The road to the top rarely runs in a straight line, but there are less circuitous routes to becoming CEO. According to analyzing every CEO succession in the S&P 500 since 2000, there are four feeder roles: COOs, divisional CEOs, CFOs, and 鈥渓eapfrog鈥� leaders promoted from below the C-suite.听

But a separate 10-year study called the suggests that the fastest climbers 卤 鈥渟printers鈥� who reached the CEO seat well ahead of the 24-year average 鈥� didn鈥檛 get there by climbing the corporate ladder to the top. They got there through bold, often unconventional career moves, such as taking on a failing division or building something from scratch.听

In fact, what set them apart wasn鈥檛 pedigree but building a specific skillset that made them CEO material: decisiveness, reliability, adaptability, and the ability to engage people around a plan.

Product management doesn鈥檛 appear in the CEO-pathway research, likely because none of the major studies breaks the role out as a separate category. It鈥檚 a relatively newer function, and it tends to get folded into general management or engineering in career datasets.听

But once you look at what the job demands 鈥� ownership of a tangible outcome, obsession with what customers value, the willingness to make tough decisions 鈥� it maps directly onto the traits the CEO Genome Project found in its sprinters.

I鈥檝e spent my career leading product and technology at companies including , , and . Those roles landed me my first CEO position without having to fill the typical CEO-starter pack jobs because I was able to articulate my skill set to the board.听

In short, product management is about making a product successful; being CEO is about making a business successful. The ingredients are the same.听

Don鈥檛 take my word for it. joined in 2004, leading product management for the Google Toolbar, years before he became CEO. spent eight years as YouTube鈥檚 chief product officer before taking the top job there in 2023.听

Yes, the scope of the job differs, but that鈥檚 true of every promotion, especially for the hardest job on offer. A CEO carries the full weight of the business: financial performance, legal and regulatory exposure, the board, and the market. A PM鈥檚 remit is naturally narrower: one product, one roadmap, one team to rally.听

But scope isn鈥檛 the same as skillset. The job gets bigger, but the muscles you exercise remain the same: setting a vision under uncertainty, prioritizing ruthlessly, making calls with incomplete information, and getting people who don鈥檛 report to you to deliver anyway. Learn to do that for a product, and you鈥檝e already learned to do it for a business, just on a bigger scale.

That mindset isn鈥檛 new to start-ups and scale-ups either, where a PM is often the closest thing to a mini-CEO, making calls across product, growth, and operations simply because no dedicated function exists yet to do it for them.听

Part of the reason I think the PM-to-CEO pathway is so often overlooked is that the function is judged by its worst practitioners. Plenty of people with 鈥減roduct manager鈥� on their CV spend more time managing processes and stakeholders than owning outcomes and building amazing products. And it鈥檚 that version of the job that shapes how PMs get perceived, and why few are inspired to make the leap. The PMs who have done the job – by taking ownership of the outcome rather than the process – are building something that truly resembles the job description of a CEO.听

The best advice I can give to aspiring executives and entrepreneurs today – whether they鈥檙e PMs or not – is to choose a metric that they want to be accountable for. In my previous role, I focused on monthly active users; now I鈥檓 focusing on EBITDA. Strip away the layers and remain outcome-oriented.听

The CEO pathway research keeps looking for the right sequence of job titles, but that model is increasingly outdated in the modern-day work environment. Rather than focusing on traditional CEO pathways, aspiring executives should focus less on glitzy job titles to add to their CVs and more on the concrete skills they can gain. Product management, done properly, offers the perfect crash course.听

is the CEO of , a London-based technology company building a global payments infrastructure to facilitate money transfers. He previously led product and technology for companies including , , and .

Illustration:

That was the intent of our latest 兔子先生传媒 News data dive into seed-stage trends. For this installment, we focused on mid-sized rounds of between $5 million and $10 million, analyzing around 800 global seed financings that closed this year.听

Why this range? In a startup investment climate characterized by the ascendance of megarounds, the idea was to focus on rounds more representative of the classic seed deal: a risky bet on unproven founders, technologies or business models.

Using this methodology we identified multiple popular investment themes and zeroed in on five. The first 鈥� cybersecurity 鈥� we tackled in a separate piece. Here we delve into the other four: proptech, cancer therapeutics, space tech and robotics.

No. 1: Proptech

Real estate is the world鈥檚 most valuable asset class, providing startups a huge and varied addressable market. By one estimate a few years ago, real estate accounted for a staggering two-thirds of global net worth.

Given the size of the space, actual venture investment tied to real estate and construction looks comparatively meager. Last year, per 兔子先生传媒 analysis, proptech startup investment totaled just over $10 billion, far below peaks hit several years ago.

Seed investors seem to believe there鈥檚 a good case for startup driven growth ahead. In particular, they鈥檙e funding a lot of rounds in the $5 million to $10 million range for companies looking to add efficiencies to the planning and building process, streamline rental operations, reduce building power consumption, and more.

To illustrate, below we put together a sample set of 15 companies that closed seed rounds in our target range this year:

A few standouts include , an AI-powered home management system, , a developer of software to support real estate decarbonization, and , an AI-enabled construction supply chain platform.听

No. 2: Cancer treatments

Startup founders don鈥檛 need persuasive superpowers to convince investors that cancer is a sufficiently serious area to address. Today, it鈥檚 that 39% of Americans will be diagnosed with cancer at some point in their lives. Cancer also ranks as the second leading , behind heart disease.听

Seed-stage companies aren鈥檛 expected to bring down numbers in the near term, but as they progress, it鈥檚 increasingly plausible. That鈥檚 the apparent mindset for investors at this stage, who鈥檝e backed a good-sized number of rounds in the $5 million to $10 million range this year for developers of cancer therapeutics and diagnostics, charted below:

Three California startups secured $10 million, the largest financing in our sample set. They include: , which is working on AI-driven discovery of undetected cancer targets, , a developer of targeted therapies for solid tumors, and , which is focused on cancer diagnostics.

No. 3: Space and satellite tech

This year鈥檚 most attention-getting event in space tech finance was obviously the IPO of sector pioneer . But while that debut may have dominated headlines, quite a few smaller, earlier, lower-profile deals were also getting done.

Per 兔子先生传媒 data, space tech was a popular area for seed financings in the $5 million to $10 million range. To illustrate, below we put together a sample set of nine such companies that raised rounds this year:

The largest fundraiser in our target range was , which is focused on developing reusable satellites. Next was , focused, as its name implies, on in-space propulsion systems, followed by , developer of an ML-native operations platform for satellite fleets.

No. 4: Robotics

Robotics is a perennial favorite in our seed-funding data dives, including the last one, focused on AI. This time, the sector made the ranking again, thanks to a bevy of intriguing seed-stage companies that met our parameters.

Turns out, you can jumpstart some highly ambitious ventures on a $5 million to $10 million seed round. To illustrate, below we aggregated a sample of 18 funded this year:

Robotics was also the most geographically dispersed sector in our lineup, with startups hailing from Asia, North America, Europe and Australia. A few that stood out include , a developer of what it calls 鈥渋ntimacy robots,鈥� , a maker of autonomous underwater robots, and , focused on robots for greenhouse harvesting.

Big picture: Midsized seed rounds for outsized ambitions

Overall, seed funding trends reviewed above may tell us more about the kinds of companies investors are willing to bet on than about the sectors attracting interest, which are already well-established.

Clearly, startup investors still believe that small, modestly funded teams with grand missions remain a worthwhile and viable wager. That鈥檚 particularly encouraging these days, when the venture and seed financings we most commonly hear about tend to be the largest ones.

That鈥檚 not to diss large rounds. Startups that are led by prominent serial entrepreneurs or have established traction hold obvious appeal, even at pricier terms. But for those of us who enjoy rooting for the underdog, it鈥檚 encouraging to see lower-profile companies with outsized ambitions are still in the game.

Related 兔子先生传媒 lists:听

Related reading:

• AI Seed Investors Flock To Cybersecurity听
• In Charts: Seed Deals Keep Getting Bigger As Odds Of Reaching Series A Fall Dramatically听
• AI Seed Trends: More Multimedia, Backend Automation, Agentic Security, And Yes, Robots

Illustration:

After pausing his entire engineering team’s workload for two weeks to ship a requested fix, he discovered the effort made no difference. The customer still threatened to churn.

“We did a retro, and wouldn’t you know? The person who’s asking for the new request was the new decision maker [we] didn’t even realize existed,” said Kataria, co-founder and CEO of San Francisco-based , in an interview. 鈥淲e missed the fact that the prior person had left, and the context had shifted hands, and no one had tracked that.鈥�

That breakdown planted the seed for Centralize, an enterprise sales platform emerging from stealth today alongside a $15 million Series A funding round led by (NEA).

The financing includes participation from ,1 , , Ritual Capital, Adverb Ventures and high-profile angel investors including former co-founder and , CEO and founder of .听

Combined with a previous $4 million seed round led by Salesforce Ventures, Centralize has now raised $19 million since its 2023 inception to build what Kataria calls a “deal GPS” for enterprise revenue teams.

Engineered by Big Tech vets

Kataria and co-founder and CTO met more than a decade ago as engineering students at the .听

Both went on to build high-scale products across Big Tech. Kataria served as a founding engineer on Facebook Shops during e-commerce push during COVID-19, scaling the platform from zero to a quarter billion monthly active users in a year. Wang, meanwhile, created Slack Huddles, building the initial version alongside Slack executives (CTO), (VP of product), and Butterfield (CEO), and later leading engineering and product teams at Slack.

After honing their technical chops in big tech, Kataria joined Y Combinator-backed fleet card startup as a product tech lead. It was there, while working closely with go-to-market teams to save that churning enterprise customer, that he recognized a fundamental gap in modern revenue operations.

鈥淚t was just this sea of information that no one had a handle on. The deal was at risk because the relationship is what mattered most, and we didn’t have a handle on it,鈥� Kataria told 兔子先生传媒 News in an interview. 鈥淥ne of the things that we always say is that the one thing AI can’t commoditize is relationships.鈥�

Solving the 鈥榤ulti-threading鈥� problem

Founded through Y Combinator鈥檚 Winter 2024 batch, Centralize aims to fix what Kataria describes as a lack of an actual relationship layer in modern sales platforms.

After bringing its primary product to market in December 2024, Centralize focused heavily on “multi-threading,鈥� or the practice of identifying, engaging, and organizing all necessary stakeholders high and wide within a target company, from procurement and legal up to the C-suite.

Rather than acting as a static record, Centralize operates as a visual, multiplayer surface centered around automated org charts that function like a map. AI agents analyze first-party data, call recordings, emails, calendar events, and web sources to continuously construct a live picture of key relationships.

鈥淚t’s kind of like a deal GPS,鈥� Kataria explained. “Or like a visual map, in which the people are the map. It’s the puzzle pieces. It’s basically like a landscape of who we know, who’s missing, how we get there, and then it’s the turn-by-turn navigation.鈥�

Centralize鈥檚 AI assistant is named “Centra,” and answers questions such as 鈥淲ho owns the budget?” or “How do we approach the CRO?” in seconds, the company claims. It also flags the moment a champion leaves, a new decision-maker joins, or engagement drops on a key deal.

Besides proactively flagging missing stakeholders, such as empty leadership seats or unengaged decision-makers, the platform also identifies warm entry points through mutual connections or past company overlaps.

Rapid growth and a bottoms-up launch

Centralize charges enterprise revenue teams based on 鈥渁ccounts under management鈥� with unlimited seats, encouraging cross-functional teams, including account executives, sales development reps, and customer success managers, to collaborate on account maps in real time.

The approach is driving rapid momentum. Over the past year, revenue has expanded significantly, driven by adoption among fast-growing enterprise companies.

“Since last year, we’ve… almost 8xed the company in revenue,” Kataria said, noting that much of that momentum accelerated over recent months.

The startup鈥檚 client roster features notable tech names, including , , , , , and .

To accelerate expansion, Centralize is launching a free, single-player tier alongside its funding news. The move allows individual account executives to sign up, build real-time account maps, and introduce the platform organically to executive leadership.

, venture partner at NEA, noted that the investment in Centralize was driven by the founders’ 鈥渦nique鈥� vision and execution.听

鈥淩achit and Will have built something rare: a product that sales teams actually want to use, not just another system of record they’re forced into,鈥� she wrote via email. 鈥淲e led Centralize’s Series A because we saw a founding team with an unusually sharp read on how AI changes the day-to-day of enterprise sales.鈥�

Koplow-McAdams also noted that buying committees have nearly doubled in size over the last decade. 鈥淭he entire revenue tech stack was built around activity capture, rather than navigating buying committees,鈥� she added. 鈥淭hat’s a structural gap, and it’s only widening as AI raises the stakes.鈥�

Startups like Centralize that bring AI to bear on enterprise marketing and sales have seen a strong uptick in funding this year, 兔子先生传媒 , with 2026 on pace to beat last year, which was the strongest year for venture investment into startups related to sales, marketing and CRM technology since 2022.

 

Related 兔子先生传媒 query:

Related reading:

• Sector Snapshot: Sales And Marketing Gets An AI Makeover听

Illustration:

---

1. Salesforce Ventures is an investor in 兔子先生传媒. It has no say in our editorial process. For more, head here.↩

]]>

and co-led the financing, which included participation from and former U.S. Commerce Secretary . With its latest capital injection, San Francisco-based Freehand has now raised $100 million.

While Freehand declined to reveal its valuation, CEO and co-founder said it was 鈥渁 significant step up鈥� from the startup鈥檚 $25 million Series A that was raised in March 2024.

The deal comes as tariffs, taxes, and immigration policy strain the outsourcing model that ran supply chains for decades. Freehand鈥檚 fundraise also lands amid an uptick in venture funding to supply chain and logistics-related startups, with 2026 on pace to deliver the strongest year since 2022, , with $6.2 billion raised by such companies in the first half of this year across 350 deals.

Logistics roots

Freehand was founded in February 2024 by Jayakrishnan and , two enterprise logistics veterans who previously co-founded and recently sold , a SaaS transportation management system (TMS) and procure-to-pay system of record for large enterprise logistics.

In early 2024, as AI transformation accelerated, Jayakrishnan and Manohar stepped away from operational roles at Pando, moving to board positions, to launch Freehand as an independent entity focused entirely on agentic AI.

Pando continued operating under a newly appointed executive team before being sold to a strategic buyer in early 2026, marking a complete shareholder exit for the founders.

Their experience building enterprise supply chain software convinced them that existing back-office paradigms were ripe for disruption.

鈥淲e had been in this fairly archaic dinosaur of an industry for the last six to eight years,鈥� Jayakrishnan told 兔子先生传媒 News in an interview. 鈥淚nstead of trying to catch them up to a technology paradigm that was sunsetting, we thought we could leapfrog them into a technology paradigm that was just rising.鈥�

Beyond corporate cards

While spend management platforms like focus on corporate cards, employee travel expenses, and bill payments, Freehand targets complex supply chain operations. That means that instead of processing standard receipts and routine approvals, its AI agents manage non-standard spending across logistics, raw materials, parts, and labor.听

The software operates inside existing company systems, performing tasks like reading contracts, policies, emails, and internal data to verify bills, track operational milestones, and handle vendor negotiations.

Automating complex financial governance

For large, global businesses, keeping track of supplier bills across complex shipping routes like the Red Sea and the Strait of Hormuz is difficult. Contracts are detailed, and checking whether large bills match actual work has historically required big back-office teams.

鈥淲hen eventually rubber hits the road, when you get an invoice from a supplier saying, ‘Hey, you owe me $16.948 million for everything that I’ve done for you in the last six months,’ there aren’t a lot of proof points to figure out whether you know if that number is right or wrong,鈥� Jayakrishnan noted. 鈥淎nd so there are large teams that have gotten built over the course of the last decade or so, whose job it is to check these invoices, negotiate these contracts, and figure out whether service obligations from global suppliers are in alignment with contract governance overall.鈥�

When billing discrepancies arise, Freehand鈥檚 AI agents negotiate adjustments directly with suppliers while maintaining strategic vendor relationships.

鈥淚f it is not, then negotiating with the supplier becomes, 鈥�’you should have charged me $16.4 million instead of charging me $16.9 million and here’s why I’m not going to pay you the difference,’ and going back and forth without… losing the sensitivity towards that relationship itself,鈥� Jayakrishnan said. 鈥淭aking those business calls, which have historically been done through tribal knowledge… and truly automating the process to the point of no human intervention is effectively what Freehand does.鈥�

Measurable ROI for Fortune 500 spend

By shifting from manual oversight to agentic automation, Freehand believes it allows enterprises to reduce their reliance on third-party offshore outsourcing and give internal employees more room to perform higher-value strategic work.

Freehand counts some 50 customers, including ,听, and . Its platform autonomously processes billions in payments across 60 to 70 countries and hundreds of currencies without human supervision, per the company.

Some of the benefits of its technology, according to Jayakrishnan, include recovering 5% to 10% of total spend across a number of categories; completing 鈥渃omplex鈥� operational workflows 5x to 7x faster; and reducing overall procure-to-pay cycle times by more than 70%.

鈥淲e are, for a lot of companies, their first global rollout of AI deployments at scale that impacts daily transactions and daily operations at global scale,鈥� Jayakrishnan said. 鈥淥ur ask of the enterprise 鈥� is to allow us to give AI a free hand to run supply chain finance for your business.鈥�

, general partner at Battery Ventures, noted that while supply chain and logistics management is a massive sector, it predominantly 鈥渟till runs on manual labor and repetitive workflows that are begging to be automated.鈥�

鈥淎nd that’s before you account for the turmoil: tariffs, shifting geopolitics, disrupted trade routes,鈥� he wrote via email. 鈥淢eanwhile, technology spending is a rounding error at just over $20 billion, which tells us AI has enormous room to drive efficiency, starting with the most mission-critical but repetitive workflows like freight audits and payments.鈥�

Thakker said his firm did deep research on supply chain AI across its global offices and found Freehand to stand out on multiple fronts, including founder market-fit, a focus on the largest Fortune 500 shippers 鈥渞ather than the intermediaries everyone else chases, and clear, measurable business outcomes.鈥�

Related 兔子先生传媒 query:

Illustration:

and each launched multibillion-dollar deployment ventures staffed with forward-deployed engineers, while a long list of startups building AI infrastructure, autonomous software and robotics also reached unicorn status. Together, the new entrants point to where investors increasingly see value creation: turning AI advances into real-world applications and pairing software intelligence with physical automation.

Beyond AI, new unicorns were minted across many sectors including healthcare, quantum, aerospace, financial services, manufacturing, e-commerce and energy.听

China dominated in the robotics sector, while Canada did so in quantum. The single new legaltech unicorn last month was from Brazil. also joined the board this past month, as the adult creator content company raised its first external financing.听

Of the new unicorns, 17 are U.S-based, while four each are based in China and the UK. Two new unicorns joined the board from Canada, as one each from India and Brazil.听

Unicorn IPOs

The board鈥檚 total value is undergoing rapid fluctuations amid lofty new valuations for some of the largest new unicorns, as well as high-profile exits to the public markets.

The 兔子先生传媒 reached $9.9 trillion in value in May, as Anthropic moved ahead of OpenAI to become the second most valued private company after . On the heels of the funding, Anthropic privately filed for an IPO, followed shortly thereafter by OpenAI’s .听

SpaceX is expected to list this Friday, in what would be the largest-ever IPO. Its listing will erase more than one-tenth of value from the board as the the -led company exits the private markets.听

Chip company went public in May in a blockbuster IPO that valued the company at $56.4 billion,听well above its last private valuation of $23 billion just three months earlier in February.听

New unicorns in May

Here are May鈥檚 new unicorn companies, including 10 companies that are less than 3-years old:听

AI deployment

• San Francisco-based raised a $4 billion private equity round led by with co-leads , and . The new company is majority owned by with partnerships with 19 investment firms and consultancies. OpenAI acquired , with its 150 forward-deployed engineers to support enterprises in this effort. The less than 1-year-old-based company was valued at $14 billion in the new funding, which it said will be used to scale operations and acquire companies.听
• raised a $1.5 billion private equity funding to build an AI services company to work with companies to bring Claude into their operations. Each of the co-leads 鈥� , private equity investor and legal firm 鈥斕齣nvested $300 million into the round. and also invested in the joint venture. The less than 1-year-old-based, San Francisco-based company鈥檚 valuation was not disclosed.
• , a company building search for AI agents, raised a $250 million Series C led by . The 5-year-old San Francisco-based company was valued at $2.2 billion and is used by coding agents, go-to-market agents and chat agents.听
• Boston-based autonomous AI software developer raised a $200 million Series A led by . Blitzy鈥檚 platform reverse engineers existing code bases to build a knowledge graph and thereby enable autonomous development of software projects over days or weeks that can re-engineer and test complicated systems and deal with technical debt. The 2-year-old company was valued at $1.4 billion and is said to be used by dozens of global 2,000 companies.听
• , a routing technology for applications to select from 400-plus models, raised a $113 million Series B led by Alphabet鈥檚 . Investors in the round included a host of corporate venture firms including , , , and . The 3-year-old New York-based company was valued at $1.3 billion.

Robotics听

• raised a $700 million Series A led by . The company plans to build personalized robotics developing its own models, training and hardware. The 1-year-old San Jose, California-based company was valued at $6 billion. It was founded by CEO , founder of humanoid robotics unicorn .
• Guangdong, China-based , a dual arm robotics developer, raised a $147 million Series B led by and . It said its new funding will be used for R&D, production and a global sales network. The 10-year-old company was valued at $1.5 billion.听

• Shanghai-based has raised four funding rounds since it was spun out of in January, and reached a valuation of $1 billion. Agilink is focused on dexterous hand technology. The funding will be used for model development, data and hardware with the spinout able to license to the broader robotics market.听
• , a robot leasing and rental platform, raised a Series A funding. The less than 1-year-old Pudong, China-based company was valued at $1 billion. It is looking to expand from event rentals to warehousing, logistics and park operations.听

Healthcare听

• , a treatment provider for cardiovascular and orthopedic disease, raised a $1.5 billion corporate round led by . Boston Scientific has an option to acquire its heart valve technology. The 10-year-old Georgia, U.S.-based company was valued at $4.4 billion.听
• , a longevity biotech company, seeking to extend human life by a decade, with therapeutics targeting age related disease raised the initial close of funding round led by . The 5-year-old Redwood City, California-based company was valued at a pre-money valuation of $1.8 billion.听
• , launched a suite of AI agents for healthcare built from its clinical data, raised $146 million in equity and secondary funding led by . The 15-year-old New York-based company was valued at $1.6 billion.

Quantum computing

• Vancouver-based , a quantum computing company that combines silicon-based qubits with native photonic interconnects, raised a $70 million extension funding led by Luxembourg-based . Photonic raised $130 million in January. The 9-year-old company was valued at $2 billion.
• Quebec-based , which says it addresses quantum error correction in each qubit, raised a $30 million funding. The company has raised a mix of government grants and venture capital. The 6-year-old company was valued at $1.4 billion.

Aerospace听

• , a builder of rockets to deploy data centers in space, raised a $305 million Series B led by . The 2-year-old San Carlos, California-based company, formerly called Aetherflux, was valued at $2 billion. The company plans to launch its first satellite later this year. Its technology entails using the upper stage of the rocket as a low-earth orbit satellite that uses solar energy to create 1-megawatt data centers in space.听
• Hyderabad, India-based , a rocket company that delivers satellites into space, raised a $60 million funding led by Singapore-based and Menlo Park, California-based . Skyroot is planning the maiden voyage of Vikram-1 in June. The 7-year-old company was valued at $1.2 billion.

Financial services听

• , an AI insurance provider for startups, raised a $160 million Series B led by . The 2-year-old San Francisco-based company was valued at $1.3 billion and plans to go after the trucking industry next.听
• Intelligent wealth management platform raised a $150 million Series D led by . With in recruited assets, it is built to create an all in one system for advisors. The 7-year-old San Francisco-based company was valued at $1 billion.

Manufacturing听

• , a manufacturer of aerospace and defense components, raised a $300 million Series B led by . The 1-year-old El Segundo, California-based company, which aims to strengthen America鈥檚 industrial base, operates six factories across the U.S. and was valued at $1 billion.
• , likewise says it is building out American manufacturing with a rapid custom manufacturing software to production platform. It raised its first institutional funding of $110 million led by , and founders and . The 7-year-old Reno, Nevada-based company supports small-scale inventors to large-scale enterprises and has shipped 30 million parts to 300,000 customers. The company was valued at $1 billion.

E-commerce

• , a real-time inventory management platform, raised a $170 million Series B led by and . Its sensor technology tracks items and its precise location and movement in the store. Retail customers include and . The 13-year-old New York-based company was valued at $1 billion.

• London-based , a booking service for hair salons, beauty experts and wellness salons raised a $80 million Series C led by . The 11-year-old London-based company was valued at $1 billion.

Energy听

• , a nuclear fusion startup spun out of Tsinghua University, raised a $74 million Series A funding. The 4-year-old China-based company was valued at $1 billion.
• , a provider of fast charging batteries, raised a $60 million Series C led by strategic investor . The batteries are used in data centers, robotics, electric vehicles and grid infrastructure. The 7-year-old Cambridge, UK-based company was valued at $1 billion.

Social media听

• Creator platform raised its first external funding, a $535 million private equity round led by , which now owns around 16% of the company. The 10-year-old London-based adult content platform was valued at $3.2 billion. Its CEO noted the company has paid out since 2016.

Data center听

• Modular data center builder raised a $230 million Series B led by , and. In partnership with the company plans to build capacity for secure data centers useful for military and remote manufacturing environments. The 3-year-old San Francisco-based company was valued at $2.2 billion. Customer booking for fiscal year 2026 was up 540% from 2025.听

Legaltech听

• S茫o Paulo-based , a Brazilian AI legal platform to manage company litigation, raised a $100 million Series B led by that valued the 2-year-old company at $1.2 billion. Enter counts , and among its customers, who use its technology along with law firms to handle litigation paperwork and settlements. Around have been managed through the platform. led the Series A.

Cryptocurrency听

• , a digital asset trader, raised a $150 million funding led by , UK bank Standard Charter鈥檚 fintech arm. The deal brings digital assets into banking and represents GSRs first strategic external investor. The 12-year-old London-based company was valued at $1 billion.听

Security听

• , a security platform built for an open-source automated coding environment, raised a $60 million Series C led by . The platform is adopted by companies including Anthropic, , , , and and supports 27,000 organizations. Its socket firewall product is free to block malicious packages. The 6-year-old Stanford, California-based company was valued at $1 billion.

Related 兔子先生传媒 unicorn lists:听

• (1,785)
• (619)
• (160)
• (189)
• (118)
• (102)
• (921)
• (525)
• (241)
• (39)
• (486)

Related reading:

• Anthropic Files Confidentially For IPO听
• Active Startup Investors Didn鈥檛 Hold Back In May
• Anthropic Funding Pushed Startup Investment To Near-Record Levels In May As Exit Market Reopened听听

Methodology

The 兔子先生传媒 兔子先生传媒 is a curated list that includes private unicorn companies with post-money valuations of $1 billion or more and is based on 兔子先生传媒 data. New companies are as they reach the $1 billion valuation mark as part of a funding round.听

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.听

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

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

Please note that all funding values are given in U.S. dollars unless otherwise noted. 兔子先生传媒 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 兔子先生传媒 long after the event was announced, foreign currency transactions are converted at the historic spot price.

Illustration:

This is a weekly feature that runs down the week鈥檚 top 10 announced funding rounds in the U.S. Check out last week鈥檚 biggest funding deal roundup here.

Defense tech unicorn led the fundraising lineup in a week heavy with rounds for companies focused on applications in the physical world. Anduril鈥檚 $5 billion financing was by far the biggest. Other large rounds went to companies focused on supplying data power, robotics, space tech, biotech, and even strawberries.

1.听, $5B, defense tech: Defense tech unicorn Anduril Industries raised another $5 billion in funding at a $61 billion valuation 鈥� double the valuation of $30.5 billion it received less than a year ago. The Series H round, led by and , brings the Costa Mesa, California-based company鈥檚 total raised to date to $11.4 billion, .听听

2.听, $775M, energy: Houston-based VoltaGrid, a provider of mobile natural gas generators for data centers, microgrids and industrial applications, secured $1 billion in strategic investment from and . The investment includes $775 million in capital funding and a $225 million secondary purchase from existing investors.

3.听, $400M, robotics: Palo Alto, California-based Mind Robotics, developer of an AI-enabled industrial robotics platform, picked up $400 million in new financing led by . The round brings total funding to date to more than $1 billion for the startup, which launched in 2025 as a spinout of .

4.听, $275M, space tech: Cowboy Space, a developer of rockets and satellite infrastructure to power and run AI compute in space, closed on $275 million in Series B funding at a $2 billion valuation. led the financing for the San Carlos, California-based startup, which was founded by co-founder .听

5.听, $150M, indoor farming: Oishii, operator of highly automated indoor farms for growing strawberries, raised $150 million in Series C funding led by . Founded in 2016, the Jersey City, New Jersey-headquartered startup has raised $370 million in total funding to date.

6.听, $125M, cybersecurity: San Jose-based Exaforce, developer of an AI-native security operations platform, secured $125 million in Series B funding from backers including , , , 听and听 .

7.听, $122M, biotech: Create Medicines, a Cambridge, Massachusetts-based startup focused on in vivo immunotherapies for autoimmune diseases and cancer, closed on $122 million in Series B funding. , , and led the financing.

8.听, $100M, autonomy: Providence, Rhode Island-based HavocAI, a provider of tools for developing military and commercial-grade autonomous systems across sea, air and land, secured $100 million in Series A funding. The round brings total funding to date for the 2-year-old company to $200 million.

9.听, $65M, space tech: Star Catcher, a startup that says it is building the first power grid in space by beaming concentrated solar energy on demand to satellites, picked up $65 million in Series A funding. , and led the financing for the Jacksonville, Florida-based company, which was founded less than two years ago.

10.听, $64M, data center power: GridCare, developer of technology to more efficiently provide power to AI data centers, raised $64 million in Series A funding. led the financing for the Redwood City, California-based startup.听

Related reading:

• Anduril Raises Another $5B As Defense Tech Startups Shatter Funding Records听

Illustration:

The energy sector necessary for AI compute also garnered significant funding this year.听

All told, roughly half of European venture funding in 2026 to date has been in AI-related companies, 兔子先生传媒 data shows.

The uptick in artificial intelligence investment has coincided with an overall gain in startup funding in the region the last past quarters. Funding was up a third year over year in Q4 and Q1, reaching more than $17 billion each quarter.听

AI talent hubs

One area where Europe is seeing momentum is with frontier labs.

Employees from 鈥� the original AI lab established in London in 2010 and acquired by Google in 2014 鈥斕齢ave spawned two new labs in London: and . And , previously Meta AI鈥檚 lead, formed in Paris. Just this year, the three companies have altogether raised $2.6 billion.听

Last year, German-based AI lab raised hundreds of million in funding. One of the earlier model companies from Europe, , founded in 2023, has raised $4 billion in total.听

Europe is also home to one of the early diffusion model companies, . from Heidelberg, Germany, recently merged with Canada-based in April for sovereign and commercial AI deployments, valuing the merged entity at $20 billion, creating a transatlantic competitor to U.S. model companies.听

The recent spate of new AI lab formation and renewed momentum on the funding front could be a driver for talent hubs to concentrate in Europe. Still, although foundation labs in Europe have raised more than , that represents a tiny percentage of the amount raised by frontier model companies in the U.S.

AI-native

In the European report, found 81% early-stage companies, largely pre Series A, are AI-native 鈥� up from 50% a year ago. Leading by company count this year were 12 companies in dev tools and infrastructure and 11 companies in industrials and robotics.听

The advantages of building in Europe are 鈥渁ccess to strong engineers in the very beginning 鈥� having people that want to build and be part of a founding business, and access to good quality talent that you can retain,鈥� said , a principal at Notion Capital who co-wrote the report.听

He also noted that in earlier vintages, the trend was to 鈥渂uild a company, expand to the U.S. at some point around the Series B. Now, from the start, founders tend to think globally from day one.鈥�

The single most dramatic change, however, is how much leaner teams are ahead of the Series A, he said.

US bound

Despite the more recent pickup, European funding growth has lagged behind the U.S. since 2024.听

The leading San Francisco-based model companies 鈥� and 鈥� have raised $254 billion since 2023 and recentered the Bay Area post-pandemic as the place to be for ambitious founders.听

鈥淭he companies that start in the UK, France, Germany, and the Nordics, then come to Silicon Valley to grow,鈥� said , managing partner at , speaking on current market trends.听

鈥淵ou can build an amazing business anywhere in the world now. The barrier to building greatness has shrunk,鈥� said McLoughlin, who himself relocated to听 San Francisco from the UK in 2010. 鈥淏ut, the chances of building a generational company are so much higher, if you come to the Bay Area.鈥�

UK-founded incubator (EF) relocated to the U.S. in 2024. EF sources founders听 from leading universities around the globe to start companies but incorporates each business it funded in the U.S.听

鈥淭he Bay Area program is not just about proximity to capital,鈥� said , CEO and co-founder on announcing EF鈥檚 recent fund raise. 鈥淚t changes the ambition gradient. Founders move faster, think bigger and compete on a global stage from day one.鈥�

鈥淚’m seeing more than ever, companies that started in these emerging markets, and then going to the U.S. very early in their journey 鈥� not to sell themselves, but to sell to customers,” said , general partner at global investment firm . The firm invests on a global basis day zero at pre-seed, with its Elevate fund investing at later stages.听

鈥淭he time to copy a business is a month or two months, as opposed to years,鈥� said Abdel-Nour,听 鈥淵ou have an incentive to go and capture these big markets before your U.S. competition has really reached escape velocity,” he said.听

Related 兔子先生传媒 queries:

Illustration:

This is a weekly feature that runs down the week鈥檚 top 10 announced funding rounds in the U.S. Check out last week鈥檚 biggest funding deal roundup here.

Another week, another infusion of big AI rounds. For this past week, the largest fundraiser by a long shot was , a developer of AI customer experience tools that picked up $950 million. Other big rounds went to companies in sectors including satellite development, biotech, and, yes, more vertical AI and AI infrastructure.

1. , $950M, customer experience AI: Sierra, a provider of AI-driven tools for customer experience management, raised $950 million in fresh funding at a $15 billion valuation. and led the financing for the three-year-old, San Francisco-based company.

2.听, $455M, space tech: Astranis, a developer of advanced satellites for high orbits, secured $450 million in equity and debt investment. The financing included a $300 million Series E equity round led by and and up to $155 million in credit through .听

3.听, $250M, biotech: Natick, Massachusetts-based Anagram Therapeutics, a developer of a pill for people living with exocrine pancreatic insufficiency due to cystic fibrosis, pancreatic cancer and related disorders, closed on $250 million in new funding from .听

4.听, $200M, AI software development: Blitzy, developer of an autonomous software development platform, picked up $200 million in fresh funding at a $1.4 billion valuation. Northzone led the financing for the Cambridge, Massachusetts-based company.听听

5. , $160M, insurance: Corgi Insurance, provider of an AI-native insurance platform for startups, secured $160 million in Series B funding. led the financing, which set a $1.3 billion valuation for the San Francisco-based company.听

6. , $140M, renewable energy: Portland, Oregon-based Panthalassa, which aims to perform AI inference computing at sea using power generated from ocean waves, raised $140 million in a Series B financing led by .

7. , $125M, insurance: Reserv, a provider of third-party administrator services to the insurance industry, closed on $125 million in a Series C funding round led by . Launched in 2022, New York-based Reserv has raised over $200 million in known funding to date, per 兔子先生传媒 data.

8.听, $107M, AI infrastructure: DeepInfra, a cloud platform for high-throughput AI inference, landed $107 million in Series B funding. and led the financing for the four-year-old, Palo Alto, California-based company.

9. , $60M, vertical AI: San Jose, California-based Tessera Labs, developer of an AI platform for enterprise ERP systems and data, secured $60 million in a funding round led by .听

10. , $56M, gaming: Astrocade, developer of an AI platform for creating, building and playing games, announced $56 million in new funding. The funding for the Los Altos, California-based company includes a Series B led by and a Series A led by , Astrocade said.听

Illustration:

With that in mind, its venture arm, , is backing startups that build the financial and technical infrastructure for a more autonomous economy.听

兔子先生传媒 News recently conducted an email interview with , managing director of , about the firm鈥檚 investment thesis, the kinds of startups it aims to back, and how it works with founders to build and scale projects in the American Express ecosystem.听

Amex Ventures鈥� recent investments reflect its focus on an autonomous future. In April, it led a round into business identity infrastructure platform and also wrote a check into , an agentic marketing platform that raised a $43 million Series B. It also backed Candex, a startup that uses AI and aims to help large companies pay small, one-time, or irregular vendors without the administrative headache or risk that comes with onboarding them.听

Since joining Amex 15 years ago, Tsang has been responsible for identifying and executing strategic investments in early- to growth-stage startups that fit the American Express thesis. He also leads the firm鈥檚 consumer services investment vertical, focusing on the future of membership, and oversees the firm鈥檚 global portfolio management operations.

Before joining American Express, he was part of the diversified industrials investment banking group at , where he focused on M&A and corporate finance transactions.

The interview has been edited for brevity and clarity.

兔子先生传媒 News: In the 鈥�2025 GenAI era,鈥� we focused on tools that inform decisions. Now that we鈥檙e in the ‘2026 Agentic era,’ where agents execute transactions, how has the bar shifted for founders pitching Amex Ventures? Are you prioritizing the AI model or the trust/identity layer that will allow an agent to use a Platinum card autonomously?

Tsang: The bar for Amex Ventures investment has shifted toward agentic commerce systems that can navigate complexity and help facilitate end-to-end workflows for customers, with appropriate user authorization and controls. The most compelling founders operate companies that can handle much more of the full commerce journey, not just surfacing options, but incorporating context, executing user decisions, and ultimately completing tasks, with personalization increasingly becoming a key differentiator in how those experiences are delivered and retained.

Agentic commerce systems are sometimes framed too narrowly as just the final execution step, but the real opportunity 鈥� and where we are seeing the most innovation 鈥� is in systems that can understand preferences, constraints, and intent, and then orchestrate a complete experience that properly reflects them.听

Over time, this could evolve to support more comprehensive experiences, such as planning entire trips rather than just recommending a flight, or managing a series of related actions instead of a single step. AI also has the potential to help scale the kind of high-touch, tailored experiences that were once reserved for a small set of customers to a much broader base.

From our perspective, we are less focused on any single layer, whether that is the underlying model or the trust and identity infrastructure, and more focused on how these components come together to deliver a seamless and high-quality customer experience.听

Trust and security are foundational, especially in financial services. Ultimately, we are looking for founders who are building with the ambition and technical depth to address real-world complexity, while delivering meaningful outcomes for customers with a focus on security and compliance.听

Many founders struggle with the 鈥淐VC paradox鈥� 鈥� getting a pilot with Amex is a huge win, but scaling it globally can take years. What is the most effective way a founder can leverage your firm to move from a localized experiment to a core membership benefit?

We see the most successful commercial partnerships follow a crawl, walk, run model 鈥� starting with a focused pilot, learning quickly, and then building toward broader integration and scale.

Our investment model creates shared incentives to build commercial partnerships that benefit both American Express and our portfolio companies, and we help advance these relationships over time. We look for founders who continue to iterate and innovate so that the scope of these partnerships can expand in a meaningful and sustainable way.

For example, we recently invested in the startup , an agentic marketing platform that helps enterprises understand, influence, and measure how brands are represented across AI-powered channels. At American Express, we are utilizing Bluefish鈥檚 technology to support our agentic search efforts, including our Answer Engine Optimization (AEO) strategy.

For travel and dining startups, customer acquisition cost (CAC) is skyrocketing due to influencer-driven marketing. How much does a startup鈥檚 ability to plug into the Amex 鈥榗losed-loop鈥� ecosystem factor into your valuation, versus their organic growth?

When we evaluate companies, we start with the fundamentals. We are looking for businesses that can stand on their own, with strong products, clear value propositions, and sustainable growth models. That is core to any investment decision we make.

At the same time, one of the advantages of an investment from Amex Ventures is the potential to partner with American Express and engage with our ecosystem, which we see as a meaningful opportunity for many companies. When there is a clear path to creating mutual value through a commercial partnership, it can strengthen our conviction to invest.

That said, we do not invest simply because a company is likely to have a commercial relationship with American Express. To invest, we must believe in the underlying business on its own merits.听 The potential for an American Express partnership represents additional upside and an opportunity to accelerate the company’s growth together.

With tech M&A volumes up significantly this year, are you managing the current portfolio with an eye toward strategic buyouts by Amex鈥檚 parent company, or are you pushing for independent IPO-ready unit economics given the partially reopened window?

We are not managing the portfolio with a specific exit outcome in mind. Our focus is on investing in companies that can build strong, durable businesses and on creating strategic relationships with our portfolio companies that drive value on both sides.

In many cases, that means working closely with our portfolio companies to explore potential commercial relationships with American Express, which is core to our role as a corporate venture investor. In fact, nearly two-thirds of our portfolio companies have had a commercial relationship with American Express.

From there, a company鈥檚 path, whether toward an IPO or M&A, is ultimately driven by the founder and the broader investor group. Our role is not to steer that outcome, but to support the company in building long-term value and maintaining the flexibility to pursue the right exit opportunity.

When you look at the current 鈥渟ervice-as-software鈥� startups, do you see them as long-term standalone companies, or are we looking at a massive consolidation cycle where travel/dining tech eventually gets absorbed back into the major financial rails?

There are a number of ways this could play out, and it will likely vary by industry. In some sectors, particularly those with high levels of specialization or unique requirements such as regulation, there is a clearer path for companies to build durable, standalone businesses that deliver meaningful value over the long term.

At the same time, we are starting to see early signals that consolidation could emerge in certain areas, particularly at more horizontal layers of the AI stack, where capabilities can extend naturally across multiple use cases. It is still early, though, and the boundaries of how far that consolidation will go are being defined.

In lifestyle categories like travel and dining, I believe the outcome will be a mix. For example, in travel, there is already a range of booking options available to consumers. While there has been some consolidation amongst these companies, many have continued to find ways to differentiate and add value.听

We expect a similar dynamic to continue, with some companies scaling independently while others partner more deeply or join broader platforms over time.

Related 兔子先生传媒 query:

• 听

Illustration:

Starting a company has never cost less. A founder with the right AI tools can ship a working product in a weekend, stand up a website in an afternoon, and fill out an accelerator application before lunch. But that speed hasn鈥檛 made it easier to get funded.听

Fewer seed-funded startups are graduating to Series A than just a few years ago, and startup funding has been in a downturn so far in 2026. Investors are concentrating capital in fewer, stronger bets. The question is what “stronger” means now.

Every generation of technology resets what investors should expect from founders. Twenty years ago, a founder who wasn鈥檛 internet-native was at a structural disadvantage. Forty years ago, it was computer literacy. Today, AI-native fluency is the baseline 鈥� the ability to build, test, and iterate using AI copilots, APIs, and low-code tools at a speed that would have required a full engineering team just a few years ago.听

Founders who haven鈥檛 embraced these tools in their daily operations aren鈥檛 even at the table. They鈥檙e new-aged dinosaurs. Technical expertise still matters, but when everyone can build, thanks to AI, it no longer differentiates. And that forces a harder question for investors: If the product isn鈥檛 the moat, what is?

Finding the fit

The answer is founder-market fit. Investors are shifting their attention from what a team can build to whether the founder has domain expertise that predates the startup, has done real customer discovery, and can articulate a path to market that competitors can鈥檛 easily replicate.

AI can help a founder build anything, but it鈥檚 what customers have a need for that tells them what鈥檚 worth building. That judgment is steeped in industry knowledge, customer relationships, and a clear-eyed view of what people will actually pay for. That is the scarce resource these days.

That鈥檚 not to say AI can鈥檛 help build a company the right way. It has implications for how early teams should be composed., the average seed-stage company last year had just over six employees, down from more than 10 in 2021.听

With teams that lean, every hire has to pull disproportionate weight. The highest-leverage early additions are a product-minded builder who can ship fast with AI tools, someone who owns the customer relationship and drives early revenue, and someone who can position the product and generate demand. A bench of engineers no longer tops the list.

The investor鈥檚 harder job

Knowing what to look for is one thing. Finding it is another, because AI has made it easier to fake the signals investors rely on.听

There鈥檚 an entrepreneurial equivalent to the that so many people are talking about. Instead of a tidal wave of empty marketing copy about 鈥渆ver-evolving landscapes,鈥� there鈥檚 startup slop that creates a serious evaluation problem for investors. Dealflow volume has become a vanity metric. There鈥檚 a surge of submissions that are pure noise, especially from software startups that can fabricate credibility in a single afternoon.

Deep tech is harder to fake. Building a therapeutics company still requires real science, real key opinion leaders, and real partnerships. The same is true for hardware and advanced manufacturing. There鈥檚 an actual moat in those sectors, which may help explain why investor interest in deep tech has been growing steadily.听

Investors can weed out the startup slop by asking more specific questions. For instance, our accelerator, AlphaLab, is based in Pittsburgh, and we always ask founders why this city is the right place for them to grow their businesses. You can sense how genuine someone is based on their answer. Same goes for asking about the customer discovery process. Even more telling is why someone started their company in the first place, whether the answer reflects real conviction or a market opportunity they read about.听

AI can鈥檛 manufacture what investors are really looking for. The signals that matter most at the early stage are coachability, hustle, and genuine conviction. There are details in an application that suggest someone has actually lived the problem they鈥檙e solving. Investors don鈥檛 want to write a check to someone who has vibe-coded a company they aren鈥檛 passionate about, and the tells are easier to spot than founders think.听

However, AI has reallocated where founders should spend their energy. Because it can help with some of the technical aspects of creating a company, founders should devote more effort to refining their strategy through higher-order skills like judgment, creativity, storytelling, and relationship-building. Speed of communication has become a revealing signal. There is no longer any excuse for taking four days to respond to an email, skipping a weekly investor update, or failing to follow up after a meeting. AI has eliminated the friction in all of those tasks. A founder who is still slow is telling investors something about how they鈥檒l run a company, and investors are paying attention to those soft interactions more than ever.

While the cost of building companies has dropped, the burden of earning investment has risen. And for investors, the evaluation itself has gotten harder, with more noise, more polish, and fewer of the old signals to rely on. The founders worth funding will stand out the same way they always have: by knowing something the rest of the market doesn鈥檛.

听brings 20 years of experience in venture capital, accelerator leadership and strategic operations to his role as director of accelerator programs at听听in Pittsburgh. He oversees听, AlphaLab Gear, AlphaLab Health and Robotics Factory Accelerate, programs that support early-stage startups with mentorship, resources and capital. His leadership has helped create a connected AlphaLab ecosystem that empowers founders across industries and stages of growth. Earlier in his career, Tainter held roles at听听and听听where he led cross-functional initiatives and evaluated early-stage investments. He also teaches at听, where his work focuses on funding entrepreneurial ventures.

Illustration:

Related reading:

• The Right Way To Pitch VCs And Accelerators (And Why Most Founders Get It Wrong)