You have likely never heard of . You should have.

Over the past decade, Tosin and his team built into the operating system for more than 6 million Nigerian businesses, , or .

As a Nigerian American, I’ve witnessed my father make trips to Western Union to send money back home for decades, and I experienced Nigeria’s fee-laden payment system when visiting the country. Moniepoint is transforming that system.

Moniepoint is not alone. , , , , ��1 — these are companies most Americans have never heard of, despite them being worth several tens or hundreds of billions, following the trail blazed by , and .

These are super apps that bundle banking, commerce, ride-hailing and bill pay into one trusted application. The idea never took hold in the U.S. for one reason: trust is cheap here. With , a specialist app inherits the credibility of the financial system. Where trust is cheap, there is no need for a super app.

Build trust first

In emerging markets, trust is the whole problem. Four conditions tend to precede a super app: High mobile penetration, which makes distribution cheap; weak incumbent competition; poor existing financial services; and the condition most investors screen past, a financial crisis severe enough to strip incumbents of legitimacy. These populations are not merely underbanked. They were harmed, and the institutions that harmed them still hold the market.

Brazil froze roughly 80% of bank deposits and financial investments for 18 months in 1990 in an effort to break hyperinflation. The banking consolidation that followed left five banks and . That was the void Nubank was born into.

Kazakhstan went through it twice: savings erased by inflation in the thousands of percent when the ruble zone collapsed in 1993, then a 2007–09 banking crisis in which the country’s largest bank, BTA, holding roughly a quarter of the system’s assets, Kaspi grew into that void.

Southeast Asia’s 1997 crisis was harsher still. Indonesia closed 16 banks in a single announcement, the %. Two decades later which enabled Sea to build and into that gap.

Kaspi also answers the objection I hear most from American investors, which is that these markets are too small to produce large exits. Kazakhstan has only 20 million people, and according to company , around 14 million — nearly 70% of its population — use Kaspi. The . It earns . Depth of spend, not population, sets the ceiling.

Compare Nubank to . Nubank has 14x the customers, to , about 7x the revenue and a market capitalization more than 6x larger. Nubank . A technology applied in an overlooked market with a large unaddressed pain point can build a bigger and more defensible company than the same technology applied in a rich one.

Screen for the four conditions and a few markets stand out as places where the next super app could emerge:

• Bangladesh: , with the government now promising to pay 7.5 million savers whose money is gone.
• Egypt: Repeated devaluations of the pound between 2016 and 2024, shrinking savings held at banks the state itself owns.
• Vietnam: after its owner was arrested in a $24 billion fraud.
• Pakistan: , then government-built rails and a national ID that makes onboarding nearly costless.

One boundary condition: The crisis must be severe enough to delegitimize incumbents but contained enough that the currency and payment rails still work.

The first generation of super apps created enormous value for the investors who backed them early. In 2001, the South African media company paid roughly $34 million for a 46.5% stake in Tencent, and . ’s investment in Nubank’s $2 million seed round, combined with its lead Series A investment, was worth $7 billion at the company’s IPO.

The second generation is scaling now. The third will be built on stablecoins and AI technologies, in Abidjan, Buenos Aires, Karachi and Lagos, by founders like Tosin Eniolorunda who will play an increasingly important role in the growth of emerging market economies.

�� is co-founder and managing partner of , where he oversees the firm’s investing strategy, governance and compliance, with a focus on fintech and enterprise technology. Since co-founding 645 Ventures in 2014, he has invested in and partnered with companies including , , , , and . Previously, he was an investor at , where he invested in 19 companies and had nine exits representing more than $9 billion in exit value.

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From January through August U.S. tech layoffs reached at least 94,046, up 16.8% from 80,486 in the same period of 2025. Interestingly, and unsurprisingly, many of the cuts came as tech companies redirected spending toward AI and restructured operations to reduce costs.

The year started off on a busy note on the layoff front. After job cuts dropped sharply in December 2025 to 5,151, they surged in January to over 20,000. May was particularly brutal. The month drove the year-to-date increase, recording 31,513 layoffs — including ’s 8,000-job reduction — the highest monthly count since March 2023, when layoffs reached 36,602.

Recent months indicate a slowdown. Layoffs fell each month after May, reaching 2,347 in August. Overall, June-August 2026 layoffs totaled 19,331, down 16.2% year over year. The decline suggests recent easing, though it is too early to establish a lasting reversal.

Artificial intelligence has become a much more common explanation for layoff decisions, noted , founder of AI was cited in 33% of tech layoff events this year, up from just 1% in 2024. His tracker attributes 92,913 layoffs globally, or 72% of this year’s total, to AI.

“There’s been little evidence that AI is actually replacing the work of the human employees let go,” Lee said of this year’s largest AI-attributed layoffs. He believes established tech companies are spending heavily on AI and cutting costs elsewhere, hoping to increase productivity with smaller workforces.

Companies cutting

This year, we’ve seen a number of Big Tech and publicly traded companies, as well as startups, make deep cuts.

But interestingly, as with last year, public tech companies have dominated layoff headlines in 2026 so far, led by and Meta.

“Big companies [have] made up about 87% of everyone laid off in 2026, which is similar to last year, when they made up 85%,” Lee said.

Amazon accounted for 17,388 cuts this year so far through August. Those included a 16,000-worker RIF announcement in January and several smaller subsequent rounds. Meta was next with 10,400 layoffs, including an 8,000-job reduction carried out in May that represented 10% of its workforce.

and recorded the next-largest totals, letting go of 4,800 and 4,760 employees, respectively. , and each recorded 4,000 layoffs, followed by with 3,000, with 2,900 and with 2,600. Notably, the Top 10 list spans a variety of sectors, including cloud computing, social media, payments and enterprise technology.

We should also note that according to reports, ’s workforce fell by about 21,000 employees in its fiscal year ended May 31, 2026, but the worker count and exact timing for each of�� those reported cuts was unclear, so we did not include that total in our tracker.

Among privately held companies in the tracker, recorded the largest disclosed total at 1,000, followed by HR software provider with 950 and with 500. Those figures were substantially smaller than the largest public-company reductions, although undisclosed layoff counts limit comparisons between the two groups.

And in early September, reportedly laid off 3,300 workers, or 10% of its workforce.

An AI focus

, of , says AI is affecting jobs in two ways. Some work, including coding, can now be done with fewer people. “There are jobs that are literally being replaced by artificial intelligence,” he told ������Ƶ News.

But companies are also changing their priorities. They’re putting more money into AI and cutting teams working on other parts of the business. “They’re letting people go from one area of their organization while they might even be hiring in an area that is focused on AI,” Challenger said. That’s why a company may lay people off and advertise new jobs at the same time.

Tech has announced more job cuts than any other industry this year, Challenger said. Across the U.S. economy, layoffs are down somewhat from last year, though that comparison is skewed by the large number of federal job cuts in 2025. When compared with the period just after the pandemic, when employers struggled to find workers, layoffs remain elevated.

Few companies outside tech have blamed job cuts on AI so far, Challenger said.

It’s not all negative though, in his view. There’s potential upside for programmers, he said. If AI makes software less expensive to build, companies in other industries might embark on projects they couldn’t afford before. That could mean new jobs outside tech, though it’s too early to know whether those jobs will make up for the ones being cut.

Also, it appears that some companies might be regretting their layoff decisions. Amazon is reaching out to eligible former employees about open roles across the company, including in its cloud-computing and AI businesses, according to a�� report.

Methodology

Layoffs figures are from The ������Ƶ Tech Layoffs Tracker, where we record reported job cuts at U.S. tech employers. The tracker includes layoffs conducted by U.S.-based companies or those with a strong U.S. presence — both privately and publicly traded — and is updated at least bi-weekly. Layoff and workforce figures are best estimates based on reporting. Actual layoff figures are likely much higher than reported as many companies do not disclose the number of jobs cut when announcing layoffs. For more about our methodology for tracking layoffs, refer to the tracker’s methodology section.

Related reading:

• The ������Ƶ Tech Layoffs Tracker

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Ten years ago, a seed-stage startup needed a product, a team and a pitch deck to raise capital. Today, that’s just the start. Technology and strategy have become inseparable, each fueling the other, and the rules that once defined success have quietly shifted under everyone’s feet.

Last month, my firm reviewed more than 2,500 inbound applications. Here are the key shifts we’re seeing in the startup ecosystem at the seed stage.

Broadening capital strategy

Equity is a powerful tool for building high-growth companies. But it’s no longer the only option. Non-dilutive growth capital is increasingly playing a strategic role for companies with revenue visibility and clear ROI channels.

For example, we recently financed a company with $1 million in growth capital it needed immediately to expand its team and infrastructure. Raising that through equity alone would have likely taken months, with significant time and execution cost along the way.

We’re now writing financing checks like this on a near-weekly basis.

Distribution focused

Leading with a “better” product isn’t enough to propel growth. The breakout companies are investing in building stronger distribution systems — aka what founders refer to as “traction.” Distribution is a critical moat for early-stage startups. Rapid scaling is no longer achieved by launching new products; it’s through distribution loops.

Distribution is something startups can now architect intentionally with social platforms, marketplaces and other ecosystems. One of the most common founder mistakes we see is delaying the distribution strategy until after the product launch. At that stage, the architecture is harder to retrofit. Strong startups design distribution before they scale their product.

For example, some of the fastest-growing startups now design their products around existing ecosystems from day one — building apps that tap into merchant marketplaces, AI tools distributed through or Teams integrations, or fintech products embedded directly into banking and payroll workflows. In many cases, the distribution channel becomes more valuable than the underlying product itself.

One of the most common mistakes we see is founders postponing distribution strategy until after the product is built. By then, the architecture is far harder to retrofit. The strongest startups design distribution into the company before they scale the product itself.

Learning over speed

“Move fast” is often dolled out as the best startup advice. Operating in a fast-paced environment remains a strategic asset, but it is not enough to maintain a competitive advantage.

Everyone is fast. It’s no longer a unique attribute. Instead, learning velocity is becoming the defining advantage in early-stage startups. How quickly can you reduce uncertainty? Competitive edge is achieved not by executing blindly, but by closing knowledge gaps faster than everyone else. Execution without learning equals wasted motion.

The founder focus advantage

Last year, my team reviewed close to 25,000 applications for our investment funds and bespoke accelerators. The ones that stand out are the companies doing the fewest things exceptionally well. The most-fundable companies can describe their business in one tight sentence. They can also defend exactly what they are not doing.

Disciplined constraint is one of the highest-leverage traits in venture-backed companies. When we review applications, this pattern consistently stands out.

When a company is focused, the residuals compound: stronger early retention, faster iteration cycles, cleaner capital deployment. In a capital-selective market, focus compounds faster than ambition.

Based on tens of thousands of applicants, close to 82% of the ones that stayed in business a year later had a strong go-to-market foundation in their deck. GTM is built on agility and learning fast.

AI as infrastructure, not experimentation

There’s no lack of interest in AI. But there is an implementation problem. We’ve seen companies struggle when AI is approached as experimentation rather than architecture. Rather than bolting tools onto already fragmented stacks and workflows, designing intelligent systems should be mapped from the ground up.

More than 78% of the founders applying to today are leveraging AI in at least one way in their startup.

The most successful playbook combines execution with operational clarity and emphasizes infrastructure over experimentation. We’ve seen successful implementations that center around two practical paths. The first is validation, with rapid prototypes and identifying market signal opportunities before investing in a full build. The second is system, designing and integrating custom AI agents directly into operating workflows for revenue-generating companies facing operational complexity. Both are required to move AI agents from concept to capability. A disciplined system design often matters more than flashy tooling.

Marketing is the moat

Marketing execution is one of the largest performance gaps we see across early-stage startups. Startups lose when they don’t distribute fast enough once there is something worth selling. Marketing is the propeller for the distribution engine.

Most startups fail at marketing because it is a business function that becomes a founder hustle with support from one junior hire. But breakout growth requires process, cadence and accountability. That’s not achievable without an experienced team and clear plan.

One of the biggest mistakes founders make is treating marketing as something that starts after launch. Founders must create unique strategies, test them and then analyze what works and what doesn’t. From there, they must keep iterating and creating to unlock the most product-market fit and traction.

If we see classic strategies in a pitch deck, it is an auto-reject. And beyond being unique, your strategies must have been tested by your team.

The key is simple: Test ideas early, measure what actually works, refine aggressively and scale the strategies that compound over time.

, a serial technology entrepreneur since age 12, is now a value-driven venture capitalist with a track record of backing more than 1,000 startups across the globe. He is a co-founder and general partner at , one of the world’s most active venture capital firms. Before becoming involved in venture investing, he built and scaled into the world’s largest debate-focused social network and edtech platform, reaching millions of users and serving students across more than 500 school districts, colleges and universities.

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Startups across sales, marketing and customer management have raised $7.5 billion so far this year, according to ������Ƶ data. The largest rounds span everything from advertising and customer data to sales software, e-commerce and customer support — reflecting just how many companies are still trying to build a better way to market and sell.

The broad trend: Investors are making far fewer bets on sales and marketing startups than immediately before and after the COVID-19 pandemic, but they’re still writing checks into the space.

Unsurprisingly, AI-focused companies are capturing a much larger share of funding than during the prior peak, with most sales, marketing and CRM investment going to companies in ������Ƶ AI-related categories.

The numbers: So far in 2026, startups in sales, marketing and CRM have raised $7.5 billion globally across 830 funding rounds, ������Ƶ data shows. At the current pace, funding could finish near the $9.3 billion raised in both 2023 and 2024, although potentially below last year’s $11.1 billion. Deal volume, meanwhile, is on track to fall for a fourth consecutive year — pointing to a market where investors are putting more money into fewer companies.

Funding in recent years remains far below past levels. In 2022, for example, funding in the sector topped $27 billion, and in 2021, it totaled nearly $41 billion.

Notable deals

The year’s largest funding recipient so far was, which raised more than $1 billion in a June Series E from , , and . The San Francisco-based marketing measurement company, whose products now include AI agents that analyze marketing data and automate tasks, was valued at $2.7 billion.

Restaurant financing and rewards platform announced $450 million in new capital in February. The Austin-based company did not identify a lead investor or disclose a valuation.

In January, AI-native customer service company raised a $350 million Series D led by . The Berlin-based company develops AI agents that handle customer conversations by phone and other channels. The financing tripled its valuation to $3 billion.

Meanwhile, , an online marketplace for digital products, communities and courses, received a $200 million strategic investment from in February. The deal valued the New York-based company at $1.6 billion.

Another larger deal went to Dubai-based property listings platform , which announced a $170 million equity investment in January. The company uses AI in products including home valuations and tools that help real estate agents improve and prioritize listings. led the deal, with participation from another UAE sovereign wealth fund and existing investor . The company did not disclose a valuation.

On Sept. 9,�� AI-powered sales automation startup announced it had raised a $115 million Series D at a $7.1 billion valuation. This was more than double the $3.1 billion valuation it achieved when it raised a $100 million Series C in August 2025. Wellington led the latest round, with participation from , , ’s a16z Perennial wealth management arm, , and others. The company says the raise followed 4x revenue growth in 2025. It also told ������Ƶ News that it’s on track to hit $200 million in ARR this quarter, and $240 million by the end of the fiscal year.

Exits

The sector has produced one notable public offering, but most exits are coming through acquisitions as larger companies buy specialized sales and marketing products to add to their existing platforms, ������Ƶ data shows.

, a Redwood City, California-based mobile advertising and app-marketing company, began trading on the in June. It initially sold 19 million shares at $23 each, raising $437 million. The IPO valued Liftoff at $3.83 billion, based on the outstanding shares disclosed in its IPO prospectus.

There have been a number of M&A deals this year in the sector, too, though in most cases, the acquisition price was not disclosed.

The largest known deal was Dutch payments giant acquisition of , a Berlin-based loyalty and promotions platform, in July for about $880 million. Talon had previously raised over $120 million in venture funding.

Other startup M&A deals in the marketing and sales arena in 2026 include:

• In July, acquired Seattle-based sales intelligence startup to add information about prospective buyers to its sales products.
• In June, agreed to acquire , whose software helps companies identify and contact people visiting their websites.
• Sales platform acquired , which helps sales teams identify prospective customers based on product use and other signals, in March.
• acquired the Estonian startup , whose software connects sales and marketing data, in August.
• acquired India-based marketing intelligence startup in September through a team and technology deal.

Funding is down from peak years, but it’s clear investors haven’t lost interest in sales and marketing startups. However, they are putting more money into fewer of them. Companies that help businesses find customers, increase sales, or retain existing business are still landing big checks and attracting buyers. But with acquisitions far more common than IPOs, a public-market exit remains much harder to come by.

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led the raise, which brings the Austin-based startup’s total funding to $40 million since its 2022 inception. Returning backers , , and also participated in the round. ClearJet’s earlier investors include , formerly JetBlue Ventures, and .

ClearJet’s model is straightforward. Rather than build its own fleet of planes or trucks, it connects shippers with unused cargo capacity on commercial flights already traveling between U.S. cities to move e-commerce packages around the U.S. Customers include major multibillion-dollar retailers, e-commerce platforms, 3PLs and marketplaces.

In just three years, the startup has built what founder and CEO calls a “super carrier,” a network that now spans 95 U.S. airports and connects retailers with major U.S. airlines and multiple final-mile delivery providers. This network gives retailers a way to ship packages so that they travel directly between cities on passenger planes already in the air rather than through the traditional networks used by major parcel carriers.

Unlike a traditional parcel carrier, ClearJet doesn’t own the planes transporting those packages. Instead, its asset-light “Uber for cargo” model taps available capacity on flights that are already traveling between cities. The startup says its approach can cut shipping costs by as much as 35% while speeding deliveries by one to three days.

“We’re basically connecting with the already moving aircraft,” Guggenheim told ������Ƶ News in an interview. “These flights are going from A to B city. We’re taking those same routes, and that’s just why we’re so fast. That’s also why we’re so cost efficient.”

The approach appears to be working. ClearJet is profitable, its revenue has more than tripled year over year, and it is approaching nine figures in top-line revenue, according to Guggenheim.

The market opportunity is still large. The startup says it moves more than 30 million packages annually, which is still a fraction of the roughly 1.8 billion U.S. parcels it considers eligible to move by air.

Global funding to supply chain management and logistics startups has reached $8.4 billion in 2026 so far, per ������Ƶ . This puts this year on pace to top 2025’s total of $9 billion considering we have over four months left in the year.

How it works

Retailers connect to ClearJet through an API and can generate a two-day shipping label. ClearJet picks up the packages, takes them to an airport, handles sorting and screening, places them on commercial flights, and then injects them into final-mile networks at their destination. Those providers can include , the , , , and , Guggenheim said.

“We call it the super carrier because it truly is that, and it gives all the power back to the retailer,” Guggenheim said in an interview with ������Ƶ News.

One of ClearJet’s first large retail customers had previously relied on FedEx for goods arriving from Asia, with deliveries taking seven days from factory to customer, according to Guggenheim. Under ClearJet’s model, products arrive at Los Angeles International Airport, where the company takes possession of the cargo, sorts it and flies it into 14 different airports before handing the packages to final-mile carriers.

The result, Guggenheim said, was a reduction in delivery time from seven days to five — and $35 million in cost savings for the customers.

That combination of time and cost savings was what caught Edison Partners’ attention.

, who leads the firm’s vertical SaaS and AI practice, told ������Ƶ News that Edison had spent years looking at ways to use excess capacity in supply chains without requiring companies to make massive investments in physical infrastructure.

“We looked at a few supply chain businesses over the years,” Ziegler said. “Candidly, most of them went bankrupt because they took an asset-heavy approach to the middle mile.”

ClearJet took the asset-light approach. And the company’s airline relationships, regional sortation infrastructure, regulatory license and technology architecture make it difficult to copy its model, according to Ziegler.

“When you think about what they built, it is a very unique aviation infrastructure platform, and it’s difficult to replicate,” he said. “He’s [Guggenheim] proven the business model, and the unit economics work.”

Backstory

The idea for ClearJet grew out of Guggenheim’s own frustrations as a longtime e-commerce entrepreneur.

He started his first company in 1997 after meeting and his family and building direct-to-fan e-commerce businesses for them. Guggenheim later worked with a range of music and sports clients, including helping launch the first beyonce.com. His company went on to support more than 2,000 Plus stores with over $1 billion in GMV, he said.

Along the way, logistics became one of his biggest headaches.

Shipping had become the second-largest cost of goods outside of the product itself for his business, he said. And in 2019, after spending $55 million with , Guggenheim said he received an email giving him five days’ notice that his account was being canceled because it wasn’t profitable enough.

“And so I said, ‘there has to be a better way,’ ” he said.

Guggenheim began thinking about the thousands of domestic passenger flights traveling around the U.S. every day and wondering whether their unused cargo space could become part of an alternative parcel network.

He had no connections with the airlines, he said, so he began cold-emailing executives until he reached the president of . At a cargo industry event, Guggenheim got about five minutes to pitch his idea in what he now calls his “Shark Tank moment.”

“I said, ‘I want to start flying packages from LA to New York. Do you have any flights?’” Guggenheim recalled. “And he put his arm around me and said, ‘You and I are going to be best friends.’”

Guggenheim went on to build relationships with , , , and , the latter of which participated in an earlier ClearJet financing. He also began recruiting people from the airline and parcel industries and building the technology underpinning the network. ClearJet formally launched in May 2023.

One logistical obstacle was the aircraft themselves. Guggenheim said most U.S. passenger aircraft are narrow-body planes whose cargo doors are too small to accommodate the pallets typically moved by freight forwarders.

ClearJet addressed this by designing its own overpack bags specifically for e-commerce parcels. Those bags can travel through airports much like passenger luggage before being unloaded and handed to the appropriate delivery company.

AI component

ClearJet’s AI models choose each parcel’s path based on cost, speed and geography across its network. AI is also built into how ClearJet routes packages. Its models choose a parcel’s path based on factors including cost, speed and geography.

The company is also developing AI agents to automate more of the operational work around those shipments.

For example, ClearJet is creating AI agents to handle tasks such as rating, booking, tracking and managing delivery problems, according to Guggenheim.

This includes features such as responding to weather disruptions by moving packages onto a different flight or through a different city, something ClearJet can do because it isn’t tied to just one airline.

“We’re building an entire agent team, an army of agents that do everything that the humans were doing,” Guggenheim said.

ClearJet raised its seed round in early 2023 and $13.4 million in a Series A in 2024, according to Guggenheim. He declined to disclose the company’s valuation but described the Series B as a significant step-up from its previous financing.

Next, ClearJet plans to expand into returns and international shipping, and expand its network of airports. Guggenheim also wants to give consumers much more detailed visibility into where packages are during their journeys, similar to the real-time experience they have become accustomed to with services such as DoorDash.

“We have a really big appetite for giving consumers a better visual experience with their packages,” he said.

For Ziegler, the bigger bet is that ClearJet can become infrastructure for a delivery market increasingly built around getting products directly to individual consumers.

“We saw this as an opportunity to actually create a category-defining business,” he said.

ClearJet has just under 50 full-time employees and hundreds of contractors operating seven days a week.

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Ten of those companies were AI labs, collectively valued at $65 billion. The most well-known was Beijing-based open source model developer — at $50 billion, the highest valued new unicorn to join the ������Ƶ this year.

The new unicorn frontier labs are focused on new architectures in AI model development in robotics, physics and self-learning, as well as on open source development, and in the case of one India-based startup, sovereign AI.

Other leading sectors with multiple companies were in robotics and AI infrastructure, with four companies in each.

Of the new unicorns, 16 are U.S-based, while eight are from China. Two new unicorns joined the board from India, Germany and the United Kingdom and one each from Netherlands, Belgium, Canada and Saudi Arabia.

Big exits remove a trillion

Despite the influx of newcomers, the total value of The ������Ƶ ������Ƶ dropped by more than $1 trillion in June as , its most valuable company, went public.

Other notable exits from the board last month were , the maker of AI coding tool Cursor, which was acquired by SpaceX for $60 billion after last being valued at $29.3 billion. , an AI infrastructure company that operates as a layer on top of GPUs, was acquired by , and customer experience agent was purchased by 1, both for well above their last private valuations.

New unicorns in June

Here are June’s new unicorn companies:

AI labs

• Hangzhou-based raised a $7.4 billion Series A, its first external financing, in a deal led by CEO . The 2-year-old company was valued at $50 billion and is said to be planning to list in as early as Q2 2027.
• is building a new AI architecture based on neuroscience called Cortex AI that promises lower power use. It raised a $500 million Series A from , , and . The less than 1-year-old New York-based company was valued at $2.5 billion.
• London-based , an AI for physical product design in aerospace, defense, energy, automotive and semiconductors, raised a $300 million Series C led by . The 6-year-old company was valued at $2.4 billion.
• , a model developer for robotics trained on gaming videos from its sister company , raised a $320 million Series A led by . The 1-year-old New York-based company was valued at $2.3 billion.
• , an embodied robotics intelligence company, raised a $400 million Series B led by . The 2-year-old San Mateo, California-based company with researchers from and was valued at $2 billion.
• Shanghai-based , a�� robotics intelligence company, raised a $220 million seed round led by and . The less than 1-year-old company founded by an researcher was valued at $2 billion.
• , a builder of world models to simulate the real world impacting robotics, science, healthcare and defense, raised a $310 million Series B led by . The 2-year-old Menlo Park, California-based company was valued at $1.5 billion.
• Bengaluru-based , an Indian sovereign AI developer, raised a $234 million Series B first close led by . The 3-year-old company was valued at $1.5 billion.
• , an AI lab seeking to automate AI research for scientific use cases, raised a $200 million seed funding led by and . The less than 1-year-old San Francisco-based company was valued at $1 billion.
• Hangzhou-based , a 3D model developer used in gaming, entertainment and product design, raised a $200 million Series A led by . The 3-year-old company was valued at $1 billion.

Robotics

• Germany-based , a physical AI company building intelligent machines to to work alongside humans, raised a $1.4 billion Series C led by stablecoin issuer among other strategic and growth investors. The 7-year-old company, with $1 billion in its order pipeline and strategic deployments, was said to be valued at $7 billion.
• Shenzhen-based , a builder of humanoid robots, raised a $148 million Series B led by . The 3-year-old company was valued at $1.5 billion.
• Guangdong-based , a humanoid robotics company, raised a $147 million Series B. The 5-year-old company, which projects 1,000 shipments in 2026, was valued at $1.5 billion.
• , a builder of industrial arm robotics for manufacturing that said its technology learns through demonstration, raised a $200 million Series C led by and . The 9-year-old New York-based company was valued at $1 billion.

AI infrastructure

• , which pivoted from crypto mining to data center build out for AI, raised a $400 million funding led by , and . The 2-year-old Coral Gables, Florida-based company was valued at $2.4 billion. The company has filed for a direct listing on .
• Las Vegas-based , a cloud operator that offers customer AMD chips, raised a $350 million Series B led by and . The 2-year-old company was valued at $1.6 billion.
• Beijing-based , an inference solution offering customers API access to hundreds of models, raised a $296 million Series B. The 2-year-old company was valued at $1.2 billion.
• , an AI developer cloud to train, fine-tune and deploy AI, raised a $100 million Series A led by . The 4-year-old New Jersey-based company valued at $1 billion has 1 million developers using the platform.

Defense

• , a precision weapons company enabling existing weaponry to defend against unmanned drones, raised a $200 million Series B led by . The 4-year-old Austin-based company was valued at $2.2 billion.
• , a manufacturer of unmanned aerospace and defense systems, raised a $300 million Series C led by and . The 3-year-old Huntington Beach, California-based company was valued at $1.8 billion.
• , a cyber intelligence company building products for the U.S. military, raised a $100 million Series B led by , and . The 1-year-old Arlington, Virginia-based company was valued at $1 billion.

Proptech

• Montreal-based , a mortgage financing platform, raised a $217 million Series E round. The 8-year-old company was valued at $1.1 billion.
• India-based ,�� a property brokerage that also owns a mortgage marketplace, a property management platform, and a home interior brand raised a $95 million private equity and debt financing led by . The 13-year-old company was valued at $1 billion.

Data analytics

• Belgium-based , an intelligence platform for global physical trade, raised a $1 billion secondary market funding led by . The 12-year-old company was valued at $3.7 billion.

Biotechnology

• , a biotech company focused on reverse cellular aging, raised a $435 million Series C led by . The 4-year-old San Francisco-based company with plans for clinical trials next year for human liver cells, was valued at $3.1 billion.

Materials

• Cambridge, U.K.-based�� , building a network of labs using AI for new material discovery, raised a $450 million funding led by and . The 2-year-old company was valued at $2.6 billion.

Cryptocurrency

• , a blockchain and smart contract solution for global financial institutions, raised a $355 million Series F led by . The 12-year-old New York-based company was valued at $2 billion.

Image generation

• Beijing-based , a video generation company, raised a $300 million Series B led by , and . The 3-year-old company was valued at $2 billion and says it has built a creator community of more than 30 million users. As of May 2026 the company has $300 million in annual recurring revenue.

Financial services

• Saudi Arabia-based , a mobile banking company, raised a $400 million Series A. The 6-year-old company was valued at $1.6 billion.

Semiconductor

• Rotterdam-based , a 3D metrology inspection tool for semiconductor manufacturing, raised a $380 million Series D led by . The 10-year-old company was valued at $1.6 billion.

Aerospace

• Beijing-based , a space infrastructure and satellite company, raised a $207 million Series D. The 10-year-old company was valued at $1.5 billion.

E-commerce

• , an e-commerce provider that supports customer interactions post purchase, raised an $81 million Series B led by . The 4-year-old Utah-based company supporting 4,100 brands and 1,750 merchants was valued at $1.3 billion.

AI healthcare

• , an AI agent built for a patient’s healthcare journey and used by healthcare providers, raised a $120 million Series C led by . The 3-year-old San Francisco-based company was valued at $1.2 billion.

Transportation

• Munich-based , a car subscription platform operating in Germany and partnering with 25 brands, raised a $113 million Series D led by . The 7-year-old company was valued at $1.1 billion.

Related ������Ƶ unicorn lists:

• (1,822)
• (637)
• (213)
• (190)
• (118)
• (102)
• (935)
• (539)
• (248)
• (39)
• (488)

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• AI Services And Robotics Lead Diverse Crop Of 29 New May Unicorns As SpaceX, Anthropic And OpenAI Line Up Blockbuster Exits

Methodology

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

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

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

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

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

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

It was not a holiday week on the funding front, as a raft of largely AI-focused companies closed big rounds. The largest of these was a $1.5 billion financing to enterprise AI startup and a Series D for meal and delivery provider . The week also included some big financings for enterprise tech, food delivery, drones and construction automation.

1. , $1.5B, enterprise AI tools: Fireworks AI, a developer of tools for enterprises to turn “general-purpose models into specialized intelligence trained on their own data,” raised $1.505 billion in Series D funding. , and led the financing, which set a $17.5 billion valuation for the San Mateo, California-based company.

2. , $650M, meals and delivery: Wonder, an operator of kitchens and meal delivery services, closed on $650 million in Series D funding at a $9 billion pre-money valuation. Capital will go in part toward expanding operations for the New York-based company, which currently has 140 locations.

3. , $400M, life sciences AI: AI drug discovery startup Chai Discovery secured $400 million in Series C funding at a $3.8 billion valuation. led the financing, investing alongside , , and others.

4. , $300M, robots: Cambridge, Massachusetts-based Walden Robotics, a startup building general-purpose robots for work in manufacturing and logistics, launched out of stealth with $300 million in funding. and led the round, which values the company at $1.1 billion.

5. , $125M, drones: Seattle-based Brinc, a developer of drones for use in public safety and emergency operations, raised $125 million in fresh funding. led the financing, with participation from , and founder and CEO .

6. (tied) , $100M, construction automation: Austin-based TerraFirma, a developer of AI-enabled software and autonomous robotics technology for the construction industry, landed $100 million in new funding, bringing total investment to date to $115 million.

6. (tied) , $100M, enterprise AI: Spectro Cloud, a provider of AI infrastructure management software, said it raised more than $100 million in a Series D round led by . The financing brings total capital raised by San Jose-based Spectro Cloud to $260 million.

8. , $80M, defense tech: Singularity, a startup focused on developing air defense technology, emerged from stealth with $80 million in Series A funding. and 1��led the financing, which set a $400 million valuation for the Los Angeles-based company.

9. (tied) , $70M, fintech: San-Francisco-based fintech startup Flex, a private banking platform for high-net-worth business owners, raised $70 million in a Series B1 financing led by . The round follows the company’s $60 million Series B in December.

9. (tied) , $70M, AI and policy: State Affairs, an AI platform for policy and regulation, secured $70 million in Series A funding led by Khosla Ventures and .

Methodology

We tracked the largest announced rounds in the ������Ƶ database that were raised by U.S.-based companies for the period of July 11-17. 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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For this matchup, “¡Gooooooooool!” is really the only acceptable way to announce a new score. And if you can make that a good 21 seconds in one breath, all the better.

Here at ������Ƶ News, meanwhile, we’ve been prepping for the final in a less vocally demanding but much more data-intense manner. Since both contenders are far more famous for soccer than accomplishments in the startup realm, we figured a small step to rectify that was in order.

To do this, we put together a snapshot of recent startup funding tallies and trends for both Spain and Argentina. As you’ll see, neither accounts for a particularly large share of global or even regional investment. Both however, have an intriguing pipeline of recently funded companies.

Argentina

We’ll start with our second World Cup-related profile of Argentina. After it won the final in 2022, we wrote a venture funding-themed story calling the country’s startup scene “small, scrappy and sometimes very successful.”

Four years later, that description still holds. Argentinian startups typically pull in a few hundred million dollars in venture funding annually. Investment is, however, lower than for Brazil and Mexico, the two most populous Latin American nations, which commonly lead in funding.

Argentina’s startup ecosystem has also delivered some big hits over the years. The most famous Argentine-founded internet company — online marketplace �� — commands a market cap around $94 billion on . (It’s currently headquartered in Uruguay but traces its roots to a Buenos Aires garage.)

More recently, Buenos Aires-based fintech has been making waves in the regional startup scene. It’s raised $1.1 billion in known funding to date, including a $195 million March financing.

Others that have raised good-sized rounds this year are also in the fintech space, including:

• , a payments infrastructure startup, closed on a $55 million Series C round co-led by and .
• , a provider of payments and collections infrastructure, secured $27 million in Series B funding in February.

So far, 2026 is shaping up as a strong year for funding, with investment already ahead of last year’s total. Funding tends to fluctuate quite a bit from year to year as the presence or absence of a single large round or two can heavily skew the totals.

Spain

Oddsmakers say Spain is the favorite going into the final. However, it’s well known that often the underdog also prevails. That was the lesson from Spain’s 2:0 defeat of favorite France this week.

But while it may have prevailed over France in soccer, Spain continues to lag in venture funding. So far in 2026, Spanish startups have raised less than $2 billion in funding across stages, which is roughly one-third France’s total for the same period.

While not large, Spain’s funded startup pipeline is not lacking in pizazz. Take this year’s largest funding recipient — — which closed a $206 million Series C in March. Its anything-but-modest mission is to be a “global space transportation service provider to support cargo and human spaceflight missions to the Moon and Mars.”

Other standouts among the bigger rounds this year include:

• , an AI-enabled HR and payroll platform, scooped up $150 million in Series D funding at a $2.5 billion valuation in June. To date, the Barcelona-based company has raised over $350 million in equity funding.
• ��, a Madrid startup focused on infrastructure for near space, space tourism and aerospace data, closed on $140 million in Series D funding in May.
• , a Madrid-based developer of AI tools for analyzing geospatial data, picked up $130 million in Series B funding in April.

Overall funding to Spanish startups is also trending higher, with 2026 on track for a year-over-year gain. For the past few years, annual Spanish startup funding has ranged between $1.8 billion and $2.8 billion, as charted below.

Rooting for the underdog

While both Spain and Argentina have a long track record of soccer success, a case could be made that both are underdogs in the startup space. It’s a familiar situation for secondary hubs in the current AI-driven investment cycle. Capital has been concentrating even more heavily in Silicon Valley and other leading venture hubs.

Given all the follow-on effects a successful startup can have on its region, it’d be encouraging to see investors spreading their bets more broadly across a wider geography. Spain and Argentina have already proven they have what it takes to prevail in one very competitive arena. Given the capital and opportunity, there’s no reason to doubt their abilities in the venture-backed startup game either.

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The purported deal, which has been rumored for months, is notable not just for its scale — it would be one of the largest acquisitions of a technology company in recent years — but also for its highly unusual nature. Privately held startups typically lack the cash, publicly traded shares and debt capacity to acquire their publicly listed brethren.

Of course, Stripe is not just any privately held company. The fintech startup was, until just a few short years ago, the highest valued startup based in the U.S., before being eclipsed on that metric by AI labs and . In February, the company announced it had inked deals with investors to provide liquidity to current and former employees through a tender offer at a $159 billion valuation, which still ranks it as the fourth most valuable startup in the world.

With substantial private capital — it has raised some $10.4 billion since inception, —��Stripe has long been one of the most acquisitive venture-backed startups. It has made since its 2010 inception, according to ������Ƶ data. Only three have disclosed prices: stablecoin platform at $1.1 billion (2025), usage-based billing software startup at $1 billion (2026), and Nigerian payments startup at $200 million (2020).

Stripe’s M&A pace has also accelerated sharply since 2020, ������Ƶ data shows, with 13 of its 21 acquisitions announced since then.

Its recent strategy appears to be focused on stablecoins and crypto infrastructure — Bridge, , and —��as well as on billing and money movement through Metronome, payment processing startup and .

If the plan to buy PayPal does go through, it will most certainly make Stripe an even more formidable player in the crowded payments space.

It would also rank as one of the largest acquisitions of a U.S. tech company, public or private, of the past five years, according to ������Ƶ data, trailing only a handful of larger deals including $61 billion purchase of in 2022 and ’s acquisition of AI coding platform Cursor and its parent, , for $60 billion last month.

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led the round, which included participation from , , , , and others.

Founded in 2020, New York-based Capchase initially made a name for itself by providing revenue-based financing for SaaS companies. However, by late 2022, the company began to evolve into its current iteration: a vendor-financing technology platform. Capchase embeds itself directly into the sales workflows of companies such as original equipment manufacturers, software vendors and cybersecurity providers.

It has entirely discontinued its revenue-based financing, and instead now focuses on B2B buy now, pay later tools that help software and hardware vendors offer flexible payment terms while getting paid upfront.

The concept addresses a longstanding friction point in enterprise sales: vendors want cash immediately, while buyers want to preserve capital. Rather than forcing a buyer to pay $1 million upfront in 30 days, Capchase allows a sales rep to offer more flexible terms — say, $15,000 per month for up to five years. When the deal is signed, Capchase pays the vendor the full amount upfront, net of a financing fee.

“We started to see that there was a very big pull in the market,” , co-founder and CEO of Capchase, said in an interview. “We saw that sales cycles were expanding, CAC was going up, and all of this was driven by the high interest rates. Buyers wanted to pay as late as possible and pay installments.”

He added: “We shipped a product quickly to solve that need, and we started to get very strong market pull to the point that that ended up eclipsing the other product lines, and we decided to focus everything there.”

Displacing a legacy market with AI

The pivot has unlocked impressive growth. Capchase says it has a 400% growth rate over the past 12 months and forecasts another 200% growth in the upcoming year. Its workforce has scaled alongside this momentum, expanding to 75 employees, up from 50 a year ago.

While legacy banks, independent financing firms and captive financing arms have dominated the $1.3 trillion equipment financing market for decades, Capchase says it differentiates itself by replacing 1980s-era workflows with real-time automation.

Traditional financing approvals often require an email-driven back-and-forth that can take four to 17 days, according to Fernandez. Capchase claims to compress that timeline into seconds.

Capchase uses artificial intelligence and machine learning agents across its platform. For example, an “order generation agent” parses uploaded quotes or purchase orders to create flexible payment links in under 60 seconds — down from a manual process that typically took eight hours — according to Fernandez. As another example, an AI email agent automatically handles multiparty coordination between vendors, resellers and buyers, all without human intervention.

“What makes us different is that we are both the lender and the technology. And AI is what makes the combination work at the speed enterprise tech sales demands,” Fernandez told ������Ƶ News in an interview. “We built the credit decisioning engines that allow us to look at all the data these other players look at as well, but we were able to do it and infer it in just seconds.”

Moving upmarket and expanding globally

The new capital will primarily support Capchase’s rapid transition into the enterprise space.

“In the past 24 months, we went from serving vendors in the tens of millions of revenue to in the last 12 months in the hundreds of millions in revenue, and now in the multiple billions of revenue,” Fernandez said.

The startup’s platform now underwrites more stable, established borrowers. The average buyer utilizing Capchase has roughly $80 million in annual revenue, has been operating for over 20 years, and is profitable, he added. This profile has allowed Capchase to maintain a highly controlled risk environment and what he described as a “spectacular” default rate.

Capchase currently supports hundreds of tech vendors and tens of thousands of buyers. Its customer roster features enterprise tech giants, public cybersecurity firms and massive distributors, including , , , and .

Though Capchase keeps its specific financials, valuation and cumulative funding figures confidential, Fernandez confirmed that the latest capital injection represents a valuation step up from its 2021 $80 million Series B round. At the time of that raise, the company had raised more than $400 million in equity and debt.

Looking ahead, Capchase will use its fresh capital to scale beyond its core markets in North America — the U.S. and Canada — and Europe, including the U.K., Ireland, Belgium, Netherlands, the Nordics and Spain. Driven by direct demand from its enterprise partners, the company is officially entering the Australian market this year.

Reducing friction with flexible terms

, co-founder and managing partner of 01 Advisors, said he was drawn to Capchase primarily because of how AI has helped it disrupt traditional vendor financing.

Incumbents possessed plenty of capital but “have never been forced to build real technology because their customers had nowhere else to go,” he wrote via email.

AI fundamentally shifts this dynamic, allowing Capchase to “underwrite a buyer and create accurate docs in 30 seconds,” he said.

This solution hits close to home for Bain, who previously ran the sales team at and says he intimately understands the friction Capchase aims to eliminate. In traditional enterprise sales, momentum frequently stalls when a ready-to-buy customer hits a roadblock over payment terms, forcing sales leaders to either “discount to close, wait for the next budget cycle, or spend weeks negotiating.”

Those outcomes drain margin or time. Capchase completely removes that friction, Bain said, by offering instant approvals and flexible terms.

Fintech startups, particularly those that apply AI to traditionally manual or burdensome processes, have benefited from increased investment in recent quarters. Global funding to VC-backed financial technology startups totaled $53.8 billion in 2025, per ������Ƶ . That’s a more than 29% increase from 2024’s total of $41.6 billion raised.

Related ������Ƶ query:

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• Fintech Startups Globally Raise More Money In Far Fewer Deals In Q1 2026
• Exclusive: Capchase Raises $80M Series B To Give Startups Alternatives To Venture

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