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B2B 软件增长分化:仅 7 家超 30%,Figma 的 AI

Only 7 Public B2B Companies Are Growing Over 30%. In the AI-Native Cohort, That Would Be Last Place

原文
推荐理由

给 B2B 创始人和增长负责人:用真实数据说明增长与估值的关系,并拆解 Figma 的 AI 附加层模式——不替换席位而是拉动席位,是多数公司可复制的机制。

Seven public B2B software companies are growing faster than 30%. Here they are, most recently reported quarter, straight from the earnings releases.

七家上市B2B软件公司增长率超过30%。以下是它们最近一个季度的数据,直接来自财报发布。

Annualized is that quarter’s revenue times four. It’s a rough figure, and for companies with seasonality it will be off by a few points, but it puts everything on the same footing as the run-rate numbers later in this post.

年化数据是该季度收入乘以四。这是一个粗略数字,对于有季节性的公司会偏差几个百分点,但它使所有数据与本文后面的运行率数字处于同一基准。

That’s the list. Not the top of the list. The list.

这就是名单。不是名单的顶端。就是名单本身。

What This Number Used to Be

这个数字曾经是什么

The SaaS Capital Index median growth rate peaked above 30% in 2021. Above. Half the index cleared what seven companies clear today.

SaaS Capital Index的中位增长率在2021年曾超过30%。超过。指数中一半公司超过了今天七家公司所达到的水平。

In five years, the median became the 90th percentile.

五年间,中位数变成了第90百分位。

That’s the whole story of this market. If you’re the CEO of a $200M ARR B2B company growing 18%, you are not underperforming your peers. You are your peers. The peer set moved, and it moved fast.

这就是这个市场的全部故事。如果你是一家年经常性收入2亿美元、增长18%的B2B公司CEO,你并没有落后于同行。你就是同行。同行群体已经移动了,而且移动得很快。

An independent read of the SaaS Capital Index data file for June 30, 2026 found the same shape across the 58 constituents reporting both growth and a multiple: 18 companies growing under 10%, 23 at 10% to 20%, 11 at 20% to 30%, and only 6 above 30%. Different universe than ours, nearly identical answer.

对SaaS Capital Index截至2026年6月30日数据文件的独立分析发现,在58家同时报告增长率和倍数的成分公司中呈现相同形态:18家公司增长低于10%,23家处于10%至20%,11家处于20%至30%,仅6家超过30%。与我们不同的样本范围,答案几乎相同。

The Cluster Right Below the Line

线下的密集集群

The more interesting finding is who missed, and by how little.

更有趣的发现是谁错过了,以及差了多少。

Put the two tables side by side and one thing jumps out: scale is not what separates them. Atlassian is the second-largest company on either list at roughly $7 billion annualized, and it missed the line by two points. Samsara made the list at $1.9 billion. Snowflake cleared it at $5.6 billion while CrowdStrike missed at $5.5 billion.

把两张表放在一起,有一件事很突出:规模并不是区分它们的因素。Atlassian是两份名单中第二大的公司,年化收入约70亿美元,却差了2个百分点。Samsara以19亿美元入选。Snowflake以56亿美元达标,而CrowdStrike以55亿美元错过。

These are not struggling companies. Several are among the best-run businesses in software. They are also all sitting in a band that earns a 5.5x median revenue multiple, while the sub-10% band earns 1.9x and the 10% to 20% band earns 3.1x.

这些并不是挣扎中的公司。其中几家是软件行业管理最好的企业。但它们都处于一个收入倍数中位数为5.5倍的区间,而低于10%增长区间为1.9倍,10%至20%区间为3.1倍。

So there is a dense, high-quality cluster of companies four to seven points below a line that separates one valuation regime from another. That’s the actual competitive situation in B2B right now. A handful of points of growth is worth more than it has been in a decade.

因此,在一个分隔两种估值体系的线下方4到7个百分点处,存在一个密集且高质量的集群。这就是当前B2B的实际竞争状况。几个百分点的增长比过去十年任何时候都更有价值。

What the Seven Have in Common

这七家公司的共同点

Four of the seven do not primarily charge by the seat.

七家中有四家并非主要按席位收费。

Palantir, Datadog, Cloudflare, and Snowflake all bill against usage in some form. When a customer runs more AI workloads, their bill goes up automatically. Nobody has to negotiate a seat expansion. Nobody has to convince a CFO that the team grew. The AI boom flows through the pricing model without a sales cycle.

Palantir、Datadog、Cloudflare和Snowflake都以某种形式按使用量计费。当客户运行更多AI工作负载时,他们的账单会自动增加。没有人需要谈判增加席位。没有人需要说服CFO团队扩大了。AI热潮无需销售周期就能通过定价模式传导。

Cloudflare’s CEO framed the quarter around exactly this: the shift to AI answer engines and agent-driven commerce as a rewrite of the internet for machine-to-machine traffic. That’s a company whose revenue goes up when machines do more work. Datadog said the same thing in different words, that customers are building and deploying with AI and using the platform to observe and secure it. Snowflake sits under the data those agents read.

Cloudflare的首席执行官正是围绕这一点来定义本季度的:向AI答案引擎和代理驱动型商务的转变,是对互联网进行重写,以适应机器对机器的流量。这是一家当机器做更多工作时收入就会增长的公司。Datadog用不同的措辞表达了同样的意思,即客户正在使用AI进行构建和部署,并利用该平台进行观察和安全保障。Snowflake则位于这些代理所读取的数据之下。

Rubrik and Samsara are the two that don’t fit the consumption pattern cleanly. Both sell into a specific structural shift instead: Rubrik into data security and recovery for AI deployments, Samsara into digitizing physical operations. Different mechanism, same principle, which is that the thing driving spend isn’t headcount.

Rubrik和Samsara是两家不完全符合消费模式的公司。它们各自针对特定的结构性转变进行销售:Rubrik针对AI部署的数据安全与恢复,Samsara针对物理运营的数字化。机制不同,但原则相同,即驱动支出的不是员工人数。

Figma Is the One Worth Studying

Figma是值得研究的对象

Figma is the exception on this list, and it’s the most useful company on it for anyone reading this.

Figma是这份名单上的例外,对于任何阅读本文的人来说,它是其中最有用的公司。

Figma sells seats. It is the most seat-dependent business among the seven. Its revenue grew 48% in the quarter ended June 30, its third consecutive quarter of accelerating growth, with net dollar retention at 136%.

Figma按席位销售。在七家公司中,它是最依赖席位的业务。截至6月30日的季度,其收入增长了48%,这是连续第三个季度增长加速,净美元留存率为136%。

The mechanism is that it added a consumption layer on top of seats rather than replacing them. Q2 was the first full quarter of AI credit monetization. Customers expanded on both dimensions, seats and AI credit add-ons. The CFO noted roughly two-thirds of customers above $10,000 in ARR added full seats at renewal. One large technology customer added more than 25,000 paid seats through an AI credit add-on.

其机制是在席位之上增加了一层消费层,而不是取代席位。第二季度是AI积分货币化的首个完整季度。客户在席位和AI积分附加组件两个维度上都进行了扩展。首席财务官指出,在ARR超过1万美元的客户中,约有三分之二在续约时增加了完整席位。一家大型科技客户通过AI积分附加组件增加了超过2.5万个付费席位。

The AI product didn’t cannibalize the seat count. It pulled seats along with it. That’s the mechanism most B2B companies can actually copy.

AI产品并未蚕食席位数量,反而带动了席位的增长。这是大多数B2B公司实际上可以复制的机制。

It isn’t free. Gross margin fell five points year over year, and management was direct about why: they don’t charge for products in beta, so they carry the inference cost with no offsetting consumption revenue. Q3 guidance implies 36% growth, a step down from 48%, partly on tougher comparisons.

这并非没有代价。毛利率同比下降了5个百分点,管理层对此直言不讳:他们不对测试版产品收费,因此承担了推理成本,却没有相应的消费收入来抵消。第三季度的指引暗示增长率为36%,较48%有所下降,部分原因是比较基数较高。

That’s what the transition looks like from inside. Accelerating top line, compressing gross margin, and an honest acknowledgment that the comps get harder. It is not clean. It’s still the clearest playbook on this list.

这就是从内部看到的转型景象:营收加速增长,毛利率压缩,并坦诚承认比较基数变得更加困难。这并不完美,但仍是这份名单上最清晰的策略。

Now Put a Second Generation Next to It

现在,将第二代公司与之并列

Everything above is one generation of companies. Here is the other one.

以上所有内容都是第一代公司。这里是另一代。

Anthropic’s run rate went up sevenfold in a year. Its Q2 revenue exceeded $11.5 billion against $787 million in the same quarter a year earlier. That is more than fourteen times, at multibillion-dollar scale, with positive adjusted operating income in the quarter.

Anthropic 的年化运行率在一年内增长了七倍。其第二季度营收超过115亿美元,而去年同期为7.87亿美元。这相当于增长了十四倍以上,达到数十亿美元的规模,且该季度调整后营业收入为正。

Higgsfield is the one worth staring at. The platform did not exist before March 2025. It crossed a $500M annualized run rate in June 2026 and $700M by August, when it raised $400M at a $5.4B valuation. It was cash-flow positive on the way through, with 390 of the Fortune 500 as customers.

Higgsfield 是最值得关注的。该平台在2025年3月之前并不存在。它在2026年6月年化运行率突破5亿美元,到8月达到7亿美元,当时以54亿美元的估值融资4亿美元。在此过程中,它实现了正现金流,并有390家财富500强企业作为客户。

Harvey matters for a different reason: it sells seats. Per-lawyer licenses to law firms, the most traditional B2B motion on this page. It roughly doubled ARR in seven months. Whatever is happening here, it isn’t only a pricing-model story.

Harvey 之所以重要,原因不同:它销售席位。向律师事务所按律师许可收费,这是本页最传统的B2B模式。其ARR在七个月内大约翻了一番。无论这里发生了什么,这不仅仅是定价模式的故事。

The slowest company in this group grew faster over seven months than all but one of the seven public companies grew over twelve.

这个群体中增长最慢的公司,在七个月内的增长速度超过了七家上市公司中除一家外所有公司在十二个月内的增长速度。

Databricks and Stripe: The Almost-Public Comps

Databricks 和 Stripe:近乎上市的对标公司

The objection to the list above is that those are small companies compounding off small bases. Fine. Look at the two that are neither small nor public.

对上述列表的反对意见是,这些公司规模小,基数小,复合增长容易。好吧。看看那些既不小也不上市的两家公司。

Databricks hit $6.9 billion in annualized revenue in June 2026, growing over 80% year over year, up from $5.4 billion in its fiscal Q4. It then crossed $7 billion and raised $5 billion at a $190 billion valuation. AI products alone account for roughly $1.7 billion of annual revenue.

Databricks 在2026年6月年化收入达到69亿美元,同比增长超过80%,高于其2026财年第四季度的54亿美元。随后,它突破了70亿美元,并以1900亿美元的估值融资50亿美元。仅AI产品就约占年收入的17亿美元。

At roughly $7 billion, Databricks is bigger than every public company above except Palantir and Atlassian, and it is growing faster than all of them. It is Atlassian’s size, growing at three times Atlassian’s rate.

Databricks 以约70亿美元的规模,比上述所有上市公司都大,除了 Palantir 和 Atlassian,而且它的增长速度比它们都快。它的规模与 Atlassian 相当,但增长速度是 Atlassian 的三倍。

CEO Ali Ghodsi was direct about the mechanism, and it’s the same one running underneath four of our seven. Consumption plus agentic AI. The agents generate far more queries, the agent platform itself generates revenue, and the result is more consumption of everything. He also volunteered that gross margin is going lower, because those queries cost money to serve.

CEO Ali Ghodsi 直接说明了机制,这与我们七家公司中四家背后的机制相同。消费加代理型AI。代理产生更多的查询,代理平台本身产生收入,结果是所有方面的消费增加。他还主动提到毛利率正在下降,因为服务这些查询需要成本。

Stripe is the counterweight, and the more instructive one for most readers. Revenue reached $6.8 billion in 2025, up 33%, its fastest growth since 2021 at a revenue base more than four times its 2021 size. Free cash flow rose 52% to $3.2 billion. Total payment volume hit $1.9 trillion, up 34%. Q1 2026 alone did $2 billion in revenue. The February 2026 tender valued it at $159 billion.

Stripe 是平衡力量,对大多数读者来说更具启发性。2025年收入达到68亿美元,增长33%,这是自2021年以来最快的增长,而其收入基数是2021年的四倍多。自由现金流增长52%,达到32亿美元。总支付额达到1.9万亿美元,增长34%。仅2026年第一季度就实现了20亿美元的收入。2026年2月的要约收购将其估值定为1590亿美元。

Stripe is not an AI-native company. It’s fifteen years old, and it grew 33% by sitting underneath the companies that are. It processes payments for the AI labs and for the long tail of Replit, Lovable, Vercel, Cursor, and Midjourney. It’s taxing the boom rather than competing in it.

Stripe 并非一家原生AI公司。它已有十五年历史,其33%的增长来自于支撑那些原生AI公司。它为AI实验室以及Replit、Lovable、Vercel、Cursor和Midjourney等长尾公司处理支付。它是在为繁荣征税,而非参与竞争。

You don’t have to be an AI-native company or rebuild into one. You can be the thing they all have to buy.

你不必成为一家原生AI公司,也不必转型为这样的公司。你可以成为他们所有人都必须购买的东西。

Two Clouds, and a Gap Where the Middle Used to Be

两朵云,以及中间曾经存在的空隙

Plot both generations on one chart, revenue against growth, and the picture is not a spectrum. It’s two clouds.

将两代公司绘制在同一张图表上,以收入对增长,画面并非一个光谱,而是两朵云。

更进一步:量化金融体系

看懂新闻只是起点——沿量化金融路径,把它变成能交付的工程能力

进入量化体系 →

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