Some are longstanding blue chip tech and pharmaceutical companies. Others are fast-growing venture-backed unicorns. And still others are more recent public market entrants looking to stay competitive in the age of AI.

To get a sense of who鈥檚 buying in bulk, we used SA国际传媒 data to put together a that acquired three or more seed- or venture-backed startups in the past three years. From there, we picked the most acquisitive names.

The most prolific startup acquirers of the past 3 years

Per SA国际传媒 data, the most prolific acquirers of seed- and venture-backed startups in recent years are 1, and . Overall, our query showed six companies with six or more known purchases, charted below.

For top-ranked Salesforce, high-volume M&A is nothing new. The San Francisco software giant has purchased at least 91 companies in the past 20 years, per SA国际传媒 data. Its most recent startup purchases include , a revenue orchestration platform, and , which focuses on agentic AI for e-commerce.

OpenAI, by contrast, has a shorter track record of M&A shopping sprees. The pioneering generative AI company has bought 16 companies in the past three years. Among the most recent was an deal involving open-source AI agent and its creator, . This month, it also snapped up , a creator of open source tools for software developers, and , an open-source tool for testing AI applications.

Snowflake, meanwhile, has 19 acquisitions to date. Most recently, it acquired , a developer of AI observability tools that previously raised more than $460 million in venture funding.

Notably, recent the active acquirers list for recent years looks quite a bit different that the ranking of all-time top M&A dealmakers in the SA国际传媒 dataset, shown below:

Highest-spending acquirers

The most prolific startup buyers also aren鈥檛 always the biggest check-writers. By the latter metric, the far-and-away leader is , and its $32 billion acquisition of .

For a broader picture view, we used SA国际传媒 data to put together a list of six companies that made the biggest-ticket funded startup acquisitions of the past three years.

2026 off to a promising start

So far this year, it looks like the pace of startup M&A dealmaking remains fairly robust.

This includes two deals in the multiple billions: 鈥檚 $5.15 billion purchase of and s $2.4 billion acquisition of . The AI sector鈥檚 appetite for acqui-hires and smaller purchases of earlier-stage startups also continues to boost momentum.

We鈥檒l see if it keeps up.

Related SA国际传媒 list:

Related reading:

• Small And Mid-Sized Startup Purchases Are Still Well Below The 2021 Peak
• SA国际传媒 Predicts: Why The Race For Talent And Tech Could Accelerate Startup M&A In 2026
• M&A The Highest On Record For Unicorn Exits In 2025

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A total of 27 companies joined the Unicorn Board last month, including six robotics companies and four semiconductor-related startups. Healthcare minted three new unicorns, while foundation AI, cloud services, aerospace and financial services each accounted for two companies that joined.

The U.S. once again dominated, with 19 companies joining the board. China tallied four new unicorns, the U.K. contributed two, and India and Germany each added one new unicorn.

Soaring valuations

Overall unicorn values soared in February as raised $110 billion at a value of $840 billion, making it the most highly valued private company of all time. Its closest rival, , raised $30 billion at a valuation of $380 billion, making it the fourth-largest valued company on the list. , the autonomous driving technology company, was valued at $126 billion, positioning it among the top 10 most highly valued private companies.

February鈥檚 new unicorns

Here are February鈥檚 newly minted unicorns.

Robotics

• , a solution for automating building equipment for autonomous construction, raised a $270 million Series B led by and . The 1-year-old company, based in San Francisco, was valued at $1.8 billion.
• Beijing-based , a physical intelligence foundation model and humanoid robotics company, raised a $290 million Series A led by and . The 2-year-old company was valued at $1.5 billion.
• , a builder of intelligent robots for industrial and service industries, raised a $145 million Series B round. The 2-year-old Beijing-based company was valued at $1.4 billion.
• Humanoid robotics company raised a $145 million Series B led by . The 2-year-old China-based company was valued at $1.4 billion.
• , a testing and control software layer for aerospace, defense, robotics and industry, raised a $150 million Series B led by . The 1-year-old Los Angeles-based company was valued at $1 billion.
• , a company that transforms 5G and Wi-Fi into spatial awareness for connective devices, an underlying layer necessary for physical AI, raised a $100 million Series B from well-known investors , , , and . The 9-year-old Belmont, California-based company was valued at $1 billion.

Semiconductor

• China-based , developer of a chip for advanced autonomous driving, raised a $330 million Series A led by and . The company, which is less than a year old and spun out of automaker , was valued at $1.5 billion.
• London-based , a photonic chip company for more efficient AI inference, raised a $220 million Series A led by . The 2-year-old company, valued at $1 billion, has plans to ship its first product in 2027.
• Reno, Nevada-based , builder of memory chips for AI, raised a $230 million Series B led by , and . The 3-year-old company was valued at $1 billion.
• , a chip developer for AI training, raised a $500 million Series B led by and . The 3-year-old company, based in Mountain View, California, was valued at $1 billion. It plans to ship its first product in 2027.

Healthcare

• New York-based , a platform that helps employers and employees source the best doctors with improved costs, raised a $118 million Series D led by . The 7-year-old company was valued at $1.4 billion.
• Palo Alto, California-based , a women’s telehealth provider, raised a $100 million Series D led by . The 4-year-old company was valued at $1 billion.
• , a Redwood City, California-based digital platform that helps medicare customers connect with advocates to navigate healthcare, raised a $130 million Series C led by . The 4-year-old company was valued at $1 billion.

Cloud services

• , a cloud platform for application development teams, raised a $100 million Series C led by . The 8-year-old San Francisco-based company was valued at $1.5 billion.
• Mumbai-based , a cloud service GPU provider, raised a $600 million round led by . The 3-year-old company was valued at $1.4 billion.

Foundational AI

• , builder of an AI model to analyze large databases, raised a $225 million Series A led by . The company also says it has signed a partnership agreement with ‘s to offer the model to its customers. The 2-year-old, San Francisco-based company was valued at $1.4 billion.
• , a model developer to debug and understand AI, raised a $150 million Series B led by . The 1-year-old San Francisco-based company was valued at $1.3 billion.

Aerospace

• , a space-based communications infrastructure player to support commercial satellite and government missions, raised a $100 million Series B led by and. The 4-year-old Livermore, California-based company was valued at $1.3 billion.
• , an aviation hardware and software company for automated flights, raised a $300 million Series C led by and . The 10-year-old El Segundo, California-based company was valued at $1.2 billion.

Financial services

• London-based , a U.K.-based digital bank for small and medium-sized businesses, raised a $155 million Series D led by , and . The 8-year-old company was valued at $1.2 billion.
• , an agentic platform for accountants, raised a $100 million Series B led by , and . The 3-year-old company, based in New York, was valued at $1.2 billion.

E-commerce

• Brooklyn-based , a marketplace for creators to sell digital products, raised a $200 million round led by . The 5-year-old company was valued at $1.6 billion.

Coding

• , a Boston-based code translation service for legacy code, raised a $125 million Series B led by 1. The round valued the 2-year-old company at $1.3 billion.

Defense

• Berlin-based , a developer of strike drones and autonomous defense systems, raised an undisclosed sum in a round led by that valued the 1-year-old company at $1.2 billion.

Forecasting

• Boston-based , an AI-native weather satellite constellation, raised a $175 million Series F led by and . The 9-year-old company was valued at $1 billion.

Sales & marketing

• New York-based , a brand marketing platform geared for AI search, raised a $96 million Series C led by that valued the 1-year-old company at $1 billion.

Web3

• , a blockchain intelligence platform to detect crime networks, raised a $70 million Series C led by . The raise valued the 8-year-old company, based in San Francisco, at $1 billion.

Related SA国际传媒 unicorn lists:

• (1,703)
• (604)
• (65)
• (187)
• (115)
• (102)
• (878)
• (500)
• (228)
• (38)
• (471)

Related reading:

• Massive AI Deals Drive $189B Startup Funding Record In February While Public Software Stocks Reel
• SA国际传媒 Data: The AI Boom Has Drastically Changed Who鈥檚 Funding The Hottest Companies In 2025 Vs. 2021
• January Delivers Highest New Unicorn Count In More Than 3 Years

Methodology

The SA国际传媒 Unicorn Board is a curated list that includes private unicorn companies with post-money valuations of $1 billion or more and is based on SA国际传媒 data. New companies are as they reach the $1 billion valuation mark as part of a funding round.

The unicorn board does not reflect internal company valuations 鈥� such as those set via a 409a process for employee stock options 鈥� as these differ from, and are more likely to be lower than, a priced funding round. We also do not adjust valuations based on investor writedowns, which change quarterly, as different investors will not value the same company consistently within the same quarter.

Funding to unicorn companies includes all private financings to companies that are tagged as unicorns, as well as those that have since graduated to .

Exits analyzed here only include the first time a company exits.

Please note that all funding values are given in U.S. dollars unless otherwise noted. SA国际传媒 converts foreign currencies to U.S. dollars at the prevailing spot rate from the date funding rounds, acquisitions, IPOs and other financial events are reported. Even if those events were added to SA国际传媒 long after the event was announced, foreign currency transactions are converted at the historic spot price.

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Clay鈥檚 back-to-back tender offers underscore a growing shift among high-growth startups: rewarding employees with liquidity long before an IPO is in sight. As companies stay private longer 鈥� and hit major revenue milestones at breakneck speed 鈥� secondary sales are becoming a tool not just for retention, but for signaling strength. In Clay鈥檚 case, the two tenders followed rapid valuation jumps and a sprint to $100 million in ARR, positioning liquidity as a performance-based reward rather than a prelude to exit.

鈥淏uilding a generational business is a marathon, and tenders help equity feel real when top talent has options,鈥� said , a partner at who noted that as companies stay private longer and talent competition intensifies, tender offers can be a powerful tool for recruiting, morale and retention.

Still, he noted, there tend to be limits. 鈥淚n the tender offers we鈥檝e participated in, most employees were limited to selling just 10-25% of their vested holdings, and nearly half of founders didn鈥檛 sell a single share, signaling long-term conviction,鈥� he wrote via email. 鈥淓ven modest liquidity can make a big difference, translating to life milestones like a down payment on a first home, a child鈥檚 education, or helping a loved one transition into care.鈥�

Clay鈥檚 previous tender, led by , happened in May 2025 at . In between the two tender offers, the startup closed at a $3.1 billion valuation. In total, New York-based Clay has raised $206 million in equity since its 2017 inception. It has 300 employees, up from 80 to 90 a year ago, and 14,000 customers.

Tender offers have become more common as an increasing number of startups choose to stay private longer. Other high-profile examples include payments giant , which has already undergone a few tender offers and is reportedly considering that could value it at more than $140 billion. Generative AI company is also believed to be working on its own at a valuation of at least $350 billion.

In Clay鈥檚 case, the motivation was twofold, according to CEO and co-founder . The tender offers have served as a way to allow new investors to come in, and for employees to feel like their equity is 鈥渞eal.鈥�

SA国际传媒 News recently spoke with Amin to dig deeper into the company鈥檚 decision to launch not just one but two tender offers in the past nine months. The interview has been edited for clarity and brevity.

SA国际传媒 News: Before we dig into the tender offers, tell us more about what Clay does.

Amin: We help businesses find and grow their best customers. You can think of Clay as an AI go-to-market tool which implements any creative idea you have for sales and marketing.

Go-to-market is just a new name for sales, marketing and customer success 鈥� the whole apparatus that helps you find customers and grow them, and implement any idea. Our vision is that in sales and marketing, you need to constantly be doing something different that’s unique for you, different from everybody else. Otherwise, it just becomes noise.

And we let you implement these strategies. It might be something like personalized landing pages to, 鈥淗ey, let’s analyze all the video calls with sales calls that you’ve had, figure out why you lost the customer, and put that into .鈥澛�1 I like to think of it as 鈥渓ike is for designers, Clay is for go-to-market teams.鈥�

So what drove you to do not just one, but two, tender offers over the past year?

It鈥檚 interesting actually to think of it as the inverse: Why not do a tender offer?

Two reasons you don’t do a tender offer is either you don’t have the demand, or you think you’ll demotivate the team. Because we’re growing super quickly, we have the demand, and people want to invest in the company because we’re extremely efficient. Our burn is very, very low.

We don’t actually need more primary capital. We haven’t touched the primary capital. So this is a way to allow new investors to come in. This is also a way to bring in new partners without diluting the whole cap table.

It鈥檚 also a way for employees to feel like their equity is real. And some employees are having some real-life events. People are getting married, people are having kids, and this allows them to be a little bit more comfortable and do things like buy a house or buy a car. There are a bunch of people who’ve told me they’ve worked in startups for 10 years and never gotten any liquidity, and this is their first opportunity.

People might only stay at a company because they want liquidity if they don’t like the culture 鈥斅� and they’re just withstanding it for the money. But we prefer people to stay because they want to do the work and they see that the value that they’re generating is real. I actually think it motivates the team.

Plus, it makes the ecosystem grow.

When you did the earlier tender offer, did you think you would be doing another one in less than a year鈥檚 time?聽聽

No, I don’t think that we were. The way I’m thinking about it is [it makes sense to do a tender offer] every time we hit certain milestones. So we hit $100 million ARR really fast (in December). Tender offers are a way to reward the team each time it performs to a level where we get to the next milestone for the company. I think it makes sense to allow some people to get some of the value that they’ve created.

Do you have an exit plan?

Sometimes even investors ask this question. And we don鈥檛. It is nonproductive to think about that. You’re only building this type of company if you want to see how big it can be. I always say it’ll be as big as it wants to be, and as long as there are problems for us to solve for customers. That’s what we should be focused on, and the valuations and the exits, those are things that are a result of that.

The other way to think about it is we’re basically close to being profitable all the time. Like we can choose to become profitable. (The company touts that it was cash-flow positive for parts of 2025, earning more in interest than it burned.)聽 We want to be in a place where we have options.

Going public is a way to fund things so you can do more for customers. So I think whenever I start going down that line, I refocus back on, 鈥淚s there work to do for customers? Can we make the product better?鈥� And the answer right now is, yes, we’re nowhere near achieving our mission, which is how we help you finally grow your best customers. And as long as there’s work to do around that, we should keep doing it.

Do you think you’re going to be doing any more tender offers in the near future?

I think as long as we hit the next set of growth milestones, we’ll consider it. We鈥檙e still early in this. There are no exits on the horizon.

Related SA国际传媒 query:

Related reading:

• Q&A: Why Deep Tech Investors Are Turning To The Secondary Market For Liquidity
• Secondary Financings Offer Lifeline In A Slow Exit Market

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The company provides sales reps with a real-time AI assistant that 鈥済uides鈥� them during a prospect call while integrating with enterprise CRM and business intelligence systems. It also aims to eliminate administrative tasks before and after the call.

The Tel Aviv-based startup was co-founded by CEO and CTO .

The biggest difference between Winn and other startups in the space is timing, according to Postan-Koren.

鈥淢ost players in the market are passive and retrospective 鈥� they record calls to analyze after the fact why a deal was lost 鈥� a 鈥榩ost-mortem鈥� approach,鈥� he told SA国际传媒 News. 鈥淲inn is proactive and real-time. We don’t just analyze history 鈥� we help the rep navigate the conversation while it’s happening to ensure the right questions are asked.鈥�

The focus, compared to other conversation intelligence tools, is execution vs. analytics, according to Winn鈥檚 co-founders.

鈥淐oaching is hard to apply when the feedback comes a week later,鈥� Postan-Koren said. 鈥淚nstead of telling a rep what they should have done, we guide them on what to do right now.鈥�

, and co-led the Series A raise, which included participation from , , , and . In total, the startup has raised $35 million since its 2022 inception.

Companies at the intersection of AI and sales and marketing raised close to $4 billion in venture capital last year, That represents a sizable increase over the $3.4 billion raised by such startups in 2024, though remains lower than the $6.9 billion raised in the peak venture funding year of 2021 or the $5 billion raised in 2022.

Growth and expansion

Postan-Koren declined to provide hard financial figures for Winn, saying only that it tripled its annual recurring revenue in 2025 and that it has achieved 30x growth over the past two years.

Winn has dozens of customers, including HR and payroll company , IT management platform , and data security startup . The company鈥檚 revenue model is a standard SaaS per-seat subscription.

The company is not yet profitable. It plans to use its new capital to expand its U.S. go-to-market team, while continuing to invest 鈥渉eavily鈥� in R&D. Presently, Winn has over 40 employees.

Its primary market is the U.S., although Postan-Koren said it is seeing 鈥渟trong organic traction鈥� in the United Kingdom and Europe. It is also expanding its target user, he said.

鈥淲e started with a laser focus on account executives,鈥� Postan-Koren explained. 鈥淗owever, the demand quickly pulled us into other departments.鈥�

The company now also works with sales development representatives, account managers, solutions engineers and customer success. Interestingly, he said that Winn is also starting to see demand from nonsales teams, such as support and HR.

, operating partner at Insight Partners, believes that Winn 鈥渢ransforms the process鈥� of scaling a sales team.

“It helps leaders to standardize excellence across every rep, delivering higher playbook adoption,鈥� he said in a statement. 鈥淔or a sales leader, this聽 shift can bring teams closer to delivering consistency.鈥�

, managing partner and general partner at Mangusta Capital, described Winn鈥檚 offering as an AI co-pilot that can 鈥渆mpower revenue teams in real time to sell more effectively and consistently in the future.鈥�

Related SA国际传媒 queries:

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People are 鈥渄ating鈥� AI bots. CEOs are being 鈥渁dvised鈥� by digital agents. Doctors are using ChatGPT to draft patient notes. AI has moved on from 鈥渄isrupting鈥� the world to fundamentally rewiring it.

Sales is no exception. AI-powered prospecting tools and automated personalization have quickly changed how we operate 鈥� and how we sound.

These tools promise progress: faster pipelines, lead generation at scale, and more meetings booked. But beneath the metrics is a deeper issue. Trust is deprioritized in favor of speed, and buyers feel it. We stand at the precipice of an entire industry 鈥� one traditionally grounded in human interaction 鈥� flipped on its head.

We’re not moving toward better relationships or healthier bottom lines. We’re moving into the uncanny valley littered with poorly crafted cold outreach.

Creepiness is costing you

The 鈥渦ncanny valley鈥� originally described dolls or robots that look a little too close to humans 鈥� but just off enough to evoke unease. In sales, too much AI-driven personalization skews into the same territory.

Take the flurry of 鈥減ersonalized鈥� notes that reference my college mascot or a podcast I was on. Recently, I received two messages on 鈥� both from sellers of hybrid collaboration tools.

One mentioned they were impressed by my career trajectory, and congratulated me on my football team鈥檚 win the previous night. The only issue? They mentioned the wrong team 鈥� a cardinal sin and the result of an AI hallucination.

The other noted they鈥檇 looked into our company鈥檚 model, and provided a quick assessment and a straightforward POV on where they thought we could benefit.

Guess which I responded to?

It鈥檚 understandable why so many sellers are turning to AI to automate: Nearly professionals report feeling burnout, and the majority are their quota.

The problem is the system itself and the misaligned incentives it runs on. Sellers are rewarded more for volume than value; pipelines are judged by growth, not quality. When you combine that pressure with tools that can blast thousands of messages in seconds, the result is predictable.

In the short term, this floods inboxes. In the long term, it corrodes credibility, laying the groundwork for buyers to become numb, suspicious and harder to reach, and placing a premium on real, human perspective.

Trust can鈥檛 be faked

Behavioral psychology and business research consistently reinforce one truth: Trust is the foundation of persuasion.

Research shows of people need to trust a brand before they’ll even consider buying from it. ones in stock performance, productivity and customer retention.

In my eyes, trust is built primarily through four signals: communication, competence, intent and consistency. Each of these takes time to build, and any of them can be lost in a single interaction.

And that鈥檚 where AI falls short. While it can mimic pieces of these, it can鈥檛 replicate the warmth, nuance and vulnerability that build real relationships. It doesn鈥檛 know when to slow down, when to ask better questions, or when to say 鈥淚 don鈥檛 know.鈥� Authenticity, even when admitting limitations, builds trust in ways that hollow personalization can鈥檛.

People are already skeptical of AI in general: say they trust generative AI outputs, and 4 in 5 consumers can accurately content. By layering it into the very first sales interaction, companies lose more than deals. They lose long-term brand equity. They lose referral momentum. And perhaps most importantly, they lose goodwill 鈥� the invisible capital that fuels long-term growth.

Comfort is the last frontier

Especially in complex B2B environments, deals don鈥檛 close on information alone. They close on confidence, reassurance and human alignment.

During a recent call with a prospect, he was saying all of the right things, 鈥渨e鈥檙e excited,鈥� 鈥渨e see the value.鈥� But his posture was stiff, his gaze was uneven 鈥� subtle signs that, after two decades in sales, I鈥檝e learned to recognize as hesitation.

After we hung up, the cues stayed with me, so I called the next day and asked directly. He admitted he hadn鈥檛 secured senior-level buy-in yet, but felt obliged to keep things moving after so much time invested. That unlocked a dialogue around real barriers to forming a partnership, laying the foundation for us to identify and align on actual, appropriate next steps (that ultimately helped us sign the deal).

Sometimes analyzing words on a transcript isn鈥檛 enough. You have to read between the lines and let human intuition guide you where the data can鈥檛.

Because, at the end of the day, when people buy software, they鈥檙e not just buying a product; they鈥檙e also buying into a relationship.

Fully automated sales motions may win early with volume, but they often lose late. Without empathy, deals stall. Without rapport, onboardings fail. Without trust, renewals disappear.

In these cases, the lack of human interaction becomes a liability.

Sales runs on belief

As trust in institutions and media declines, buyers need more reassurance, not less. Companies have an opportunity to step up as reliable, responsive, human-first actors in their customers’ lives.

At its best, sales isn鈥檛 about pushing products. It鈥檚 about helping people find a better way forward. We just need to be intentional about how we use AI; not as a replacement for humans, but as a way to give them more room to do what matters.

No matter how sophisticated AI becomes, it can鈥檛 replace the moment of belief. The point where someone decides to trust you, your company and the future you鈥檙e offering. In an era of uncanny outreach, the most radical thing you can do is be unmistakably human.

is the senior vice president and head of growth at , a leading enterprise meal benefits platform. Landsman is a seasoned executive with more than 20 years of experience in SaaS and food tech sectors. His expertise spans startup scaling, partnership development, organizational leadership and market expansion. As former head of corporate sales at Seamless, his work helped to facilitate its merger with in 2013. At , Landsman led strategic partnerships and enterprise sales efforts, contributing to its 2021 IPO.

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The number of new monthly entrants has picked up in recent months. The top 20 companies on the board have also been reshuffled and we鈥檝e seen a marked increase in new decacorn-valued companies.

Of the 20 companies that joined in October, 11 came from the U.S. China added three new unicorns and Sweden contributed two. The U.K., Germany and Ukraine each minted one new unicorn, as did India.

Among the new entrants, New York-based open model developer and Austin-based residential battery operator each raised billion-dollar rounds that valued them as unicorns for the first time.

The highest valued among the new unicorns were Reflection, which was valued at $8 billion, and San Francisco-based payments blockchain聽 , valued at $5 billion.

Exits

A pair of companies from the unicorn board were acquired in October: Passwordless authentication company was acquired by , and , an IT employee experience platform was acquired by . In another October exit, data management tooling company merged with in an all-stock deal.

Three companies also went public: Silicon Valley-based travel and expense management company , Shanghai-based e-commerce software platform , and Beijing-based silicon wafer production company .

New unicorns

Here are October’s 20 newly minted unicorns across multiple sections. AI led with four companies, transportation with three, and healthcare and financial services followed, each with two companies.

AI

• Open source model developer , founded by engineers to compete against DeepSeek, raised a $2 billion Series B from among other investors. The 1-year-old New York-based company was valued at $8 billion.
• , which helps customers build AI applications, raised a $230 million Series C led by , and . The 3-year-old Redwood City, California-based company was valued at $4 billion. It says it has 10,000 customers, up 10x from July 2024.
• AI agent automation platform raised a $180 million Series C led by . The 6-year-old Berlin-based company was valued at $2.5 billion.
• , a platform for deploying AI agents, raised a $125 million Series B led by . The 3-year-old San Francisco-based company was valued at $1.25 billion.

Transportation

• , a builder of autonomous robovans for B2B delivery, raised a $100 million Series B4 extension led by . The 4-year-old Beijing-based company was valued at $1.6 billion.
• raised its first external financing, a $281 million funding round. The 4-year-old company is a Shanghai-based subsidiary of car battery provider CATL and was valued at $1.4 billion in the deal. It鈥檚 a developer of an integrated chassis for battery and electric vehicle functions for driving.
• Self-driving trucking company raised a $100 million funding led by existing investor and quantum company . Einride builds electric big rigs, automated smaller delivery trucks for fixed routes, and a logistics platform. The 9-year-old Stockholm-based company was valued at $1 billion.

Healthcare and biotech

• , provider of a noninvasive therapy for tumors, raised a $250 million private equity round led by its new owners which include , and , as well as additional investors and . The 16-year-old Minnesota-based company was valued at $3 billion.
• In women’s health, weight loss treatment provider raised a $50 million Series A. Investors were not disclosed. The 1-year-old London-based company was valued at $1 billion.

Financial services

• , the owner of retail trading platform Dhan, raised a $120 million Series B led by . The 4-year-old India-based company was valued at $1.2 billion.
• Digital banking software developer , owner of neobank , raised a private equity round led by . The 8-year-old Kyiv, Ukraine-based company was valued at $1 billion.

Web3

• Blockchain payments provider , incubated by and , raised a $500 million Series A led by and . The less than 1-year-old San Francisco-based company was valued at $5 billion.

Energy

• Battery-powered home energy company raised a $1 billion Series C led by . The 2-year-old Austin-based company was valued at $4 billion.

Aerospace

• Reusable rocket manufacturer raised a $510 million Series D led by to scale manufacturing. The 6-year-old Kent, Washington-based company was valued at $2 billion.

Professional services

• 鈥檚 legal platform supports lawyers with research and legal drafting. The 2-year-old Stockholm-based legal tech company raised a $150 million Series C led by . It was valued at $1.8 billion.

E-commerce

• , which connects brands with creators for e-commerce, raised a $70 million funding led by . The 5-year-old Holden, Massachusetts-based company was valued at $1.5 billion. ShopMy says it has enabled $1 billion in sales across its platform.

Sales and marketing

• , which provides a platform for community management for homeowners associations, raised a $300 million private equity round led by . Vantaca says it serves more than 500 management companies. The 9-year-old Wilmington, North Carolina-based company was valued at $1.3 billion.

Defense tech

• Defense acquirer raised a $150 million private equity round led by . The 14-year-old Arlington, Virginia-based company was valued at $1 billion.

Beauty

• Chinese skincare brand raised a $104 million funding led by and . The 24-year-old Shanghai-based company was valued at $1 billion.

Semiconductor

• , a company planning to build a compact lithography machine to support the manufacturing of chips in the U.S. market, raised a $100 million Series A from , and among others. The 4-year-old San Francisco-based company was valued at $1 billion.

Related SA国际传媒 unicorn lists:

• (1,628)
• (147)
• (113)
• (102)
• (819)
• (494)
• (220)
• (38)
• (469)

Related reading:

• In The Space Of Months, AI Funding Boom Adds More Than $500B In Value To Unicorn Board And Reshuffles Top 20
• Highest Count Of New Unicorns Join SA国际传媒 Board In Over 3 Years As Exits Also Gain Steam
• The MVPs Of The Startup World Are Still Getting More Valuable
• SA国际传媒鈥檚 Global Unicorn List Tops $6T In Value In August For The First Time Despite Slowdown
• Here Are Some Of The Newer Investors Entering The AI And Megaround Race
• These Are The Speediest Companies To Go From Series A To Series C

Methodology

The SA国际传媒 Unicorn Board is a curated list that includes private unicorn companies with post-money valuations of $1 billion or more and is based on SA国际传媒 data. New companies are as they reach the $1 billion valuation mark as part of a funding round.

The unicorn board does not reflect internal company valuations 鈥� such as those set via a 409a process for employee stock options 鈥� as these differ from, and are more likely to be lower than, a priced funding round. We also do not adjust valuations based on investor writedowns, which change quarterly, as different investors will not value the same company consistently within the same quarter.

Funding to unicorn companies includes all private financings to companies that are tagged as unicorns, as well as those that have since graduated to .

Exits analyzed here only include the first time a company exits.

Please note that all funding values are given in U.S. dollars unless otherwise noted. SA国际传媒 converts foreign currencies to U.S. dollars at the prevailing spot rate from the date funding rounds, acquisitions, IPOs and other financial events are reported. Even if those events were added to SA国际传媒 long after the event was announced, foreign currency transactions are converted at the historic spot price.

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Clarification: This story has changed since its original publication to correct an error in the Exits section.

Just over a year ago, my co-founders and I realized that our company had an existential problem.

The product we had been building and selling 鈥� a SaaS platform for sales engineers 鈥� was rapidly going to be made obsolete by AI.

When we tried to envision how our software would fit into an AI-enabled future, we realized there simply wasn鈥檛 going to be a future where people interacted with our software the way they do today. The world of SaaS tools will eventually be killed by AI-native interfaces.

We needed to start over and rebuild a product for the future from scratch. And if we were going to survive, we needed to do it without losing the bulk of our customers.

Here鈥檚 how we managed it.

Same outcomes, brand-new world

It鈥檚 important to recognize that this wasn鈥檛 a case of selling customers on an existing platform upgraded with AI features. Instead, we needed them to embrace a brand-new, AI-native product that would completely replace their existing workflows.

For a moment we asked ourselves whether we should even expect our customers to move over for us.

But the reality was that we were still aiming to solve the same problems 鈥� plus so much more with the new vision. Our existing customer was still our ideal customer profile. They bought us to solve a specific problem: improve sales productivity for sales teams selling complex products.

Our goal was to deliver the same outcomes, but far more effectively. Instead of providing a SaaS system to keep track of work done by humans, we would provide an AI system that could do the work itself.

As the CEO, I realized that it was on me to communicate such a dramatic change to our customers. I reached out to many of them across every channel I could find 鈥� I sent personal emails and personal messages, and in many cases I scheduled calls to talk through the details and answer their questions.

The message boiled down to this:

鈥淎I is a once-in-a-generation technology shift. We鈥檙e not doing you any good as a customer if we keep building things for a world that doesn鈥檛 have a future. We want to give you the same outcomes, and so much more, in a brand new world.鈥�

Three types of customer transition

For a startup founder, explaining a vision is easy. Things get harder when you start getting contracts involved.

As we looked at how to transition our customers from their existing agreements to the new product, we found that we had to have three types of conversation.

Our customers paid for user licenses, and our approach depended on their level of utilization with our existing product. The first group of customers were those who were basically completely utilized and relying on our existing SaaS product.

For those customers, our approach was essentially a net new cross-sell sales cycle, helping them to secure new budget for the new product we were selling. Over time, we expected them to free up budget as users transitioned from the old platform to the new platform, but these heavily utilized customers needed us to help them communicate the new direction and secure additional budget.

While those were tough conversations, the majority of SaaS customers are not typically 100% utilized. For customers that had some capacity, we were able to offer a middle path. We took the amount that those customers were underutilized and offered it as a credit to use the new service.

That way they could prepare for the transition by having some users on the new service as a forward-deployed team; once it became time for renewal, those users could help with change management and support the rest of the organization.

The last group of customers were those who were underutilized but didn鈥檛 have significant change management needs. These companies 鈥� typically smaller, more nimble organizations 鈥� could simply take their existing spend and move it from point A to point B. For those customers, we just turned off the SaaS service, booted up the new AI platform and provided the same level of training that we would provide to a net new customer.

The result? Across all three groups, more than 80% of our customers have already transitioned or are in the process of transitioning to the new platform. While it wasn鈥檛 easy, the result is a stable company that鈥檚 now built to thrive in the AI era.

What we learned

When we were deciding what to do a year ago with our suddenly disappearing product roadmap, we settled on a specific motto: Instead of waiting for the axe to fall, prepare for a world where you have no head.

Right now there are hundreds of SaaS companies that are anxiously waiting for the moment when AI renders their product or service obsolete. Instead of trying to wring the last drops of revenue we could out of an inferior product, we chose to make a bet and build into the fog.

We learned a few key lessons in the process:

• Rip off the Band-Aid: While the decision sounds easy in hindsight, the actual change itself had to be handled extremely delicately. We had to reassess team members to determine who could support the new product while maintaining the existing product at the same time, and we had to let go of employees who no longer fit with the new vision of the company. We also had to make the case to our investors that we were still on the right path. The longer we waited to change our platform, the harder the transition would have been 鈥� this is a moment for decisive action.
• Don鈥檛 sugarcoat the situation: In all of our conversations with employees, investors and customers alike, we gave them a straight, unvarnished story. By being brutally honest about how we saw the market, we maintained a lot of credibility at a moment when it would have been fair to question our judgment.
• Look for easy compromises: We could have taken a take-it-or-leave-it approach with our customers. We believed in our new product and didn鈥檛 see a long-term future for our old one. But a rigid approach probably would have led to a lot more lost customers, even though we were still solving the problems they bought us for in the first place. Finding the middle ground and supporting companies that needed to linger on the older SaaS platform a little longer allowed us to keep more customers in the fold and maintain a stable business during a period of disruption.

In the end, we found one more silver lining to our year of disruption. In talking to our customers, there were a few who were approaching renewal who weren鈥檛 planning to continue with the previous SaaS platform. But the new AI platform? They didn鈥檛 just renew 鈥� they expanded.

is the CEO and co-founder of , the AI sales teammate. Prior to Vivun, he built the global presales team and ran multiple product lines during ‘s IPO run.

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鈥檚 independent growth fund, , led the round. Existing backers , , , and , as well as new investor , also participated.

Notably, the financing comes just six months after New York-based Clay announced it had secured $40 million at a $1.25 billion valuation in led by Meritech Capital.

In May, Clay completed led by Sequoia at a $1.5 billion valuation. The latest infusion brings Clay鈥檚 total raised to $204 million since its 2017 inception. The company told SA国际传媒 News that it 鈥渉asn鈥檛 touched鈥� the last round it raised.

Clay鈥檚 platform aims to 鈥渢ransform鈥� traditional sales and marketing operations, building automated workflows that it says can research thousands of prospects, personalize outreach at scale, and identify revenue opportunities 鈥渢hat would be impossible to find manually.鈥�

It integrates with more than 150 data sources, and its AI agents can perform research tasks such as monitoring competitor mentions to trigger personalized campaigns, or analyzing satellite imagery to count warehouse parking spots as a predictor of customer fit.

The company also claims to have developed something it calls a 鈥�.鈥�

鈥淕TM engineering represents the first true AI-native profession, and we believe that it will be tech鈥檚 next big job category,” said , CEO and co-founder of Clay, in a written statement. Amin originally founded Clay and was joined by co-founder in 2021.

Anand told SA国际传媒 News via email that Clay first coined the role of GTM engineering in 2023.

鈥淕TM engineers combine growth acumen with AI and automation to build revenue engines. We call it 鈥榚ngineering鈥� because they work within certain parameters to build scaled systems 鈥� but instead of coding software, they’re coding revenue,鈥� he said.

Clay raised another round to fuel the growth of GTM engineering and make 鈥渕ajor鈥� product upgrades, including autonomous agents for research and messaging, the ability to use first-party data, and better signals, according to Anand.

While Clay did not disclose hard revenue figures, it notes that its revenue is 鈥渙n track to more than triple this year.鈥� The company鈥檚 10,000-plus customers include , , , , and .

For its part, CapitalG said in that over the past 18 months, it spoke with more than 100 sales and marketing leaders, studied past approaches to the sales and marketing stack, and projected how AI would change go-to-market. Its goal was to develop its perspective on the next era of go-to-market technology.

鈥淯ltimately that work culminated in our deep conviction that Clay will become the de facto go-to-market platform for the AI era,鈥� wrote 鈥� who previously served as CMO of 鈥� and CapitalG investor .

鈥淔or decades GTM teams have had to deal with a suite of point solutions that chip away at pain points but in aggregate created a Frankenstein’s monster of disconnected tools,鈥� they added. 鈥淔or the first time, Clay gives revenue teams a single platform from which they can launch any campaign, limited only by their imaginations.鈥�

Related SA国际传媒 query:

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Photo courtesy of Ava Pellor via Clay.