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.

Venture funding has always been a world of haves and have nots. And these days, the haves are having more than ever. Case in point this week was . The 5-year-old generative AI giant secured $65 billion in Series H funding this week, pushing its post-money valuation to a mind-blowing $965 billion.

After that, the next-biggest financing was a $1 billion round for AI software development tool maker , lifting its valuation to $26 billion. Companies in a range of other sectors also managed to secure sizable though smaller rounds, in areas including commerce logistics, developer AI, insurtech, fusion and more.

1. , $65B, foundational AI: Generative AI company Anthropic raised $65 billion in a Series H funding round, more than doubling its post-money valuation to a staggering $965 billion. San Francisco-based Anthropic said , , and led the financing, and that , , , , and co-led the investment.

2. , $1B, AI software development: Cognition, developer of AI software engineer Devin, has closed on over $1 billion at a $26 billion valuation. , , and 1聽led the financing for the San Francisco-based company.

3. , $250M, logistics: Atlanta-based Stord, developer of a fulfillment network, software and AI tools for independent brands, secured $250 million in Series F funding. The round set a $3 billion valuation for the 11-year-old company.

4. , $113M, AI for developers: OpenRouter, a marketplace for AI models, secured $113 million in Series B funding. led the financing for the New York-based startup.

5. , $106M, insurtech: San Francisco-based Corgi Insurance, developer of an AI-native insurance platform for startups, picked up $106 million in Series B1 funding led by . The financing, which set a $2.6 billion valuation, comes just three weeks after Corgi $160 million in Series B funding at a $1.3 billion valuation.

6. (tied) , $100M, fusion energy: Kearny, New Jersey-based Thea Energy, a developer of technology for fusion energy systems, raised $100 million in Series B funding led by . Thea says the funding will go toward manufacturing infrastructure.

6. (tied) , $100M, healthcare data: Garner Health, a platform for finding healthcare providers, closed on $100 million in Series E funding led by . The financing set a $2.74 billion for the New York-based company.

8. , $90M, space tech: Observable Space, a space tech startup that develops and builds advanced optical systems, says it raised $90 million in Series A funding led by to scale manufacturing and develop its technology. The Santa Monica, California-based company also announced that it secured a $94 million contract with the.

9. , $59M, AI video: Reactor, a San Francisco-based developer platform for real-time generative video, emerged from stealth with $59 million in funding led by .

10. , $52M, cancer detection: San Diego-based ClearNote Health, a developer of early detection and monitoring tests for multiple forms of cancer, picked up $52 million in Series D financing. Founding investor led the round.

Methodology

We tracked the largest announced rounds in the SA国际传媒 database that were raised by U.S.-based companies for the period of May 23-29. Although most announced rounds are represented in the database, there could be a small time lag as some rounds are reported late in the week.

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The global innovation economy remains largely defined by agglomeration dynamics. Worldwide, 19 ecosystems dominate the innovation landscape, increasingly concentrating innovation demand (corporates) and supply (scaleups) 鈥� attracting further growth capital (investors).

Meanwhile, other ecosystems struggle to achieve a meaningful presence on the global innovation map and are at serious risk of technological disruption and economic downfall.

Yet something is happening below the surface. Over the past decade, the composition of the Global Innovation Ecosystems Life Cycle Curve changed dramatically, as the number of scaleup ecosystems worldwide has more than doubled.

The trend is not stopping just here: we expect these figures to even triple in the coming years.

In this new scenario, emerging innovation economies hold the potential for disrupting the agglomeration paradigm, toward a new scheme of interconnected networks of specialized local innovation hot spots.

Among them, there is also Africa. While the continent still lacks ecosystems at the most advanced stages of maturity, it now counts four ecosystems at the startup stage and 40 at the standup stage, compared with respectively 25 of those 10 years ago, according to by my organization, , in collaboration with and .

Africa: the awakening giant of the coming decade?

As of today, Africa鈥檚 innovation economy includes 883 tech scaleups that have raised a combined $24.7 billion. Despite this progress, the continent still represents only about 1% of global figures.

The African innovation landscape remains highly concentrated around four main hubs: South Africa, Egypt (North-East), Nigeria (West Africa) and Kenya (East Africa). The North-Western corner of the continent still lacks a dominant hub, although Tunisia, Morocco and Algeria remain the leading candidates.

A testbed for clean technologies?

Emerging innovation economies that thrive on the global innovation map typically build on top of highly specialized, unique local strengths.

Our recent analysis has identified clear evidence that Africa holds significant potential over the development of clean energy systems and technologies.

The relative prominence of the cleantech sector in Africa is evident from the data:

• Africa is home to 95 cleantech scaleups, representing roughly 11% of the total scaleup base.
• Collectively, they have attracted approximately one-fifth of all capital deployed to African ventures.
• Cleantech has also generated a disproportionate share of high-growth leaders, accounting for around 20% of both scalers (scaleups that raised more than $100 million) and super scalers ($1 billion-plus).

Within cleantech, a highly specialized vertical is also emerging, what we might call 鈥済ridtech鈥�:

• It comprises 16 scaleups (17% of the cleantech total) and two scalers (25% of total).
• It has attracted around 30% of total cleantech funding.
• Africa鈥檚 sole cleantech tech giant, Kenya-based , operates within this gridtech vertical.

That said, the numbers still point to a gap.

The elephant in the room

The main challenge is the grid infrastructure deficit, which remains the primary bottleneck to scaling energy system technologies. As shown in the map below, Africa鈥檚 grid infrastructure is highly fragmented: High-voltage networks are concentrated in a few densely populated areas, while large parts of the continent remain largely disconnected.

As a result, grid infrastructure development and electrification are key to unlocking Africa鈥檚 growth 鈥� consider that Africa still accounts for only about 5% of global energy supply 鈥� and its innovation potential.

At the same time, the continent holds world-class renewable resources, including approximately 13% of global technical hydropower potential and around 60% of the world鈥檚 best solar resources.

Africa鈥檚 energy system is expanding, but fully unlocking its economic and innovation potential will depend on accelerating electrification and strengthening grid infrastructure.

Blended finance will be critical to enable this growth. Both private and public capital are required: private capital drives innovation, while public finance enables foundational infrastructure such as grid expansion.

In particular, private capital needs to be complemented by structured public finance initiatives to address the inherent limitations of a relatively small domestic VC market, which remains heavily focused on early-stage investments.

Public capital will be essential for infrastructure development. In gridtech especially, public investors are expected to account for up to about 80% of total investments by 2030, reflecting the capital intensity and risk profile of grid infrastructure.

International capital still dominates the market, with approximately 69% of active investors originating outside Africa, underscoring continued reliance on foreign capital despite growing local participation.

Get the full story in our report:

is chairman of and a professor at . He is a serial entrepreneur who has started three startups in his career, the last of which is , among the five Italian scaleups that have raised the largest amount of capital. He is recognized among the leading international experts in open innovation and has wide experience in setting up and managing open innovation projects 鈥� venture clients, venture builders, intrapreneurship, CVCs 鈥� with large multinational companies, as well as advising and training on this subject. Onetti has a column on () and several other tech blogs.

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At least not these days. The space and AI pioneer posted a net loss of $4.28 billion in the first quarter of 2026, up more than 700% from a year ago. Revenue, meanwhile, totaled $4.69 billion in Q1, up 15% from a year ago.

As a public company, SpaceX is reportedly seeking a valuation of around $1.5 trillion or more, . It鈥檚 aiming to raise up to $80 billion or more in the offering, which would make it the largest IPO in history.

At its target valuation, SpaceX would join a rarified club of just seven U.S. public technology companies with market caps of $1.5 trillion or more. Of those, just five have crossed the $2 trillion mark.

Of course, those companies took time to grow into their 13-digit valuations. But at some point, they too made their first public IPO filings. And they too had revenue.

The similarities end there. For a sense of how SpaceX compares at IPO time to other members of the trillion-plus-club, we took a look at their original S-1s from the 1980s and onward. Here鈥檚 what their numbers looked like just before their public market debuts:

: Today, the Silicon Valley chip designer is a $5.3 trillion market cap company. Anyone who invested in its 1999 IPO, needless to say, has done extraordinarily well.

At the time of its market debut, of course, such a trajectory was not obvious. Still, it looked like a solid bet. The company, which then focused on designing 3D graphics processors for the PC market, had $93 million in revenue for the three reported quarters prior to its IPO, growing severalfold year over year. Over the same period, it posted a modest $3.5 million loss.

: Google was already the dominant player in online search when it went public in 2004, with impressive financials to boot. Revenue for the first half of that year totaled $1.35 billion, more than doubling in a year, paired with a $326 million profit.

While that was impressive, so is Google鈥檚 ongoing growth. Currently, its market cap is $4.7 trillion and it posts more than $400 billion in annual revenue, with massive profits as well.

: The iconic smartphone and computing giant knows a thing or two about longevity. Apple turned 50 last month, and it went public over 45 years ago, in 1980.

It was an impressive and attention-getting offering for the time, with $118 million in sales and nearly $12 million in profit. It helped that Apple was already a prominent consumer brand at the time due to its popular home computers. These days, its market cap hovers around $4.5 trillion.

: Microsoft went public in 1986, so it鈥檚 had some 40 years to grow into its current $3.1 trillion valuation. But even back in the era of big hair and floppy disks, the software giant鈥檚 IPO prospectus showed clear signs this would be no ordinary market entrant.

In the year before its IPO, Microsoft had revenue of $140 million and net income of $24 million. That income figure, however, includes stepped-up spending on marketing and R&D. Without those expenses, profit margins looked astoundingly high for a time before software business models were status quo.

: At the time of its public offering in 1997, Amazon was known as an online bookseller, branding itself as “Earth’s Biggest Bookstore.” All the other stuff came later.

Still, it was a compelling offering at the time, with Amazon growing annual sales from zilch to around $16 million in just two-and-half years after its inception. It pitched losses as part of its growth strategy, which called for investing heavily in marketing and promotion, site development and operating infrastructure.

Needless to say, things worked out well, with Amazon currently valued at more than $2.8 trillion.

SpaceX is not like the others

If we look at the most valuable public tech companies, a few commonalities about their earlier days stand out. All went public relatively early in their operating histories and debuted with sharply growing revenue and either profits or losses in the single-digit millions.

SpaceX, founded in 2002, looks by comparison like an oldster for a company on the cusp of a public market debut. It鈥檚 also worth pointing out that Google, founded in 1998, is only four years older than SpaceX. That means, it鈥檚 had 28 years to grow into becoming a company with over $400 billion in revenue over the past 12 months and $138 billion in operating income.

SpaceX, by contrast, has had 24 years to grow into becoming a company that loses $4.3 billion in a single quarter.

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• The IPO Pipeline Finally Gets Interesting
• PwC鈥檚 US IPO Lead On The 2026 Outlook, IPO Timing And The Secondary Boom
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We鈥檙e not talking about confidential filings either. Sure, they signal serious intent and contain valuable information for regulators. But for the rest of us, it鈥檚 the public S-1 filing that signifies an IPO is actually imminent.

By this latter measure, the past few weeks have been pretty busy for venture-backed startups. , the designer of speedy AI inference chips, filed publicly last week for an offering expected to raise around $2 billion. The Silicon Valley company, which withdrew plans for an IPO last fall, is reportedly seeking a valuation upwards of $35 billion this time around.

That alone would be enough to set IPO market watchers abuzz. Per SA国际传媒 data, it stands to be the largest initial share offering of a U.S. semiconductor company to date.

However, Cerebras wasn鈥檛 the only venture-backed company seeking a multibillion-dollar IPO valuation.

Power players

Another, albeit smaller, contender is nuclear power startup , which is making its debut today. The Rockville, Maryland-based company priced shares at $23 each late Thursday, above the projected range, raising around $1 billion. Shares closed up 27% in first-day trading Friday.

Meanwhile, on the geothermal power front, is also looking to take its clean energy ambitions to the public market. The Houston-based company filed last week for a offering that could bring in around $250 million.

Biotech IPOs heating up

Biotech is also heating up. Last week delivered a big debut from , a Waltham, Massachusetts-based developer of oral and injectable treatments for obesity and metabolic disease that $718 million in its Nasdaq offering. , a Fremont, California-based startup applying proteomics to early disease detection, made its market entry as well, securing a current market cap around $1.6 billion.

More biotech debuts are on deck too. Austin-based , a venture-backed developer of a nerve stimulation device for stroke survivors, filed last week for an offering. The prior week brought S-1 filings from Boston鈥檚 , a developer of medicines for depression, anxiety and other neuropsychiatric disorders, and , a Denmark-based biotech which focuses on treatment of blood coagulation disorders.

Space and defense on the rise

Of course, everyone knows the Texas-based company on deck to publicly file for a space tech offering of unprecedented magnitude. for an IPO a few weeks ago, with media reports pegging its target valuation around $1.75 trillion. If the company forges ahead with reported plans for a June market debut, a public filing should follow in the next few weeks.

In the interim, another, much, much smaller offering in the defense tech space is on track to hit the market much sooner. , a Herndon, Virginia-based developer of radio frequency intelligence for military customers, filed earlier this month for a offering. It comes amid a period of heightened investor appetite for defense tech, with an expectation of more debuts in the space likely in coming months.

Now we just need some software

Of course, it鈥檚 not an IPO market that is welcoming to all venture-backed startup sectors. One area noticeably absent from the impending offering list is enterprise software. While SaaS has long been a mainstay of the IPO pipeline, the sector has taken a hit of late amid investors’ concerns of AI disruption.

That said, it鈥檚 still encouraging to see a swathe of other sectors dipping a toe in IPO waters.

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Look closer, and the story changes completely. Early-stage funding was up 41% year over year. AI/ML deal count , up from roughly 5,600 the year before. More companies are getting funded at the early stage, not fewer.聽 The concentration at the top? That’s an infrastructure play. The application layer looks entirely different.

Build vertical, not horizontal

The real signal is in the shift from horizontal to vertical. shows horizontal SaaS down 35% over the past 12 months while vertical SaaS is essentially flat (up 3%). That divergence matters for founders deciding what to build.

Horizontal software (project management, general productivity, collaboration) is commoditizing fast as AI agents handle coordination natively. But vertical software? That鈥檚 where proprietary data shines and industry-specific compliance workflows matter. AI makes the first category less valuable and the second category more valuable.

If you’re starting a company right now, the data says: Pick an industry, not a feature. Claims processing in insurance, scheduling in healthcare, compliance in financial services, job costing in construction. These are workflows where software penetration has been shallow for decades because the problems were too specific for horizontal tools. AI changes that math.

Build for the $6T, not the $500B

The addressable market for software is expanding, not contracting. In Redpoint’s CIO survey, 58% cite AI as the top driver of increased software spend. As agents move from copilot features into autonomous workflow execution, the addressable market grows from roughly $0.5 trillion in current U.S. enterprise software spend toward $6 trillion or more, because AI starts capturing portions of the knowledge-worker payroll that software never could.

This is classic : When a resource gets dramatically cheaper to produce, consumption goes up. AI makes software dramatically cheaper to build, deploy and maintain. Suddenly, job costing for midsize contractors pencils out. Inventory optimization for independent pharmacies becomes economically viable. The cottage industries that enterprise software ignored for decades? They’re all in play now.

Build for acquirability, not just IPO optionality

But let’s talk about exits, because that’s where the rubber meets the road. The IPO market remains largely closed. In 2025, roughly 2,300 VC-backed startups were acquired compared to just 65 IPOs, per SA国际传媒 data.

LPs have seen nearly $200 billion in cumulative negative net cash flows since 2022. The pressure to return capital through M&A is real and growing.

Smart founders are building for this reality from day one. They鈥檙e building products that integrate into existing enterprise stacks, accumulating proprietary data that makes them expensive to replicate and cheap to integrate. Strategic acquirers in insurance, healthcare, logistics and financial services are actively buying vertical software companies. Why? Because these buyers can’t build this stuff internally 鈥� they lack the talent, the focus, and frankly, the DNA.

Start with the workflow, not the technology

So while everyone’s mesmerized by the infrastructure megarounds, the real opportunity is staring us in the face. Pick a specific industry workflow that’s still manual or stitched together with Excel. Build the AI-native solution that actually works for that vertical. Get to revenue before the market catches up.

The record quarter and the shrinking fund base are telling the same story from different angles. Infrastructure capital is concentrating at the top while the application layer is wide open for those willing to roll up their sleeves and solve real problems for real industries. That’s where I’m putting capital, and that’s where smart founders should focus their energy.

As the co-founder and managing partner of , is committed to establishing MGV as the premier venture firm for world-class tech entrepreneurs to accelerate their visions. Under Schr枚der鈥檚 stewardship, MGV has swiftly ascended to a top-quartile firm, surpassing the performance of 95% of venture funds. The performance of MGV is driven by Schr枚der鈥檚 unique approach to venture investing 鈥� that providing intensive sales training, devising robust fundraising strategies and securing follow-on investments is the best way to support founders and drive the deepest return for investors. has recognized him as one of the Top 100 global seed investors, and his perspectives are published regularly in SA国际传媒 News and other leading publications.

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led the financing, which included participation from , , and . It brings Boulder, Colorado-based Schematic鈥檚 total funding since its 2023 inception to $12 million.

Schematic builds entitlements and enforcement infrastructure for SaaS and AI companies. Put more simply, it serves as a digital gatekeeper for software and AI companies. For example, if a company鈥檚 sales team wants to give a major client a special discount or extra storage, they have to ask an engineer to go in and 鈥渕ove the walls.鈥� The process can be slow, expensive and tedious.

That鈥檚 where Schematic comes in. It essentially acts like a universal remote control for a company鈥檚 features.

Instead of burying those rules in the code, a company can plug Schematic into its product. Then, if it, for example, wants to launch a new “AI Tier” or change how many users a client can have, a person in marketing or sales can flip a switch in a simple dashboard.

鈥淲hen a software company sells you a plan, something inside their product has to enforce what you can do and access based on what you paid for,鈥� said CEO and co-founder . 鈥淢ost companies build that enforcement infra themselves, often badly, and it becomes the thing that slows down every future monetization change. Schematic is the infrastructure that handles it, so engineering doesn’t have to.鈥�

In addition to the fundraise, Schematic is also announcing that payment giant has tapped it 鈥渢o solve entitlements as a first-class primitive: decoupled from code, enforced at runtime, on top of Stripe Billing.鈥�

Schematic will be launching its new Stripe app publicly on stage next week at Stripe Sessions.

Systems like Stripe currently handle the money, sending invoices and charging credit cards. But Stripe doesn’t actually sit inside the app to block or allow a user from clicking a button. Schematic claims it will now serve as the “muscle” that actually enforces the rules that a platform like Stripe sets.

鈥楢n emergent crisis鈥�

By using Schematic, Glover said that companies like went from taking weeks to change their pricing to just 10 minutes. The startup鈥檚 other customers include , and .

AI has made entitlements an emergent crisis, in Glover鈥檚 view.

鈥淣either underlying costs nor customer value are predictable, and both accrue at runtime,鈥� he told SA国际传媒 News. 鈥淭his is why we describe what we’re building as runtime monetization infrastructure: Value is now accruing nondeterministically at runtime, and as a result, pricing and packaging have to be enforced at runtime. A shadow enforcement system catching webhooks from a billing platform cannot support this inflection.鈥�

, general partner at S3 Ventures, said his firm was drawn to invest in Schematic for a few reasons.

鈥淎s operators and through our portfolio companies, we’ve seen firsthand how often pricing changes get delayed or deprioritized because entitlement logic is buried in application code. On top of that, AI is accelerating a structural shift away from seat-based pricing; hybrid and consumption-based models now represent 38% of SaaS companies and that number is rising as companies hone their AI pricing strategies, putting real pressure on legacy monetization architectures,鈥� he wrote via email. 鈥淔inally, Fynn, Ben, and Gio have worked together for nearly a decade, and each of them encountered this specific problem while running pricing and packaging at growth-stage SaaS companies.鈥�

Fintech startups have benefited from increased investment in recent quarters. Total global funding to VC-backed financial technology startups totaled $53.8 billion in 2025, per SA国际传媒 . That鈥檚 a more than 29% increase from 2024鈥檚 total of $41.6 billion raised.

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His company raised a few million in seed, and lifted the curtain, and 鈥� crickets. Nothing happened. Businesses didn鈥檛 sign up. My friend was confused while prospective clients hesitated. This simply didn鈥檛 sit well with them.

Then the founder decided to do something odd. He charged money on top of the original monetization plan. Same product, same value proposition, but now there is a monthly subscription. Almost overnight, new businesses began signing up.

Today, that startup is worth billions.

This highlights a counterintuitive truth in strategy: In real-world markets, free or lower prices don’t always drive demand. Frequently, they achieve the opposite.

Higher prices amplify perceived value

The price-quality heuristic is a cornerstone of behavioral economics. When buyers lack complete transparency, they use price as a shortcut for quality. This is why identical items, from fine wines to electronics, are rated higher when they cost more. In B2B, this effect is amplified: A cybersecurity solution priced far below the market doesn’t look like a bargain; it looks like a risk.

Pricing dictates customer behavior and expectations

Low entry points tend to attract price-sensitive users who optimize for cost over outcomes. These cohorts are often more prone to churn and demand excessive support. Conversely, premium pricing attracts partners who value reliability and performance. Opting for higher pricing means going after clients with a different mindset. Even in strategic advisory, I see premium pricing as a filter for commitment.

Your price defines your competitive landscape

Pricing at the bottom floor frames the company within a commoditized segment where differentiation is minimal. Pricing at a premium forces a higher standard of depth, service and trust. Price defines who you are competing against and how you will be compared to them.

is a strategic adviser to tech companies and investors, specializing in strategy, growth and M&A, a guest contributor to SA国际传媒 News, and a seasoned lecturer. Learn more about his advisory services, lectures and courses at . for further insights and discussions.

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鈥淚 recognized both the massive potential AI brought to the tax world, as well as the risks to firms and clients by making mistakes and hallucinations,鈥� he told SA国际传媒 News.

The accounting industry has historically been slow to adopt new technologies. As of today, the majority of small to mid-sized accounting firms 鈥� which make up 90% of the market 鈥� remain stuck in a cycle of manual data entry.

Addressing both the opportunities 鈥� and risks 鈥� that came with advances in AI, Haase started building , a tax prep automation startup, on the side in 2023. Rather than targeting the self-prep market, like does, or the mega-enterprise firms that can afford $15,000-per-return software, Juno was built for the underserved SMB accounting firm.

鈥淲e continuously 鈥榙og fed鈥� the early Juno prototypes into the firm to see what worked best, what slowed things down, and to make it the most efficient tax preparation platform as possible,鈥� Haase said.

It took about a year and a half just to build integrations. 鈥淲e had to do a bunch of hacky things to be able to work with the existing tax software,鈥� he explained, 鈥渂ecause your typical tax software is actually around 15 to 20 years old and they don鈥檛 have public APIs.鈥�

By 2024, Juno had launched a co-pilot. Then, in July 2025, it had a tax product. The startup began onboarding other tax firms, growing to nearly 500 customers over the past year. Last year, Haase sold his accounting firm to focus on growing Juno full-time.

Today, he鈥檚 announcing that San Diego-based Juno has raised $12 million in a seed funding round led by , including participation from and .

AI to help humans 鈥榖e the advisers they were trained to be鈥�

What makes Juno different from others in the market, Haase believes, is that it operates on the premise that, at least for the foreseeable future, human tax preparers should be the ones driving the tax-return preparation process.

鈥淎 business or high-net-worth tax return requires hundreds of calculations, edge cases, deductions and more,鈥� said Haase, who holds an MBA from . 鈥淎I simply can鈥檛 do that with the 100% accuracy required not to get audited or charged with tax fraud.鈥�

Describing much of the manual work that most accountants must perform to complete returns as extremely tedious, Haase acknowledges that it鈥檚 also very easy for accountants to make mistakes that could prove very costly.

鈥淚n school, if you get a 93, an A, you get all the credits,鈥� he said. 鈥淏ut on a tax return, if you have a 99%, you fail, and your client could pay the price in penalties.鈥�

In a nutshell, Juno acts as the bridge between a client鈥檚 raw documents and the accountant鈥檚 filing software. It performs tasks like pulling data from IRS forms and even unstructured documents, such as business financial statements. Overall, it automates 90% of data entry across more than 90 document types while also flagging prior-year changes and inconsistencies for human validation.

The result is that a process that typically takes a human two to three hours is shrunk down to seven to 10 minutes, Haase estimates.

鈥淲e do 95% of a tax return in minutes, leaving the accountant to handle the strategic human decisions 鈥� the parts that actually save the client money,鈥� he said.

While he declined to reveal hard revenue figures, Haase said that in just eight months, Juno grew to mid-seven-figure annual recurring revenue.

The startup sells on a per-return basis, starting around $45, dropping to the low $30s for high-volume firms.

‘s recent move into consumer taxes and OpenAI’s hiring of a tax director show that the bigger players are eyeing the tax market. But Haase doesn鈥檛 feel threatened.

鈥淗igh-wealth individuals want assurance. If you鈥檙e paying $40,000 in taxes, you don’t want to 鈥榗ross your fingers with a chatbot,鈥� he said. 鈥淵ou want a human to talk to, someone who understands the context of your life.鈥�

Juno isn’t trying to replace accountants, he added.

鈥淚t’s trying to rescue them from the data-entry basement so they can actually be the advisers they were trained to be,鈥� Haase said.

The startup plans to roll out business returns soon, a move that Haase expects will significantly scale its customer base.

鈥楢 huge, obvious pain point鈥�

, co-founder and managing director of Bonfire Ventures, said he was drawn to invest in Juno because he believes the company is going after 鈥渁 huge, obvious pain point in a category that hasn鈥檛 been meaningfully modernized in a long time.鈥�

鈥淭he workflow pain is real, the labor dynamics make the timing right, and Dave brought exactly the kind of founder-market fit you hope to see,鈥� Andelman told SA国际传媒 News via email. 鈥淗e lived this problem before he built the company. That always matters.鈥�

The investor believes that tax prep is a category where trust is crucial to product success.

鈥淚f you鈥檙e going to bring AI into that workflow, it has to be transparent, auditable, and built with a human in the loop,鈥� Andelman added. 鈥淭hat鈥檚 what Juno understood early, and I think that鈥檚 a big part of why the product is resonating.鈥�

Fintech startups, particularly those that apply AI to traditionally manual or burdensome processes, have benefited from increased investment in recent quarters. Total global funding to VC-backed financial technology startups totaled $53.8 billion in 2025, per SA国际传媒 . That鈥檚 a more than 29% increase from 2024鈥檚 total of $41.6 billion raised.

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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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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.

Busy week, big checks, lots of AI and robotics. That, in ultra-brief synopsis form, characterized the general startup fundraising environment this week. Notably, the two largest global rounds were U.K.-based and Paris-based , which raised $2 billion and $1.03 billion, respectively.

In the U.S., meanwhile, e-commerce platform , AI networking developer and industrial automation startup each picked up $500 million.

1. (tied) , $500M, e-commerce: Quince, an online fashion and home goods retailer with an affordable luxury theme, said it secured $500 million in Series E financing led by . The round sets a $10.1 billion post-money valuation for the 8-year-old, San Francisco-based company.

1. (tied) , $500M, AI infrastructure: AI networking startup Nexthop AI raised $500 million in Series B funding led by , with joining as a major investor alongside other backers. The Santa Clara, California-based company develops switching technology built on open-source operating systems for AI and cloud networking.

1. (tied) , $500M, robotics: spin-out Mind Robotics closed on a $500 million Series A round, co-led by and Andreessen Horowitz. The Palo Alto, California-based company is developing an AI-enabled industrial robotics platform, with a focus on automating industrial and manufacturing tasks at scale.

4. , $450M, robotics: Palo Alto, California-based robotics startup Rhoda AI emerged from stealth with $450 million in Series A funding reportedly led by . The startup trains robots using hundreds of millions of videos to develop intelligent models for operating in complex and changing environments.

5. , $400M, AI software creation: Replit, an agentic AI software creation platform, picked up $400 million in Series D funding at a $9 billion valuation, up from $3 billion just six months ago. led the financing for the Foster City, California-based company, joined by a long list of venture and celebrity investors.

6. (tied) , $200M, AI networking: AI startup Eridu emerged from stealth with over $200 million in a newly announced Series A round led by , , , and . Saratoga, California-based Eridu develops a high-performance network switch for AI data centers.

6. (tied) , $200M, artificial intelligence: Palo Alto, California-based Axiom Math AI, a developer of AI systems that can perform automated verification of computer code, $200 million in Series A funding at a $1.6 billion valuation. led the round, joined by , , and .

8. , $165M, robotics: Sunday, a startup planning a beta launch for a household robot called Memo later this year, raised $165 million in Series B funding. led the financing, which set a $1.15 billion valuation for the Mountain View, California-based company.

9. , $125M, cybersecurity: San Jose, California-based Kai, developer of an agentic AI cybersecurity platform, announced that it secured $125 million in funding led by .

10. , $100M, procurement: Oro Labs, developer of a procurement platform for enterprise customers, raised $100 million in Series C funding. and led the financing, which the company said follows a year of 300% revenue growth.

Global financings

The week鈥檚 largest rounds went to European startups.

, $2B, AI infrastructure: Nscale, an AI infrastructure hyperscaler, secured聽 $2 billion in Series C funding. and led the financing, which set a $14.6 billion valuation for the London-based company.

, $1.03B, artificial intelligence: Advanced Machine Intelligence, a startup co-founded by computer science pioneer and former AI chief , said it has raised $1.03 billion to develop 鈥渨orld models,鈥� or AI designed to learn from and interact with the physical world. The funding for the Paris-based company represents the largest seed round ever for a European startup.

Methodology

We tracked the largest announced rounds in the SA国际传媒 database that were raised by U.S.-based companies for the period of March 7-13. Although most announced rounds are represented in the database, there could be a small time lag as some rounds are reported late in the week.

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