listening to the official SaaStr AI podcast brought to you by Hey everybody, starting a business can get expensive fast.

您正在收听 SaaStr AI 官方播客,本节目由……嘿各位,创业烧钱可以烧得非常快。

Website here, email somewhere else, business phone with another provider.

网站在这家,邮箱在那家,企业电话又是另一家。

Northwest Registered Agent gives you a complete business identity in one place with free tools, resources, and built-in privacy from day one.

Northwest Registered Agent 一站给你完整的企业身份,附带免费工具、资源,以及从第一天起就内建的隐私保护。

Get more at northwestregisteredagent.com/saastrfree.

详情见 northwestregisteredagent.com/saastrfree。

[music] That's [music] S A A S T R F R E E.

[音乐] 也就是 [音乐] S A A S T R F R E E。

Absolutely, this is a great honor for me to present here.

非常荣幸能在这里做分享。

So, let me maybe briefly overview our journey in numbers.

我先用数字简单过一遍我们的历程。

We are excited about a new wave of AI native video creation for social media.

我们很兴奋地看到,面向社交媒体的 AI 原生视频创作正掀起新的一波浪潮。

First and foremost, social media is relatively new.

首先要说,社交媒体本身还很年轻。

It has been around for 15 years and last 5 years it has become the largest media in the world.

它出现了 15 年,而最近 5 年才成为全球最大的媒介。

We're seeing numerous direct-to-consumer companies who actually make hundreds of millions or billions of dollars of sales by by leveraging social media as a distribution channel and using platforms like Higgsfield for content production.

我们看到大量 DTC 公司,靠把社交媒体当分发渠道、用 Higgsfield 这类平台做内容生产,做出了几亿甚至几十亿美元的销售额。

And this is exactly the reason why we are growing so quickly as we are we are addressing this massive demand in the markets to make content for social media every day and build a brand and sell products on social media.

这正是我们增长这么快的原因:市场上每天都有巨大的需求——为社交媒体产内容、建品牌、在社交媒体上卖货,我们接住了这块需求。

So, the the We were the first to maybe introduce camera controls, and camera controls are extremely important for professional creative directors.

我们大概是第一个做出镜头控制的,而镜头控制对专业创意总监来说极其重要。

We were really surprised that it took off so quickly, and within just in like maybe 5-6 weeks, we got to 10 million ARR.

它起量之快让我们非常意外,大概五六周就做到了 1000 万 ARR。

And then, in August, September, and October, we realized that adoption goes beyond just individual creators.

到了八九十月,我们意识到用它的人已经不止是个人创作者。

And since October, the priority is to make sure that creative teams can work together to make videos very efficiently.

从十月起,我们的首要任务就变成:让创意团队能高效地协同做视频。

So, let me give you a few Let me give you a few numbers.

我给你们几个数字。

So, for example, this in a week, we are going to present full-feature movie in Cannes, and we are doing that to showcase the possibility and opportunities unlocked with video AI.

比如一周之后,我们会在戛纳放一部完整的长片,目的就是展示视频 AI 解锁了哪些可能性和机会。

So, roughly, it took a team of 10 and maybe 3 weeks to accomplish that.

这部片大概是 10 个人、3 周做出来的。

So, the efficiency gains are unparalleled.

效率提升是无可比拟的。

And that applies both to long-form and short-form content creation.

长内容和短内容都一样。

Alex, how big's the team today, and how big's engineering?

Alex,现在团队多大?工程团队多大?

So, this is a good question.

这是个好问题。

We have roughly half and half split.

大致是一半一半。

So, 80 people engineering.

工程 80 人。

And engineering is now really broad.

而「工程」这个概念现在非常宽。

I need to acknowledge that.

这一点我得说明。

Software engineering, machine learning engineering are always kind of traditional professions, but the amount of people who do automation, prompt engineering, also increasingly grows.

软件工程、机器学习工程算是传统工种,但做自动化、做 prompt engineering 的人也在快速增加。

And the rest of the team are We have maybe around like 70 people creative team who are not native prompt engineers.

团队的另一半大约 70 人是创意团队,他们并不是天生的 prompt engineer。

And this actually was very important for us.

这一点对我们非常关键。

We learn by external signals and internal signals how to make those models actually usable.

我们靠外部信号和内部信号来摸索:怎么让这些模型真的能用起来。

How to empower creatives to actually use them.

怎么让创意人真的用得动它们。

And what we are seeing is that one creative director can now make ad end-to-end.

我们看到的是,现在一个创意总监就能端到端做完一支广告。

Like let's say within a day.

差不多一天之内。

Like before that, it would take weeks.

而以前这要花好几周。

It would require to assemble like physical production crew, rent a lot of equip- equipments, book a space, and so on.

得组一支实拍制作团队、租一堆设备、订场地等等。

And now it's completely different.

现在完全不一样了。

So, for us, we believe that like one of the core unlocks for Higgsfield is to having creative team and engineering team working together.

所以我们认为,Higgsfield 的核心解锁点之一,就是让创意团队和工程团队在一起干活。

So, at 300 million ARR, you have 60 people in the R&D or in in product and development doing 300 million revenue.

也就是说,3 亿 ARR,你们只有 60 个人在研发、在产品和开发上,撑起 3 亿收入。

We have roughly So, so just in terms of like traditional engineering and product is probably is probably 60.

传统意义上的工程加产品,大概是 60 人。

So, it is it's a still a substantial efforts.

这仍然是相当大的投入。

We we we are moving very quickly when we were smaller.

我们体量小的时候跑得非常快。

Now, we have to invest a lot in stability, safety.

现在必须在稳定性和安全上投入很多。

We have to invest a lot in like things like anti-fraud and so on.

反欺诈这类事情也要投入很多。

So, the engineering team grows cuz I mean, vibe coding is not really good for this really deep infrastructure work yet.

所以工程团队还在扩——vibe coding 目前还干不了这种很深的基础设施活。

But it's to by traditional standards, it's a pretty it's still a pretty tight engineering team even today as you scale, right?

但按传统标准看,即便规模上来了,你们的工程团队还是相当精简的,对吧?

Yeah, I I I I would agree with you cuz let's say typically an a ratio of engineers to ARR would be maybe around two.

同意。一般来说,工程师和 ARR 的比例大概是 2。

For us, this ratio is probably around five today.

我们现在大概是 5。

Yeah, maybe two two to three times more efficient or something like that.

也就是效率高个两三倍。

Yeah.

嗯。

Cool.

不错。

And the And the going back to engineering, it's also very important the very important trend which I see is that the engineering jobs are getting very nuanced. there are for for a lot of new product developments, the team now can consist with just just of one person and they can and they can maintain fast space of developments.

回到工程这块,我看到一个很重要的趋势:工程岗位正变得非常细分。很多新产品的开发,团队现在可以只有一个人,而且照样能维持很快的开发节奏。

So, for us what's important is we we help we deliver time to value faster than any other platform and we have this feedback loop.

对我们来说重要的是:我们的 time to value 比任何平台都快,而且我们有一个反馈闭环。

As we see what's trending, we see what users post on social media and using this to improve Higgsfield.

我们看什么在流行、看用户在社交媒体上发什么,再拿这些去改进 Higgsfield。

And I think that's very important for us to make sure that we have this unique blends of researchers and the filmmakers on the team.

我认为很关键的一点是,团队里要有研究员和电影人这种独特的混编。

Most of the team is still is is really centered around kind of those who made commercials and they and all the materials published by Higgsfield — Higgsfield's YouTube channels, all of that is generated with AI.

团队里大部分人其实是做过广告片的;Higgsfield 发布的所有素材——包括我们 YouTube 频道上的内容——全部由 AI 生成。

It's always generated by our platform.

永远是用我们自己的平台生成的。

That's how we establish trust.

我们就是这样建立信任的。

So, the reason why we're doing full-feature movie in Cannes is another way to show what's actually possible with technology today.

所以我们去戛纳放长片,也是为了展示今天的技术到底能做到什么。

And we have over thousands various tutorials on the on YouTube to help with this transition from traditional production to AI native production for for creative professionals.

我们在 YouTube 上放了上千个教程,帮创意从业者完成从传统制作到 AI 原生制作的过渡。

Jason, this is exactly the points what I wanted to bring up.

Jason,这正是我想讲的点。

Like we are not building in a vacuum.

我们不是关起门来做产品。

We listen to feedback on social media, on Discord channel, Reddit, but also we have a team of 80 creative professionals who help our engineers to build. we also learned that also we made a very controversial bet early on.

我们在社交媒体、Discord 频道、Reddit 上听反馈,同时还有 80 位创意专业人士帮工程师一起造。另外我们也学到一件事:很早的时候我们下了一个很有争议的赌注。

We made a bet that number of people who need social media video, number of people who want to sell is probably tens of millions of users, but number of people who want to learn prompt engineering is probably hundreds of thousands.

我们赌的是:需要社交媒体视频的人、想卖货的人大概有几千万,而愿意学 prompt engineering 的人大概只有几十万。

And there is this immersive gap which someone has to close.

中间这道巨大的鸿沟,总得有人来填。

That's why we started with social first user experience.

所以我们从社交优先的用户体验做起。

What's also very interesting is we see people buying up more and more credits on top of the subscription.

还有个很有意思的现象:用户在订阅之外还不断加购 credits。

So, and that's very natural for all the marketing technology.

这在营销技术里是很自然的事。

Like I I personally like like I know like 7 years ago learned a lot about that from reading SaaS stories that like one of the positive things about marketing technology, one of the positive trends is that customers come and buy more more and more of the product if they use it more and if they can convert and drive more sales.

我自己大概七年前从 SaaS 的案例里学到:营销技术有个好处是,客户用得越多、转化越好、卖得越多,就会回来买得更多。

And we built a trust that all the new video AI models are available on Higgsfield so that it's one AI video studio for content production.

我们也建立了这样一种信任:所有新的视频 AI 模型在 Higgsfield 上都能用,它就是内容生产的一站式 AI 视频工作室。

Let me please show how it works.

我给大家演示一下它是怎么用的。

Let me show you the city city.

我带你们看看这座城市。

I'm creating fashion campaign with three locations and one model.

我在做一支时尚广告,三个场景、一位模特。

First, I build my character in AI cast.

首先,我在 AI Cast 里建好我的角色。

The platform generates a full character sheet I can reference across every scene.

平台会生成一整套角色设定图,后面每个场景都能引用。

Same with locations.

场景也一样。

Move to the dawn, the minimalist studio and Tokyo at night.

换到黎明、极简风摄影棚,以及夜晚的东京。

Now, I can start generating.

现在可以开始生成了。

And here's my model in the studio holding a product.

这是我的模特在摄影棚里拿着产品。

But I want to explore other options.

但我想多试几种方案。

So, relight gives me the different lighting directions and color.

Relight 能给我不同的打光方向和色调。

Angles generates new character assets from the same image.

Angles 能用同一张图生成新的角色素材。

I pick the best one and I move forward.

我挑出最好的一张,继续往下走。

Now, I'm ready for the video.

现在可以做视频了。

I have full control over the camera, the lens, the aperture, the focal length, the style settings for color, the lighting, and how the camera moves, as well as the genre that shapes the base scene.

镜头、镜头规格、光圈、焦距、色彩风格、灯光、运镜方式,还有决定整场基调的类型片风格,我都能完全控制。

Or, I can ask the AI director.

或者,我可以直接问 AI 导演。

It knows my characters, my locations, and the style I'm going for.

它知道我的角色、我的场景,以及我要的风格。

I tell what I need, and it writes the prompts that picks the best settings for this version.

我说出需求,它来写 prompt、挑出这一版最合适的参数。

I hit generate, and the character stays consistent, the location matches, and audio is synchronized.

点生成,角色保持一致,场景对得上,音频也同步好了。

Now, when I'm ready, I share this version with my client to review and collaborate.

做好之后,我把这一版分享给客户,让他们审阅、一起协作。

And the And And this is very important.

这一点非常重要。

I wanted to pay attention to to the last piece.

我想请大家注意刚才最后那一步。

What's important is that video creation becomes digital and that's asynchronous.

关键在于:视频创作变成数字化的了,而且是异步的。

And that's very important.

这非常重要。

So, the reason why software evolves so quickly is that there is a lot of There are lots of open-source projects, and people naturally build on top of each other.

软件之所以演进得这么快,是因为有大量开源项目,大家天然地在彼此的基础上往上搭。

Historically, video was extremely gated, meaning that it was It's nearly impossible to to reproduce, to kind of see how these popular movies, how music clips are built.

而视频历来是高度封闭的:你几乎不可能复现,也看不到那些热门电影、音乐 MV 到底是怎么做出来的。

And we see a major democratization across the space as those prompts become available, projects become available.

现在 prompt 公开了、项目文件也公开了,整个领域正在经历一次大的民主化。

People can see like the behind-the-scenes, they can see the prompts which were used to make a video, and they can collaborate Teams can collaborate together digitally.

人们能看到幕后过程、能看到做这条视频用了哪些 prompt,团队之间也能在线上协作。

So, to to really like let's say make make videos together.

真正地一起把视频做出来。

Like historically, what we have seen with incumbents like Adobe is that it used to be like desktop tooling, all the storage was on desktop, and it was just very cumbersome process of constantly exchanging files and so on.

而看 Adobe 这类老牌厂商,过去都是桌面工具,存储全在本地,来回传文件的过程非常繁琐。

We bring it all in one platform.

我们把这一切都收进一个平台。

What we also learned is like these models evolve so quickly.

我们还学到一点:这些模型迭代得太快了。

So we work on behalf of our customers to build a trust with them that they will get the best models optimized for the four specific workflows on Higgsfield platform.

所以我们替客户去盯这件事,让他们相信:在 Higgsfield 平台上,他们拿到的是针对具体工作流调优过的最好模型。

So we ship pretty much every day.

我们基本上每天都在发版。

Like last last year on average we were shipping six times a week.

去年平均每周发六次。

This year as we pay more attention to stability, it's probably two or three times a week.

今年因为更看重稳定性,大概每周两三次。

And earlier today there was another major launch where we introduced our marketing agent called Supercomputer.

就在今天早些时候我们又有一次重要发布,推出了名叫 Supercomputer 的营销 agent。

So um with with all of that, we we are excited that we we are able to emerge as number one platform in multimedia AI.

靠这些积累,我们很高兴能成为多媒体 AI 领域的头号平台。

And there are many direct-to-consumer brands who actually can achieve product and brand consistency.

很多 DTC 品牌确实做到了产品和品牌形象的一致性。

And they are scaling their social media budgets to tens and hundreds of millions of dollars with AI-generated videos.

他们正把社交媒体预算加到几千万甚至上亿美元,全部投在 AI 生成的视频上。

It's very important to say that in some categories, especially when it comes to mobile apps, AI-generated ad creatives are absolutely necessary.

必须说明的是,在某些品类里——尤其是移动应用——AI 生成的广告创意已经是刚需。

This is the AI-generated creatives is the only way to get people attention cuz there is a strong novelty effect to that.

只有 AI 生成的创意才抓得住注意力,因为它自带很强的新鲜感效应。

And we pay a lot of attention to that.

我们在这上面下了很大功夫。

So those use cases around people building content machines are very important for us when we for high-scale for high-scale video production.

所以那些把内容做成流水线的用例,对我们做大规模视频生产来说非常重要。

But also there is a strong adoption by creator economy with people like Madonna, Snoop Dogg, Will Smith using Higgsfield just to create an across their audience.

另外创作者经济这边采用度也很高,Madonna、Snoop Dogg、Will Smith 这些人都在用 Higgsfield 做内容、触达他们的受众。

Alex, I want to show my account in a minute if I give it to I'm going to show my account for fun if you don't mind.

Alex,等下我想给大家看看我的账号——如果你不介意的话,纯属好玩。

If it's helpful to you guys when I started using Higgsfield right after it launched, I did Higgsfield does a lot if you look at the top.

说给你们听可能有用:我是它一上线就开始用的。你看顶部这一栏,Higgsfield 能干的事很多。

Image, video, audio, Supercomputer, which we just demonstrated all of this.

图像、视频、音频、Supercomputer——刚才演示的就是这些。

I'm a basic guy, okay?

我是个很基础的用户,好吧?

But here's In the beginning it had it had a couple cool things, but this is a great use case for B2B if you see.

最开始它只有几个挺酷的功能,但你看,这对 B2B 来说是个很好的用例。

You go into it and it has start frame and end frame and you can update a photo from this event of like the stage and me and it will just connect them with different models and create a movie from it.

点进去有首帧和尾帧,你可以传一张这次活动的照片,比如舞台和我,它就用不同模型把两帧连起来,生成一段片子。

There's other ways today you can do it.

今天还有别的做法。

I'm going to ask Alex some questions, but it was just magical that I could take a picture of of the outside at SaaStr and this page and get a 6-second or 10-second video.

我等下会问 Alex 几个问题。但当时的感觉就是神奇:我拍一张 SaaStr 会场外的照片,加上这个页面,就能得到一条 6 秒或 10 秒的视频。

I'd never seen this before.

我以前从没见过这种东西。

And what I want to show you and I still make these videos.

我想给你们看的是——这些视频我到现在还在做。

Here's one for if you if we have this new podcast called The Agents.

这条是给我们那档新播客《The Agents》做的。

I just wanted to animate it with me and Amelia here.

我就是想把我和 Amelia 做成动画。

It seems very simple compared to what Alex saw, but I'll just This is my whole account of all the assets we've built.

跟 Alex 刚才演示的比起来很简单,但这是我账号里做过的所有素材。

Fun promos for this event.

这次活动的趣味宣传片。

This one.

这一条。

All different ones.

各种各样的。

I think it's pretty fun, right?

挺好玩的吧?

I'm not yet running an ad campaign.

我还没拿它去投广告。

It's pretty slick, right?

做得挺利落的,对吧?

And we can go back in time.

还能往回翻。

See if I can find any other ones.

看看还能翻到别的。

Welcome to the event, everyone.

欢迎各位来到本次活动。

We're so glad you're here.

很高兴见到你们。

What What model is this one?

这条是哪个模型做的?

Veo 3.1.

Veo 3.1。

I actually think Kling is like my favorite.

其实我最喜欢的是 Kling。

Here's all the collateral for the event.

这是这次活动的全套物料。

You might have seen this in our videos.

你们可能在我们视频里见过。

So like I wanted to make an intro.

我当时想做个片头。

I don't know if I picked it right.

不确定我选对了没有。

Make a little techy intro that just the event.

做一个有点科技感的片头,就为这次活动。

Sometimes there's artifacts, you rerun it.

有时会有瑕疵,重跑一次就行。

This is like to promote sponsorships.

这条是用来推赞助的。

We built this.

这是我们自己做的。

100% Vic, that's top of the list.

百分之百,Vic,这条排在最前面。

And five solid VCs, this could be our own.

还有五家靠谱的 VC,这单可以算我们自己的。

Let's line them up.

我们把他们排上。

Great to finally meet you both.

终于见到你们两位了。

Welcome board.

欢迎加入。

Couldn't be more excited.

再兴奋不过了。

Sora have the win.

这局归 Sora。

Get funding.

拿到融资。

Yeah, we have all these tools that you haven't used it.

我们还有一堆你们没用过的工具。

We have this Alex has used it to a startup evaluator that's used over a million times.

我们有个创业公司评估器,Alex 也用过,已经被用了超过一百万次。

All the promos.

所有宣传片。

I don't have time.

我没时间。

I don't have a team.

我也没团队。

I built them all here.

全是在这儿做出来的。

But when I think when it launched maybe used one model, right?

但我印象里它刚上线时只用一个模型,对吧?

Is that possible to use one model?

是只能用一个模型吗?

So we actually started with our own model.

我们其实是从自研模型起步的。

Your own model which was open source plus plus plus.

你们自己的模型,算是开源 plus plus plus。

Is that what it was?

是这样吗?

Yeah, open source plus plus plus, exactly.

对,开源 plus plus plus,没错。

So and then we realized very quickly that the number of models just increases.

然后我们很快发现,模型数量一直在涨。

Basically new model coming every week.

基本上每周都有新模型出来。

And it's very difficult to just follow everything what's happening in the space.

想跟上这个领域的所有动静非常难。

And this is actually an opportunity for one platform to consolidate all the models.

这其实给了一个平台把所有模型聚合起来的机会。

And let's say pick the best model based on each use case.

再按每个使用场景挑出最合适的模型。

Yeah.

嗯。

And so now it's much more powerful.

所以它现在强大多了。

You look at it now, you can pick from all the models.

你现在看,所有模型都能挑。

So you can make a video or an asset a short video.

你可以做一条视频、一个素材、一段短片。

And and what's to me in first of all, you're embracing in a sense your competition, right?

对我来说,首先,你们某种意义上是把竞争对手拥抱进来了,对吧?

In a sense.

某种意义上。

You have Google Veo here, right?

这里有 Google Veo,对吧?

You could use Sora before it got deprecated, I think, right?

Sora 下线之前也能用,是吧?

You you have your own model.

你们还有自研模型。

I think you've got Kling and Seedance and Wan, which you know what they are and I don't even know what they are.

还有 Kling、Seedance、Wan——你知道它们是什么,我压根不知道。

On the one hand the product is more complicated.

一方面,产品变复杂了。

On the other hand, I can run all of these things in seconds in parallel and use different models to see which is the better video for me, right?

另一方面,我能几秒之内并行跑完所有模型,看哪一条视频更适合我,对吧?

Yeah, it's super powerful.

确实非常强。

So talk about complexity and then talk about the business model and why it's not a thin wrapper.

那你讲讲这个复杂度,再讲讲商业模式——以及为什么它不是一层薄套壳。

This is a This is a great question.

这是个好问题。

And I think I think fundamentally there is a question for every business in the world if they are a thin wrapper or not.

我觉得从根本上说,今天世界上每一家公司都得面对「自己是不是薄套壳」这个问题。

Because I mean most of the software is going to rely on AI anyway, right?

因为大部分软件反正都要依赖 AI,对吧?

So, the way how we think is there are two major unlocks for us.

我们的想法是:我们有两个主要的解锁点。

So, first is to empower teams to create together.

第一,让团队能一起创作。

Like I think the collab like the network effect and collaboration is is very strong.

协作和网络效应的力量非常强。

That's what made Figma successful.

Figma 就是靠这个成的。

That's what That's what made Canva successful.

Canva 也是靠这个成的。

And we do believe there are many opportunities in the video space.

我们相信视频领域里也有很多这样的机会。

That's probably first.

这是第一点。

Second major unlock for Higgsfield is to help brands to sell more products.

Higgsfield 的第二个解锁点,是帮品牌卖出更多产品。

So, we launched our MCP 2 weeks ago.

我们两周前上线了自己的 MCP。

Today we launch our own agent called Supercomputer.

今天又发布了自己的 agent,叫 Supercomputer。

And that's really designed to make bulk of creatives to sell more.

它的设计目标就是批量产创意、卖出更多货。

Cuz we're all dealing with this, right?

因为我们都在面对这件事,对吧?

We all the LLMs are getting so good, right?

LLM 现在都这么强了。

We're all a wrapper at some level.

某种程度上,我们全都是套壳。

Thin, thick, left, right, on top of it, right?

薄的、厚的、左边的、右边的、架在上面的,对吧?

So, when I pay for Higgsfield, and for me, I know there's two different segments in the market.

那我付钱给 Higgsfield 的时候——我知道市场上有两类人。

I'm not I'm not counting every penny.

我不是那种一分一厘算账的人。

It's cheap.

它便宜。

To to me it's cheap, right?

对我来说很便宜,对吧?

But do you do you mark up the underlying models?

但你们会在底层模型上加价吗?

Is that a good deal for your customers?

这对客户划算吗?

How do you think about it?

你们怎么想这件事?

Cuz like sometimes I actually don't love Veo and Higgsfield, but Veo I could get in Gemini or I could pay for it directly, right?

因为有时候我其实不太喜欢在 Higgsfield 上用 Veo,而 Veo 我在 Gemini 里就能用,或者直接付费给它,对吧?

So, how do how do you think about the economics?

所以这笔账你们是怎么算的?

And all I It's just a mystery to me.

这对我来说完全是个谜。

Absolutely.

好的。

So, today 40% of usage is not associated with just picking the model, but they use workflows like cinema studio, marketing studio.

今天有 40% 的用量跟「选模型」无关,用户用的是 cinema studio、marketing studio 这类工作流。

So, that's a way higher level abstraction.

那是高得多的一层抽象。

That's probably first thing which is important to say.

这是第一点,很重要。

Second thing is we are still one of the most affordable platforms out there.

第二点,我们依然是市面上最便宜的平台之一。

So, for some of the models we are the most affordable.

有些模型上我们是最便宜的。

For some other models we could be top two, top three.

另一些模型上我们能排前二、前三。

But, I mean, we we are moving with a market there and increasingly trying to implement agentic workflows.

但这块我们是跟着市场走的,同时越来越多地去做 agentic 工作流。

That's where that's where we evolve from kind of per token costs to charging by outcome, by video.

这正是我们从按 token 计费,转向按成果、按视频计费的地方。

So, the model

所以这个模式——

If if you just do the seemingly basic stuff like I have, which is leverage the models more efficiently inside of Higgsfield, that's a lower margin product.

如果只做我这种看起来很基础的事——在 Higgsfield 里更高效地调用模型——那是个低毛利的生意。

Upsell is to use it for more cinematography and more value add workflows like you described.

往上卖,就是用它做更多影视级的东西,以及你说的那些更增值的工作流。

But, you can still make money on the basic workflow of marking up the model, right?

但光靠在模型上加价这种基础用法,你们也还是赚钱的,对吧?

Yeah, yeah.

对,对。

So, let me just throw like some numbers so that it makes sense.

我抛几个数字,这样好理解。

On average, customers on Higgsfield spend around $1,000 a year.

Higgsfield 的客户平均一年花大约 $1,000。

So, it is like, for example, Canva is $200 a year.

作为对比,Canva 是一年 $200。

And for us, we include every like every quarter, we almost pretty much double our ACV as we move substantially up the markets.

而我们几乎每个季度都把 ACV 翻一番,因为我们在明显往上游市场走。

As we want to attract more Jasons on on the platform.

我们想在平台上吸引更多像 Jason 这样的客户。

The reality is that social media like marketing budgets, I mean, many companies have like hundreds of thousands, millions, tens of millions of dollars.

现实是,很多公司的社交媒体营销预算是几十万、几百万、几千万美元。

So, when we think about experimentation from experimentation budgets from even $1 million, it's 10,000, right?

就算只从 100 万美元的实验预算里拿一点出来,也有 1 万美元,对吧?

And I think eventually, everyone would want to try video AI if that really yields positive ROI on social media.

我认为只要在社交媒体上真能跑出正 ROI,最终所有人都会想试试视频 AI。

And we want to make sure that these customers, they will they will be successful on the platform when they try.

而我们要保证:这些客户来试的时候,真能在平台上做成事。

And effectively, your job is to keep marching them up the value stack.

说白了,你们的活儿就是不断把客户往价值链上游赶。

But, on average, folks are paying you five times more than Canva.

但平均下来,大家付给你们的是 Canva 的五倍。

Now, people are going to start paying more for Canva as Canva gets more agentic with 2.0.

当然,Canva 2.0 变得更 agentic 之后,大家给 Canva 的钱也会涨。

But, it is a reminder for the theme of this week.

但这正好呼应了本周的主题。

If you build I mean listen, I made these videos in seconds on Higgsfield, right?

你们看,我在 Higgsfield 上几秒钟就做出了这些视频。

And and I probably pay more than for Can- I've been a Canva customer since the 1970s or something like that.

我付给它的钱大概比 Canva 多——我从上古时代就是 Canva 的客户了。

I mean I don't know.

具体记不清了。

I pay 18 bucks a month.

我一个月付 18 块。

I'm sure I pay Higgsfield more than 18 bucks a month and I don't care.

我给 Higgsfield 的肯定不止 18 块,但我不在乎。

But if you provide that agentic value, but the value I get out of Higgsfield, even though I love Canva, is higher.

因为只要你提供了那种 agentic 的价值——尽管我很喜欢 Canva,我从 Higgsfield 拿到的价值还是更高。

I can build a whole like What would it cost for me to build a video like without skills and people?

我能做出一整套……让我自己做一条视频要花多少钱?没手艺、没人手的话。

I mean, infinity.

无穷大。

I'd have to hire an agency.

我得去请一家代理商。

It would come back 2 weeks later.

两周之后东西才交回来。

It would be terrible.

做得还很烂。

They would charge me thousands of dollars and I would delete times the ACV of Canva, but even though by having an agentic workflow that that replaces humans.

他们收我几千美元,我看完就删——所以他能拿到 Canva 几倍的 ACV,靠的是一套替代人力的 agentic 工作流。

And honestly, for me, it replaces contractor and agency that I don't have the patience to hire anyway, right?

说实话,对我来说,它替掉的是我本来就没耐心去找的外包和代理商。

Rather than just be helping me create an asset manually.

而不只是帮我手工做一个素材。

This is a good point.

这个点说得好。

So, there are several things which I want to say is that we're seeing that increasingly companies bring the capabilities in house.

我想说几件事。我们看到越来越多公司把这项能力收回内部。

As you are right, that like back and forth with agency is just very frustrating.

你说得对,跟代理商来回拉扯实在太让人受不了。

And that's is both budget-wise and timeline.

预算上和时间上都是。

And other huge issue is that it's very difficult to go vice versa, go back and say, "Oh, I wanted the actor in this ad to look differently." It's just impossible with physical production.

另一个大问题是很难反悔:你没法回头说「我想让这支广告里的演员换个长相」——实拍制作根本做不到。

But like very often, what we're seeing on the platform, customers create variations of the same ad, but just with difference with different actors.

而在我们平台上经常看到的是,客户为同一支广告做出多个版本,只是换不同的演员。

So, essentially, what happens is the Essentially, what we're seeing here is content that's like one social media marketer can make several minutes of commercially viable videos, social media videos a day.

本质上我们看到的是:一个社交媒体营销人员一天就能产出好几分钟商业可用的社媒视频。

And cost-wise, there is also a massive drop in the cost of production.

成本这边,制作成本也大幅下降。

For sure.

当然。

He says, let me ask you one or two questions and then and then we can break.

我再问一两个问题,然后我们就休息。

Agencies, it's it's a meta question for a lot of folks.

代理商这件事,对很多人来说是个更上层的问题。

Do you enable them?

你们是在赋能他们吗?

Do you have the Higgsfield offering for agencies?

你们有面向代理商的 Higgsfield 方案吗?

Because you're disrupting to agencies, but also if if I if I have budget for agency and they can give me 10 times more assets at faster, it enables agencies, too.

因为你们在颠覆代理商;但反过来,如果我有代理商预算,而他们能更快给我十倍的素材,那你们也是在赋能代理商。

So, how do you What's your interaction with with creative agencies?

所以你们跟创意代理商之间是什么关系?

So, this is this is a good question.

这是个好问题。

So, first part, which is creative agencies, is this is the number one customer on the platform.

第一块,创意代理商——他们是平台上的头号客户。

We love to bring up examples of brands building

我们很喜欢举那些品牌自己做内容的例子——

Number one customer are agencies.

头号客户是代理商。

Agencies, for sure.

是代理商,没错。

Creative agencies is number one.

创意代理商排第一。

We are excited to see more and more direct-to-consumer companies kind of using Higgsfield directly.

我们也很高兴看到越来越多 DTC 公司直接用 Higgsfield。

But, this is still an emerging trends.

但这还只是个刚冒头的趋势。

Like, if we just talk specifically about 300 million ARR, most of that's like almost 70% are agencies.

具体到这 3 亿 ARR,其中大部分——差不多 70%——来自代理商。

Oh, I wouldn't have guessed that.

这我可猜不到。

I would have guessed early I mean, I would have guessed you were getting there, but your early adopters were web heads and AI nerds and people like that.

我本来以为你们最终会做到这一步,但早期用户应该是网络极客、AI 发烧友这类人。

But, it's actually agencies found you early because it made them radically more efficient.

结果其实是代理商很早就找到了你们,因为它让他们的效率发生了质变。

Because I think all agencies a lot of especially creative agencies, yeah, they have been mostly struggling, frankly, and they use AI as a new opportunity to sell.

因为坦白说,大多数代理商——尤其是创意代理商——这几年一直不好过,他们把 AI 当成一个新的销售机会。

Mhm.

嗯。

To sell.

拿来卖。

And I think that's There is definitely a lot of demands.

需求确实很旺。

We have seen Super Bowl ads generated with with AI.

我们见过用 AI 生成的超级碗广告。

We have seen many Olympic ads, Christmas ads, like Coca-Cola Christmas ad was generated on Higgsfield.

也见过很多奥运广告、圣诞广告,比如可口可乐的圣诞广告就是在 Higgsfield 上生成的。

So, I think there is there is just a lot going on.

这个领域里正在发生的事很多。

And there is clearly there is clearly a lot of demand for innovation. and also all these companies they have experimental budgets like millions of dollars.

对创新的需求显然非常大;而且这些公司都有几百万美元级别的实验预算。

So it's natural that they are all signing AI.

所以他们全都签 AI,是很自然的事。

And I'm just a solo user so I don't see it.

我只是个单人用户,所以看不到这一层。

When agencies use you and I think how good are market channels change in AI is interesting.

代理商用你们的时候……我觉得 AI 时代渠道怎么变,是个有意思的话题。

When agencies because you're also disrupting some agencies or enabling agencies that use Higgsfield 70 you know 200 million of revenue but you're disrupting agencies that used to charge $10,000 for something that you can do in minutes.

你们既在颠覆一部分代理商,也在赋能那些用 Higgsfield 的代理商——七成、也就是两亿的收入;但你们同时也在颠覆那些过去为一件事收一万美元、而你们几分钟就能做完的代理商。

Do they hide it from their clients?

他们会瞒着客户吗?

Do they white label Higgsfield?

他们会把 Higgsfield 做成白牌吗?

Are they worried their clients will see it's on Higgsfield and feel like they're being overcharged?

他们会不会担心客户发现东西是在 Higgsfield 上做的,觉得自己被宰了?

This is a This is a good point.

这个点问得好。

So this is the second part of the markets which are larger agencies.

这属于市场的第二块,也就是大型代理商。

Larger agencies they make money from kind of media consulting.

大型代理商赚的是媒介咨询的钱。

That's kind of first kind of McKinsey but for for marketing, right?

有点像营销界的麦肯锡,对吧?

And the second part is a paid is paid marketing.

第二块是付费营销。

Like basically media buying.

也就是媒介投放。

So So his Video AI and Higgsfield did not change the way how media is bought.

视频 AI 和 Higgsfield 并没有改变媒介是怎么买的。

This hasn't happened yet.

这件事还没发生。

But with our Supercomputer products we have direct integration to Meta MCP and some other MCPs as well.

但我们的 Supercomputer 产品已经直接对接了 Meta 的 MCP,还有其他一些 MCP。

So that we can play broader role.

这样我们能扮演更大的角色。

Not just from ideation to creation collaboration but also we want to add distribution piece.

不只是从创意构思到制作协作,我们还想补上分发这一环。

Basically distribute ads across different ad networks.

也就是把广告投到不同的广告网络上。

Got it.

明白。

And and inform clients what works the best.

并且告诉客户哪一套效果最好。

Cool.

好。

For just cuz I haven't really chatted with many founders about it.

因为这事我没跟太多创始人聊过。

For these agencies that 70% of your model.

这些代理商占了你们模式的七成。

I know your team is only 120 people at 300 million revenue is that what you said?

你们团队 120 人做 3 亿收入,是你刚说的吧?

Do you have a dedicated partner team, enablement team, people that are making these agencies that maybe aren't at the cutting edge successful with these tools?

你们有专门的合作伙伴团队、赋能团队吗?——去帮那些还没站在最前沿的代理商把这些工具用起来。

Yeah, we are very very actively building uh for the client engineering team.

有,我们正在很积极地建客户工程团队。

Your clients

你们的客户——

Your your own team you have that, yeah.

是你们自己的团队,明白。

absolutely.

没错。

I think what we're seeing is that the demands like there is a lot of interest in customization and higher volume content creation.

我们看到的需求是:大家对定制化和更大批量的内容生产很感兴趣。

We have seen I know like I think out of top 50 media organizations in the world, at least 10 building internal tooling.

全球前 50 的媒体机构里,我知道至少有 10 家在自建内部工具。

Cuz they feel that everything available out there is not good yet.

因为他们觉得市面上现有的东西还不够好。

But to me it feels like this is actually a signal to us that we should make our products more customizable and like our and like we really double down on enterprise adoption.

但在我看来,这其实是给我们的信号:我们该把产品做得更可定制,并且在企业级市场上加大投入。

Okay.

好。

And maybe one last kind of a question.

可能还有最后一个问题。

I really believe you guys are doing six releases a week because the product has changed so much since I've used it, right?

我真的相信你们一周发六次版,因为从我开始用到现在,产品变化太大了。

Some of the stuff you did in the beginning didn't work out that well, right?

早期做的一些东西效果并不好,对吧?

Or you deprecated or stopped investing in it.

或者你们把它下线了、不再投入了。

What sort of I mean maybe it's just usage and miles and miles and miles, but how do you decide quickly what to abandon, what to put to the side, what to hide in the nav, where to go deep because this product radically evolves?

也许答案就是用量、就是一遍遍跑出来的经验。但你们怎么快速判断:什么砍掉、什么先放一边、什么藏进导航深处、什么要往深里做?毕竟这个产品在剧烈演进。

You haven't just I mean missing part of story right it's not like you went from zero to 300 million with the exact same product.

故事里缺了一块——你们不可能是拿同一个产品从零做到 3 亿的。

So this is absolutely true.

确实如此。

I still kind of I'm in the past using maybe Higgsfield 2.0, but 95% of folks use a radically different product than when I started.

我大概还停留在 Higgsfield 2.0 的用法上,但 95% 的人用的产品,跟我刚开始时已经完全不同了。

So how how do you how do you pick that look at the data to decide what to do, decide what to cut?

那你们怎么看数据、怎么决定做什么、砍什么?

Absolutely.

好的。

So we really saw maybe March last year that there is an interest from top creative directors to use AI, but camera control does not exist.

大概去年三月我们看到:顶级创意总监对用 AI 是有兴趣的,但当时根本没有镜头控制。

So they just immediately rejected.

所以他们直接就否掉了。

So that was our first innovation.

这就是我们的第一个创新。

Then we I can we kind of went to our roots.

然后我们算是回到了自己的老本行。

So I sold my previous company to Snap where we built the face filters basically and face filters is just kind of one click So, we did that did the same for visual effects.

我上一家公司卖给了 Snap,在那儿我们做的基本就是人脸滤镜——人脸滤镜就是一键的事。我们把同样的思路用到了视觉特效上。

And this helped us to get to 10 million ARR within eight weeks or so.

这让我们在八周左右做到了 1000 万 ARR。

Then, the interesting part for us was to also I mean, we noticed maybe in July that some people start to make commercial projects end-to-end with AI.

接下来有意思的是,大概七月我们注意到,有人开始用 AI 端到端地做商业项目。

And and this is and this is where like kind of AI video AI is is no longer a toy.

从那一刻起,视频 AI 就不再是个玩具了。

It's not just a tool kind of for some fun effects, kind of face masks, or whatever.

它不只是拿来做好玩的特效、人脸面具之类的工具。

It It actually brings a lot of commercial value.

它真的能带来很大的商业价值。

And we reoriented the whole company around that.

于是我们围绕这件事把整家公司转了个向。

And now we reoriented the whole company again around agentic.

而现在,我们又围绕 agentic 把整家公司转了一次向。

Cuz as as we as I mentioned like agentic workflow is like it like marketing workflow is extremely repetitive.

因为像我刚才说的,营销工作流是极度重复的。

Every day, it's important to understand the trends, which are relevant, which are irrelevant.

每天都要判断哪些趋势相关、哪些不相关。

What's worked well yesterday?

昨天什么跑得好?

Then, decide if which videos we need to make today.

然后决定今天要做哪些视频。

How it's different across different channels?

不同渠道之间有什么差别?

What's the difference?

差在哪里?

What's the audience like overall sentiments?

受众的整体情绪如何?

And then, make the videos, post, and rinse and repeat every day.

然后做视频、发出去,每天循环往复。

To And that's very important to stay relevant on social media.

这对在社交媒体上保持存在感非常重要。

So, and I think the kind of agentic actually I mean like our agentic workflows is our first step to cover the whole marketing workflow end-to-end.

我们的 agentic 工作流,是我们端到端覆盖整个营销流程的第一步。

That's amazing.

太厉害了。

One last round question, just at a high level for founders over there.

最后一个大问题,讲给在座的创始人听。

Cuz this is a this is I think an over-discussed topic.

因为我觉得这个话题已经被讨论得过头了。

But, what is ARR?

但——ARR 到底是什么?

This is

这个——

300 million ARR.

3 亿 ARR。

But, this isn't all sales for subscriptions at $150 a month per seat.

但这不可能全是每席位每月 150 美元的订阅销售额。

How do you define it?

你们怎么定义它?

What does it mean?

它到底意味着什么?

I think you're pretty honest and direct on this.

我觉得你在这件事上挺坦率、挺直接的。

So, just just give us a snapshot on what you think ARR today is in an AI and agentic world.

那就给我们讲讲:在 AI 和 agentic 的世界里,你认为今天的 ARR 该怎么算?

Absolutely.

好的。

So, I think there are There are There are There are two subcomponents.

我认为它有两个组成部分。

First, I think it's important to take annual subscription and divide by 12.

第一,年费订阅要除以 12,这一点很重要。

And wherever you how you measure ARR, it's just very important to do and kind of be intellectually honest.

不管你怎么衡量 ARR,关键是要做到智识上的诚实。

And I think a lot of kind of, you know, like kind of wishy-washy stuff starts with credits.

我觉得很多含糊其辞的地方,都是从 credits 开始的。

Cuz if someone uses on demands, then there is a question of like where it all gets attributed.

因为如果有人是按需消费,那这笔钱该归到哪儿就成了问题。

Right?

对吧?

So, like for us, we Like for us for 300 million, we see the on-demand usage for specific lasts 4 weeks.

我们这 3 亿是这么来的:按需用量取最近四周的数据。

We see we take the monthly subscription revenue, annual subscription revenue divided by 12, sum it up all together, multiplied by 12, and that's how we get the result.

再取月订阅收入,加上年订阅收入除以 12,全部加总,然后乘以 12,得出的就是这个结果。

I think on-demand usage is the most tricky one.

我觉得按需用量是最难处理的一块。

Yeah, but you're using But you're still using the last 30 days of revenue in essence and multiplying it by 12, right?

但本质上你还是用最近 30 天的收入乘以 12,对吧?

So,

那个——

But it's revenue.

但那是 revenue。

It's not just sales.

不只是销售额。

It's revenue.

是收入。

What's importance?

重点是什么?

Booked revenue.

已确认收入?

GAAP revenue or

还是 GAAP 收入?

Yeah, yeah, revenue.

对对,是收入。

Meaning that we take we take like annual subscriptions or annual contracts and divide by 12.

意思是我们把年度订阅或年度合同除以 12。

Sure.

好。

Which is importance cuz some companies they take whatever like cash they got and multiply it by 12.

这很重要,因为有些公司是拿到手的现金直接乘以 12。

This is I think

我觉得这——

Well, that's That's But But okay, and but at 300 million, how much is on annual versus monthly versus yearly?

那……好吧,那在这 3 亿里,年付和月付各占多少?

I mean, do you have a lot on annual?

年付的比例高吗?

A lot of annual is a very substantial.

年付的量相当可观。

I mean, like look, in terms of the number of subscription, it's it's not high, but I mean, it's it's definitely like 40 40% of total of total revenue for sure.

从订阅数量上看不算高,但从总收入看,年付肯定占到 40% 左右。

I think some folks are stretching the definition of ARR so far it stretches credibility.

我觉得有些人把 ARR 的定义拉得太长,长到失去了可信度。

But also I I I also think sometimes people take this issue too seriously.

但另一方面,我也觉得有时候大家把这事看得太重了。

If you're doing 300 What's 300 million divided by 12?

如果你做到 3 亿……3 亿除以 12 是多少?

I'm getting tired.

我脑子转不动了。

25, 26 million or something like that, right?

两千五、两千六百万左右,对吧?

If this month you're roughly doing 26 million, honestly, then you're have a 300 million uh revenue rate, right?

说实话,如果你这个月大概收了 2600 万,那你的收入年化就是 3 亿,对吧?

It's It shouldn't We're making this too complex.

我们把这事搞得太复杂了。

Whether it's credits I think if you're giving marked 80% marketing discounts at zero and claiming it's revenue, it's pretty suspect, If it's cash in the door or cash properly recognized for accounting, I I think we're What am I missing, Alex?

不管是不是 credits——如果你打八折甚至白送出去还算成收入,那就很可疑了。但只要是真金白银进账、或者按会计准则正确确认的收入……Alex,我是不是漏了什么?

I think we're overcomplicating this.

我觉得我们把这事想复杂了。

Like that should be your ARR, you know, close enough to what your real revenue is, whether it's one off, 10 off, 20 off, annual, weekly.

那就该是你的 ARR,跟你真实收入足够接近就行,不管它是一次性的、十次的、二十次的、年付的还是周付的。

I I At some level, I don't care.

某种程度上我并不在乎。

What is your rev Just show me the money, right?

你的收入是多少?把钱亮出来就行了,对吧?

Yeah, absolutely.

完全同意。

So for us, I think what's And they also spoke a lot about that with Stripe team, frankly.

说实话,我们也跟 Stripe 团队聊过很多这个话题。

A lot of businesses are run on Stripe.

很多生意都跑在 Stripe 上。

Stripe also has their registration across the various payment systems.

Stripe 在各种支付系统里也都有记录。

And I think I mean, at the end of the day, I think very soon we will be sharing Stripe dashboards.

说到底,我觉得很快我们就会直接公开 Stripe 的后台数据。

Cuz, you know, like it's just kind of this Otherwise, there is just a lot of discrepancy in definition.

否则光是定义上的分歧就太多了。

Stripe says 25 million this month.

Stripe 说这个月 2500 万。

I call it 300 million

我就叫它 3 亿。

Yeah, we call it the same.

对,我们也是这么算的。

for me, right?

对我来说就是这样。

All right, incredible success story.

好了,一个了不起的成功故事。

Let's give it up for Alex and thanks.

我们把掌声送给 Alex,谢谢。

We One one we can be proud of.

这是一个我们可以引以为傲的故事。

Thanks for doing this.

谢谢你来。

Thank you.

谢谢。

Thank you for having me.

谢谢邀请。

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