Crunchbase data shows that so far this year, investors have poured around $48 billion into financings around the Series B stage 1, the highest tally in years. Yet round counts are below year-ago levels and are on track for a multiyear low.

Smaller Series B rounds grow scarcer

One trend driving capital concentration is a sharp decline in small and mid-sized Series B rounds.

So far this year, less than a third of deals in our sample set 2 were for under $30 million. By contrast, between 2021 and 2025, rounds in this range accounted for about half of deals, per Crunchbase data.

The smallest Series B deals have gotten particularly scarce. This year there were just 26 rounds under $10 million in our sample set.

Big rounds still a big thing

On the flip side, really large Series B rounds are quite popular.

At least 110 companies have raised rounds of $100 million or more around this stage so far this year. That’s roughly a quarter of all deals.

Of these, the largest by far was a $12 billion round 3���ڴǰ� , ’ physical AI startup that launched last year.

Model developer , led by AI pioneer , was tied for next-biggest fundraiser, closing on $1 billion in February. Nuclear energy startup also secured $1 billion in Series B funding across tranches this year, with as lead investor.

For  a wider snapshot, below we put together a sample list of more of this year’s biggest U.S. Series B recipients.

Mostly an AI story

Meanwhile, one of the least surprising findings from our analysis of Series B recipients is that it was a heavily AI-focused group.

So far this year, about two-thirds of Series B funding has gone to AI-focused startups, per Crunchbase data. In 2025, by comparison, about half of investment went to companies in AI categories.

AI companies were also heavily represented by round count. So far in 2026, more than half of all reported U.S. Series B deals have been for AI companies.

Bullish climate for Series B

Overall, the numbers point to a bullish climate for Series B investment, particularly for AI startups with demonstrated traction. The environment looks particularly favorable for companies that have already raised considerable sums at Series A and seed.

Even so, these don’t look like the best of times for startups seeking smaller Series B rounds. Seems like in the current AI-driven cycle, investors are increasingly focused on big checks for high-valuation companies.

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U.S. startups closed 272 Series A rounds in the third quarter, according to Crunchbase data, about 28% fewer than the 377 a year earlier. Seed held up better, at 984 rounds vs. 1,059. The megarounds hide how few A rounds are getting done.

Seed checks keep growing. The median U.S. seed round was about $3 million last year, 3x its 2018 level, according to Crunchbase. Yet only 24% of companies that raised a $1 million-plus seed in 2023 have moved past seed, and just 16% of the 2024 cohort, down from 55% or higher through 2020.

Size your seed against the Series A

‘s told Crunchbase News that Series A investors now expect $2 million to $3 million in ARR, sometimes $4 million, and the time from seed to A has stretched past two years. If a seed won’t carry you to that bar with six months to spare, a smaller round is the better deal.

A bigger seed isn’t required. Take , a New York-based supply chain planning software company founded in 2023 (and not an portfolio company). It raised a , right at the median, in April 2025, led by and , then closed a led by Madrona and about 17 months later.

Map your Series A leads now

Funds of $100 million to $500 million typically lead the Series A. Figure out which ones lead at your stage and when their current fund closes, then send the right partners updates for a year before you ask for anything.

Sell your way to the bar

The Series A bar is now a revenue bar, which makes it a go-to-market problem first. Most seed companies I meet have a stronger product than sales motion.

At MGV, our work starts with a first session we call Sales Jumpstart: we interview the founders and their team. We then score the company on our proprietary matrix: where it is today, where it should be, and what it needs to become a scalable go-to-market machine.

From there, founders work through workshops on outbound reach, qualification, profiling, the funnel, objection handling, hiring assessment, compensation plans, fundraising, deck building, storytelling and investor intros, with mentoring alongside.

A company at $2 million in ARR with a sales process a new hire can run is a better Series A candidate than one at $3 million built on founder-led deals nobody else can repeat. The founders who make it are already planning for the round after this one.

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 Schröder’s stewardship, MGV has swiftly ascended to a top-quartile firm, surpassing the performance of 95% of venture funds. has recognized him as one of the , and his perspectives are published regularly in Crunchbase News and other leading publications.

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Related reading:

• Seed Funding Is Bigger Than Ever — And Harder To Get
• In Charts: Seed Deals Keep Getting Bigger As Odds Of Reaching Series A Fall Dramatically
• Data: The Seed Funding Boom Is Concentrating Capital In The San Francisco Bay Area
• These Are Sectors Where Seed Rounds Of $5M To $10M Are Clustering This Year
• The Billion-Dollar Seed Isn’t The Deal You Think It Is

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But that’s not all. As investment hit unprecedented levels in 2026, Golden State companies alone raised more than all U.S. startups in any prior year on record. Most of that stems from a handful of megarounds for San Francisco-based AI pioneers.

And keep in mind: This year still has a couple months left. Yet California companies have already pulled in an unparalleled $385 billion in seed- through growth-stage rounds. That’s more than double last year’s tally.

California’s share of U.S. startup funding also has been trending higher for the past three years. Much of this is due to San Francisco AI unicorns, but we’re also seeing strength in the broader Silicon Valley region as well as Southern California.

Where the money went

Flabbergasting financings for San Francisco-based and account for more than half of this year’s California statewide tally. But even without those, California companies 1 still secured a disproportionate share of the largest U.S. equity funding rounds.

To illustrate, we used Crunchbase data to put together a list of the 10 next-largest California funding rounds this year.

Some of these are familiar names and involve fairly mature companies. For instance , which launched inside in 2009 and spun out as an independent company 10 years ago, picked up $16 billion in February.

Another old-timer is , which picked up $5 billion in August. It’s now 13 years old and has raised over $30 billion in debt and equity funding to date.

Still, we’re also seeing younger companies secure megarounds. , the physical AI startup co-founded and led by and launched last year, pulled in $12 billion in new funding this spring. And AI model startup landed $5 billion in a -led round this summer.

Early-stage funding

That brings us to our next point. California’s startup funding windfall isn’t only about late-stage and pre-IPO companies bagging enormous rounds. Early- and seed-stage companies are also attracting big checks from investors.

Per Crunchbase data, California companies have secured nearly $62 billion in seed- and early-stage financings so far in 2026. That’s roughly 57% of all U.S. funding at these stages.

It’s also far above prior year tallies, as charted below, and appears to be a record funding level.

Don’t bet against California

If there’s a lesson to be learned in these numbers, it’s one that savvy startup investors ought to have learned a long time ago: Don’t bet against California.

Whatever the year, whatever the technology cycle, California, and Silicon Valley in particular, have a knack for being home to the leading companies of the era.

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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 another interesting week for AI-related startup funding, with a number of large rounds and quirky companies. The largest financings went to , a developer of AI processors and systems, and AI lab . The quirkiest round, meanwhile, was undoubtedly a $200 million financing for , which wants to breed elite military dogs.

A number of big rounds in areas including biotech, space tech and physical AI rounded out the list.

1. , $1.5B, AI infrastructure: Santa Clara, California-based Tenstorrent, a developer of AI processors and systems, secured $1.5 billion in Series E funding. and led the round, which set a $6.2 billion valuation for the 10-year-old company.

2. , $1B, foundational AI: Flapping Airplanes, an AI lab with a focus on developing models that cost less to train and run, closed on $1 billion in Series A funding led by and . The round comes less than 10 months after the year-old San Francisco startup raised a $180 million seed financing.

3. , $325M, AI for critical infrastructure: ASI, a developer of AI technology for securing and operating critical infrastructure in areas such as aviation, transportation and defense, picked up $325 million in Series C financing. led the round, which set a $3 billion valuation for the Boston-based company.

4. , $250M, space tech: Xona, a startup developing a next-generation version of GPS, raised $250 million in Series D funding led by . The round sets a $2.4 billion valuation for the Burlingame, California-based company.

5. , $237M, biotech: Pathos AI, a startup applying AI to drug development, completed a $237 million Series E financing at a post-money valuation around $3 billion. led the financing for the New York-headquartered company.

6. , $215M, AI, robotics and life sciences: Warp Sciences, a startup applying AI and robotics to help develop new medicines faster, raised a $215M Series A round led by .

7. (tied) , $200M, online business marketplace: Whop, a platform that helps entrepreneurs build and run online businesses, secured $200 million in Series D funding led by and . The round set a $5.1 billion valuation for the New York-based company.

7. (tied) , $200M, biotech: South San Francisco, California-based drug developer  Star Therapeutics says it raised $200 million in new financing led by and . The investment follows ’s July acquisition of , a subsidiary of Star, in a deal valued at up to $2 billion.

7. (tied) , $200M, military dogs: Warhound, a startup that wants to breed working dogs for U.S. military forces and emergency responders, launched from stealth with $200 million in seed funding from a long list of backers including and 1.  The startup, co-founded by founder , plans to equip the dogs with Anduril technology.

10. , $160M, AI manufacturing software: Arda Industries, a developer of AI-powered software for manufacturing engineering, closed on $160 million in Series A funding at a $1.5 billion valuation, co-led by , and . The San Francisco-based startup also announced a previously undisclosed $72 million seed financing.

Methodology

We tracked the largest announced rounds in the Crunchbase database that were raised by U.S.-based companies for the period of Oct. 17-23, 2026. Although most announced rounds are in the database, there may be a small time lag, as some rounds are reported late in the week.

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and co-led the round, with participation from insurance industry veterans including , who will join Slingshot’s board. Rally is also a co-founder of the Minneapolis-based startup, as part of the firm’s broader approach. So far, it has co-founded roughly eight portfolio companies that have either launched or remain in stealth.

Slingshot, which is led by first-time founder and CEO , focuses on small insurance policies that consumers can buy as part of another purchase, such as coverage when booking a flight. Known as embedded insurance, the model puts coverage in front of customers when they might need it.

The startup’s software helps businesses offer those policies by connecting them with insurers that back the coverage. It uses AI to process and share data between the two sides, aiming to reduce the administrative work that can make inexpensive policies costly to offer.

Its first customer and design partner is , which serves more than 750,000 customers at an average premium of $25, according to Slingshot. Genteman told Crunchbase News that Slingshot’s first program will launch this month.

For now, Slingshot earns revenue as a technology provider working with outside insurers. But the six-person company, which formally began operating July 1, is also pursuing an acquisition that would allow it to back policies itself.

“We’re not a carrier yet, but we are rapidly closing on our carrier,” Genteman said in an interview.

Making the math work on a $25 policy

One product Slingshot is working on would let parents buy insurance when signing a child up for youth sports, Genteman said. A parent spending $2,000 on a volleyball league, for example, might be offered a $25 policy covering cancellation or an injury during the season.

Each policy includes paperwork and coordination with an insurer, and can bring potential claims. But when policies cost so little, managing them can quickly eat into the money they bring in, noted Genteman.

He believes that as vertical SaaS companies increasingly look beyond traditional subscription fees for growth, embedded insurance is “a largely untapped opportunity” to generate incremental revenue from transactions already happening on their platforms while delivering additional value to customers.

“The challenge is that the insurance and regulatory landscape is incredibly complex, and most SaaS companies don’t have the expertise, industry relationships or understanding of where to begin,” he said.

Slingshot aims to solve this by providing a white-glove service for those vertical SaaS companies, helping them go from an insurance product idea to “a fully operational offering.”

He offered a hypothetical example: A program collecting $500,000 in premiums with a 10% margin would have just $50,000 in margin.

“That’s not a viable program for the way incumbent carriers have set themselves up operationally,” he said.

Slingshot’s goal is to replace the spreadsheets, emails and disconnected systems used to manage that work with software that connects policy distributors and insurers directly. The company says its AI automates data-heavy tasks while keeping a record of decisions that the businesses involved can review and check.

It charges a 5% technology fee to administer programs through its platform. Acquiring an insurer would let it provide both the software and the financial backing, according to Genteman.

A customer helped shape the business

The difficulties facing Slingshot’s first customer helped bring the startup together.

Rally had already helped start Vertical Insure, which uses software platforms to sell insurance to its customers. According to Genteman, that business had opportunities to introduce more products but struggled to find insurers whose technology and processes could keep up.

“We can design the products our customers need almost overnight, but the industry is highly regulated, and we need delegated authority just to write and distribute what we’ve built,” Vertical Insure co-founder and CEO said in a statement. “The antiquated approval process on the carrier-side slows everything down.”

Even after finding an insurer willing to back a product, connecting the two companies’ systems could create more delays, Genteman said.

Slingshot was built to address those problems, with Vertical Insure helping shape its product as a design partner. Noland is also a Slingshot co-founder.

The opportunity in vertical SaaS

Genteman sees a broader opening among vertical SaaS companies: businesses that sell software tailored to a particular industry.

As vertical SaaS companies look for ways to grow beyond subscription fees, insurance could give them another avenue to make money from purchases customers already make through their platforms, argues Genteman. They already know their customers and what they’re buying, putting them in a position to offer coverage that fits the purchase.

A babysitting platform, for example, could offer coverage to help parents pay for replacement childcare if a sitter cancels at the last minute. Software used by pet boarding facilities could offer coverage for unexpected vet bills if a pet is injured during a stay. An equipment rental platform could let customers add protection at checkout against accidental damage or theft.

Those are examples of what could be developed, Genteman said. Slingshot aims to help vertical SaaS companies take ideas like those and turn them into insurance they can sell, providing both the software and help navigating the insurance industry and its regulatory requirements.

“Insurance becomes another product that can be offered naturally within the existing customer experience,” he said.

For , managing director at Rally Ventures, that opportunity is familiar. Before joining Rally, he ran , where insurance sold through its software became a key revenue source.

“That experience gave me firsthand insight into the opportunity for software companies to generate revenue through embedded financial products,” he wrote via email.

Kaufenberg sees similar potential across Rally’s portfolio, where most companies combine AI products with financial services. He said founders increasingly want insurance partners that can help them introduce coverage quickly.

Rally co-founded Slingshot to bring insurance backing, underwriting, reporting, claims handling and distribution together in one business.

“To get the carrier, the reinsurance, the underwriting platform, the data flow engine, the reporting capabilities, the claims handling, the embedded distribution engine, and every other part of the offering from a single vendor is unheard of,” Kaufenberg said.

From insurance executive to founder

Before starting Slingshot, Genteman was chief actuarial officer at publicly traded , where he also led data. He joined in 2019 and helped build its actuarial and data team as the company expanded beyond earthquake insurance into other coverage types.

That work led him to explore whether newer technology could reduce the costs of running insurance programs. About a year ago, he began coding and building prototypes in his basement. He started talking with Rally toward the end of 2025 and left Palomar on July 1 to run Slingshot.

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The partner began his career as a high school math teacher with after studying astrophysics at . He later worked in college access and Yale admissions, and earned graduate degrees in business and education from before joining Reach. As a teacher, he was an early user of , an experience he describes as “game-changing.”

His investment firm, Reach Capital, has also evolved. Founded in 2015 after spinning out of , the San Francisco-based firm initially focused on technology for K-12 schools and districts. Its mandate has since expanded to learning, health and work, with investments in companies including ClassDojo, , and .

In August, Reach announced its fifth fund, a $265 million vehicle that brought its assets under management to nearly $1 billion. The firm, which has backed more than 180 companies, plans to invest in approximately 50 additional teams through the new fund, targeting pre-seed, seed and Series A rounds.

Crunchbase News spoke with Kim about how Reach’s education roots inform its broader strategy, what it saw in AI detection company , and why some of its best investments initially divided its own team. We also discussed how ownership stakes and secondary transactions have shaped the firm’s approach to returning capital.

This interview has been edited for length and clarity.

Crunchbase News: You started your career as a high school math teacher. How did that shape your view of education technology?

Kim: I taught ninth through 12th grade, mostly Algebra I and geometry. I was very early to ClassDojo. Back then, it was a very simple classroom management tool, and it was game-changing for me. It has since evolved into a sprawling suite, but I already knew technology could move the needle.

Reach began as an education investor. How did the firm’s focus evolve into learning, health and work?

Kim: Reach started in 2015, and our original focus was exclusively on learning and education technology — more specifically, technology sold into schools and districts.

Our founding partners were seeing the growth of devices in schools, one-to-one device ratios and broadband penetration. The belief was that you would start to see a proliferation of technology serving students, teachers and administrators and moving the needle on learning outcomes. That is what ended up playing out. Some of our early bets are now household names in edtech, such as , and ClassDojo.

Reach spun out of NewSchools Venture Fund, where three of our four founding partners had started doing for-profit seed investing before 2015. Over time, we branched out from K-12 into higher education, and then into consumer learning.

We also started getting pulled toward healthcare and work. Health and wellbeing affect a learner’s readiness for the classroom, so we were being pulled toward mental health, behavioral health and developmental health. On the work side, formal learning typically ends in college, but you still need the bridge to a job. Once you’re on the job, you need to continue learning, especially in the current environment.

A few years ago, we officially put a stake in the ground and said we invest across learning, health and work. The common thread is that these are the most important systems underlying human development and flourishing.

So far, the breakdown has been roughly 50% learning, 25% health and 25% work.

These sectors have different buyers, regulations and business models. What did investing in education teach you that translates to healthcare and work?

Kim: Education is highly regulated, and institutional buying is complex. Many stakeholders must provide input, and decisions often require board-level approval. We were familiar with and comfortable with regulated products and complex go-to-market motions.

Selling to a university or a K-12 district, in terms of the complexity and the need to intersect with regulation and policy, is quite comparable to selling to a health system, hospital or insurance carrier.

Cartwheel is a good example of where our experience gave us an advantage. It provides mental health teletherapy, but the customer is the school district and the care setting is in schools.

While we were relatively new to behavioral health when we made that investment, we were very familiar with selling to school districts and implementing an intervention within a school setting. That gave us an advantage both in winning the investment opportunity and supporting the company afterward.

Reach talks about “elevating human potential.” What makes an investment fit that mandate?

Kim: We look for products and services that increase access to quality education, quality care or quality earnings, or some combination of those. We really have to see the mechanism for that happening.

It’s not good enough to be pitched a SaaS or AI product and have the founders say, “This will make people more productive at work, and therefore maybe they will earn more or enjoy their jobs more.” That’s plausible, but it isn’t a good enough theory of how the product actually increases access to quality earnings.

Several teammates, including myself, are former educators. We care about meaningful, needle-moving impact.

We address access from both the demand side and the supply side. On the demand side, we build products that create delightful, impactful experiences for consumers: , Stepful’s allied healthcare training, and Replit for what its founder calls “citizen developers.”

On the supply side, it’s helping schools, health systems and companies function more efficiently and effectively. , for example, helps logistics and hospitality companies hire hourly workers better and treat them better. We think about the problem from both sides of the market.

Reach backed GPTZero, which agreed to join . Was that an investment in solving a problem created by AI?

Kim: That wasn’t actually our investment thesis. In my opinion, they have the best AI detector on the market. But their thesis was that AI use in education should not be banned. It shouldn’t be punitive or become a cat-and-mouse game between the educator and the learner.

Since all of us as professionals use AI in our jobs, students should learn how to use it responsibly and thoughtfully. It was the first AI detector company I had seen with that positioning, as opposed to helping schools, districts and universities clamp down on AI usage.

That’s why I liked it. I don’t see it as a problem for students to use AI for certain purposes, such as brainstorming, organizing thoughts and editing. GPTZero helps educators work with students and teach them how to use AI responsibly.

Do you see other opportunities to build companies around the problems AI creates?

Kim: Yes, most notably in AI governance and evaluations.

Going back to regulated categories, you need to make sure AI is not irresponsibly using personally identifiable information in education or healthcare. Those categories have very strict regulations, and infrastructure companies are emerging to help ensure AI products interact with that data responsibly.

I do think there are opportunities for large, successful, profitable companies to be created in response to the problems AI creates.

What does GPTZero’s sale tell you about which AI products can become durable standalone companies and which belong within larger platforms?

Kim: I don’t know whether GPTZero is an example of either. They had been fielding acquisition offers from pretty early on. This particular opportunity arose earlier this year, and there was a compelling synergy story with Superhuman, formerly .

The founders and the board agreed that it made sense to combine the companies. But they could just as easily have remained standalone. There is another AI detection company called that’s quite good and is still a standalone, venture-backed company.

It’s not clear to me that this category can’t exist on its own. We have to be very case-by-case. We don’t know until we see the trajectory, financial sustainability and evolution of the market, whether it makes sense to explore a strategic acquisition or grow independently and perhaps one day become a publicly traded company.

Reach has backed more than 180 companies. What patterns have you noticed among those that exceeded expectations?

Kim: The reality of venture is that a very small share of investments yields the overwhelming majority of returns. Given the outlier nature of those successes, it’s hard to identify unifying principles that always predict a successful exit. If we could, we would only make those investments.

But there are a few things we think are somewhat common across our wins. One is a very smart, gritty, genuinely mission-driven founder or founding team, often with a strong personal connection to the problem.

Second is some sort of nonconsensus insight about the market. That often comes from experiencing the problem themselves, sometimes as practitioners in the industry — a former educator, for example.

Third is a defensible and scalable business model.

The nonconsensus insight is funny because it’s what makes these companies look weird and maybe uninvestable in the beginning. Even within our team, they’re often the most polarizing opportunities. You look at the votes, and a bunch of people vote no, but it gets just enough yeses to pass. Then, 10 years later, it’s one of our best investments.

People lose sight of this in the current environment, but the best opportunities are often the most nonconsensus. Those can be the most creative and interesting founders, and you can get in at reasonable valuations early and help them become consensus bets.

Reach says its first two funds have returned investors’ capital. What produced those returns?

Kim: We’re no exception to the power-law distribution in venture. Our first fund has been returned 2.2x by literally two investments. Our second fund has been returned 1.2x by one investment. These are cash distributions, by the way.

Especially in the second fund, there’s still remaining value, so we’ll see how high that number gets. One fund-returning exit would be great; two or three would be amazing. That’s what we’re striving for.

How has that experience changed your approach to ownership and follow-on investing?

Kim: We’ve had some great exits where, given how prominent the company is, you might be surprised that our share of the returns wasn’t that large. That’s purely an ownership calculation.

From our first fund to today, we’ve meaningfully increased our initial ownership target. We now try to get as close to 15% ownership upfront as possible.

That means writing slightly bigger checks and reserving relatively less for follow-on investments and more for the initial check. It’s important for the exit math and distribution math.

What role do secondary transactions play in getting liquidity?

We’ve become very proactive and conscientious about liquidity opportunities. Much of our distributions to investors come from secondary sales — selling our shares in a subsequent round, before an actual exit.

Whenever there’s an opportunity, we evaluate it. We consider how long we’ve been in the company, how much we can get out, and how much upside we think remains.

As companies stay private longer, early-stage investors are achieving liquidity much more often through secondary transactions. I like to think we were early to that trend, but it’s certainly mainstream now.

Sometimes, when we see enough upside, we’ll buy secondary shares. GPTZero was an example: After our Series A investment, we bought secondary shares, and I’m really glad we did because it worked out well. For us, we sell more often, but occasionally we buy.

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• ‘Nobody Wanted to Give A Former Principal Money’: How An Educator Built An Edtech AI Startup With $63M From VCs

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All told, startups in Latin America raised a combined $1.3 billion across seed- and growth-stage deals in the three-month period ending Sept. 30. That was up 26% year over year but down 9% from the second quarter.

For perspective, we charted out total investment, color-coded by stage, for the past 12 quarters below.

Of the quarterly total, $757 million went into late-stage and growth deals, up 74% compared to the $435 million that flowed into such deals in the third quarter of 2025. However, that is down 21.3% from the $962 million in late-stage and growth rounds raised by LatAm startups in the second quarter. (Although it’s worth noting that Q2 2026 represented the most raised at that stage since the second quarter of 2022.)

Mexico startups have raised $1.52 billion in venture funding during the first three quarters of 2026, per Crunchbase data. Notably, that’s about 40.7% more than the $1.08 billion Brazil’s startups raised in the same period. This is unusual as Brazil has historically been the largest recipient of venture funding in Latin America.

Still, Brazil continues to attract a broad range of investors.

“Over the past year, we have seen investments into Brazil from firms including , , , and ,” , managing partner of , told Crunchbase News. “For several, this marked either their first investment in Latin America or their first in a long time.”

, Endeavor Catalyst’s vice president and head of Latin America, noted that Mexico drew more venture funding in the first half of 2026 than Brazil. But much of �ѱ�澱����’s funding went to a few startups, he pointed out, while Brazil recorded many deals.

“Investors are concentrating on a few Mexican winners, while Brazil retains the breadth,” Piquet said, adding that Brazil also leads in realized exits.

Table of contents

• Outsized rounds
• An uptick in seed funding
• ‘Another rediscovery moment’
• Methodology
• Glossary of funding terms

Outsized rounds

Several mega-raises took place in Latin America in the third quarter. And notably, the two largest funding deals were not for companies in Brazil or Mexico, which have historically raised the largest share of venture capital in the region. They also weren’t to fintech, which typically has the most funding recipients in the region, but rather to energy-related startups.

, the Chilean project company for ’s Black Giant lithium project, raised $225 million in a July round at a reported $900 million valuation. And Colombia’s , a clean energy company that builds and operates solar power systems for homes and businesses, landed a $129 million Series C in August at a reported $600 million valuation.

�ѱ�澱����’s , an AI-powered financial services company, raised a $125 million Series C in September at a $1.6 billion valuation. led the financing, which included a senior debt funding facility provided by .

And in August, Brazilian fintech brought in $106.9 million in an equity and debt seed round at a $626 million valuation.

Also in August, Brazil’s , an AI-native wealth advisory company, landed $85 million in  what Crunchbase shows is the largest seed funding deal ever raised for a Latin American startup. Founded by , former CTO of , and , founder of , the startup is backed by ,,, and .

An uptick in seed funding

Latin America experienced a marked surge in very early-stage funding totals in the third quarter, largely thanks to the seed rounds mentioned above.

Of the $1.3 billion raised by Latin America’s startups in the third quarter, about 20.5% — or $266 million — was raised across the angel and seed stages.

That’s up 128% from the $117 million raised across those stages in the second quarter of 2026, and up 62% from the $165 million in the same quarter last year.

Just over 22%, or $288 million, was raised at early stages, down 18.9% from $355 million in the second quarter and 34% from $437 million in the same period last year.

We expect the Q3 deal counts to rise somewhat over time; however, as seed rounds in particular are commonly reported weeks or months after they close.

‘Another rediscovery moment’

Latin America is drawing renewed interest from international venture investors, according to Endeavor’s Taylor. He said international VCs were more active in the region, particularly Brazil, during the first three quarters of 2026 than in 2024 and 2025 combined, through both new investments and follow-on funding.

“I joke that investors from the U.S. ‘rediscover’ Latin America every five or six years, and I think we are approaching another rediscovery moment,” Taylor told Crunchbase News.

Endeavor Catalyst recently closed its oversubscribed $320 million fifth fund. Latin America accounts for nearly 40% of its portfolio by both deals and dollars, and Fund V had made 14 investments in the region as of Sept. 22. Taylor also pointed to opportunities beyond Brazil and Mexico, including repeat founders building global businesses from Colombia and emerging companies in Venezuela and Central America.

Liquidity is improving, although acquisitions and secondary transactions are providing more opportunities than public listings, Piquet said. He pointed to approximately 60 private Latin American technology companies that have each raised at least $150 million as a potential pipeline for future IPOs.

“The exit door is open, although it is not primarily opening through IPOs yet,” Piquet said.

Taylor expects more exits could help bring global investors back consistently, with potential listings by companies such as , or contributing to another “rediscovery moment” in 2027.

International investors remain interested in Latin America but have become more selective about deploying capital, according to of . Firms with a longstanding presence in the region remain engaged, while many that entered during the 2020–2021 investment boom have shifted toward AI opportunities elsewhere and are concentrating on existing portfolios, she noted.

“Global investors are increasingly investing behind themes rather than geographies,” she said, putting Latin American startups in more direct competition with companies in the U.S. and other markets.

Investor interest is increasingly centered on AI-native businesses and financial infrastructure, particularly stablecoins and cross-border payments. Gadala-Maria said more founders are targeting global markets from the outset, marking a departure from the previous wave of startups that adapted established business models to underserved local markets.

“Increasingly, we’re seeing founders build globally competitive technology companies from Latin America, rather than necessarily for Latin America,” she said.

Gadala-Maria agrees that Brazil and Mexico remain the region’s largest markets, with Brazil offering a deeper, more mature startup ecosystem and Mexico providing substantial room for financial services innovation. She pointed to Argentina as an overlooked market, citing its strong technical talent and founders building companies for global customers.

Correction: Details regarding Kapital’s Series C were updated. The deal was a debt and equity raise.

Related Crunchbase queries:

Methodology

The data contained in this report comes directly from Crunchbase, and is based on reported data. Data is as of Oct. 5, 2026.

Note that data lags are most pronounced at the earliest stages of venture activity, with seed funding amounts increasing significantly after the end of a quarter/year.

Please note that all funding values are given in U.S. dollars unless otherwise noted.

Crunchbase 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 Crunchbase long after the event was announced, foreign currency transactions are converted at the historic spot price.

Glossary of funding terms

Seed and angel consists of seed, pre-seed and angel rounds. Crunchbase also includes venture rounds of unknown series, equity crowdfunding and convertible notes at $3 million (USD or as-converted USD equivalent) or less.

Early-stage consists of Series A and Series B rounds, as well as other round types. Crunchbase includes venture rounds of unknown series, corporate venture and other rounds above $3 million, and those less than or equal to $15 million.

Late-stage consists of Series C, Series D, Series E and later-lettered venture rounds following the “Series [Letter]” naming convention. Also included are venture rounds of unknown series, corporate venture and other rounds above $15 million. Corporate rounds are only included if a company has raised an equity funding at seed through a venture series funding round.

Technology growth is a private-equity round raised by a company that has previously raised a “venture” round. (So basically, any round from the previously defined stages.)

Illustration:

Overall, investors put $38.5 billion into reported seed- through growth-stage financings for countries in the region in Q3, per Crunchbase data. Of that, a majority went to AI-focused companies, echoing the trends we’ve seen globally.

Deal counts, meanwhile, were relatively flat. That indicates concentration of capital into favored startups remains pronounced but is not intensifying.

Table of contents

• An AI-driven quarter
• China leads by far in country-by-country breakdown
• Late stage
• Early stage
• Seed
• A big quarter for China
• Methodology
• Glossary of funding terms

An AI-driven quarter

Around 55% of investment — an estimated $21 billion — went to AI-focused companies. Total funding is down substantially from the prior quarter, which was boosted by a $7.4 billion financing for China’s , but still the second-highest tally on record.

For Q3, a couple of extra-large rounds bolstered the AI investment tally. The largest went to Beijing-based foundational model company , which secured $3.5 billion in July at a reported $35 billion valuation.

, the AI spinout of China-based short video platform , was the second-biggest fundraiser. The generative video startup raised around $3 billion in a July financing that included and .

China leads by far in country-by-country breakdown

China was the leading Asian destination for venture investment by a very wide margin.

Per Crunchbase data, roughly $27 billion — or 70% of all Asian startup funding in Q3 — went to China-based companies. India was a distant second, with $2.9 billion, followed by Singapore, with $2.5 billion.

For perspective, below we charted third-quarter startup funding tallies for the six countries with the largest totals.

Late stage

Most capital went to late- and growth-stage funding rounds.

Per Crunchbase data, investment at this stage totaled around $20 billion in Q3. That’s down a bit from the prior quarter but nearly double year-ago levels and the second-strongest showing in four years.

Multiple jumbo rounds kept the total high. The largest was Moonshot AI’s aforementioned $3.5 billion Series F.

Several others raised financings in the multiple hundreds of millions. Shenzhen-based , a provider of robotics hardware and software, for instance, picked up $400 million in a September Series C. And Hong Kong-based , an e-commerce fintech platform, secured $300 million in Series C funding as it eyes an IPO.

Early stage

Early-stage investment drifted lower in Q3 but remained at historically high levels.

Per Crunchbase data, financing for startups at the Series A and Series B stages totaled $13.6 billion for the just-ended quarter. That’s a decline of 28% from the prior quarter but up 65% from year-ago levels.

Seed

Reported seed funding hit its highest level in years, boosted by investor enthusiasm around AI.

In total, investors poured $4.9 billion into reported seed and angel deals across Asia, per Crunchbase data. That’s up around 22% from the prior quarter and more than double year-ago levels.

A big quarter for China

Overall, Q3 was a robust period for venture funding to China-based companies, with far smaller sums going to other Asian startup hubs. Funding to startups based in India and Singapore was down significantly quarter over quarter, while Israel’s investment totals declined slightly.

We’ll keep an eye out in the coming months to see if this divergence of fortunes persists.

Related Crunchbase query:

Related reading:

• Crunchbase Data: Q3 2026 Posted A Record Count Of Billion-Dollar Rounds As The Global AI Race Heats Up

Methodology

The data contained in this report comes directly from Crunchbase, and is based on reported data. Data is as of Oct. 5, 2026.

Note that data lags are most pronounced at the earliest stages of venture activity, with seed funding amounts increasing significantly after the end of a quarter/year.

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

Glossary of funding terms

Seed and angel consists of seed, pre-seed and angel rounds. Crunchbase also includes venture rounds of unknown series, equity crowdfunding and convertible notes at $3 million (USD or as-converted USD equivalent) or less.

Early-stage consists of Series A and Series B rounds, as well as other round types. Crunchbase includes venture rounds of unknown series, corporate venture and other rounds above $3 million, and those less than or equal to $15 million.

Late-stage consists of Series C, Series D, Series E and later-lettered venture rounds following the “Series [Letter]” naming convention. Also included are venture rounds of unknown series, corporate venture and other rounds above $15 million. Corporate rounds are only included if a company has raised an equity funding at seed through a venture series funding round.

Technology growth is a private-equity round raised by a company that has previously raised a “venture” round. (So basically, any round from the previously defined stages.)

Illustration:

Two decades later, Herrin is building a business around the marketing problems she encountered along the way. She started in 2025 to help consumer brands decide which products to promote and prepare their campaigns. The startup has now raised $5 million in seed funding, it tells Crunchbase News exclusively.

led the round, joined by and angel investors including former and current leaders.

Marklo helps consumer brands plan marketing campaigns using their sales, inventory and past marketing data. Its software shows which promotions drove sales, suggests what products to promote next and uses AI to draft campaign briefs and organize tasks.

While Marklo is still pre-revenue, more than 100 brands are already using its software in a pilot, according to Herrin. Those brands include , , , and .

The Burlingame, California-based company is now opening its software to the public ahead of the holiday shopping season. It plans to use its new funding to hire engineers, develop the product and expand customer support.

Planning campaigns

To decide what to promote next, marketers first need to understand what drove past sales. That can be a challenging endeavor when sales, inventory and marketing records all sit in separate systems.

Marklo collects that information from Shopify and services such as Klaviyo, , and , then puts past launches, promotions and sales into a calendar. Teams can see, for example, whether a rise in sales attributed to paid advertising coincided with a new product launch or a widely shared social post — factors they might miss when reviewing each service separately, Herrin said. Marklo can then draft a campaign plan and create related tasks for the team to review, edit and assign.

Using those records, along with competitors’ promotions and social media trends, Marklo suggests what a brand should market next. It also considers what the retailer has in stock and when a promotion would run.

From there, teams can use the software to plan campaigns, draft marketing materials and assign work, with suggested campaigns and reports also delivered through or email.

Herrin said the lack of broader-picture context with other AI tools frustrated her. For example, a tool might identify a Fourth of July sale as a successful promotion and suggest repeating it.

“Hey, no, I can’t. It’s not Fourth of July. We don’t have the inventory anymore,” she recalled thinking.

In one case, Herrin described how Marklo identified a color trending on social media and a matching handbag a retailer had in stock but hadn’t promoted recently. It offered to plan a post based on one that had performed well before.

Latico Leathers offers another example of how a brand uses Marklo. The company used the software to plan a month’s worth of marketing in one day, a process that had previously taken most of a week across meetings, spreadsheets and five tools, according to Herrin.

In the end, humans review and approve Marklo’s proposed work. The company says it does not use customer data to train AI models.

As for its revenue model, Marklo plans to charge a monthly subscription fee, with additional charges based on usage. For now, brands can install and try it for free.

“I’m very passionate about small and medium businesses, and I want to make it accessible to every single brand that runs on Shopify,” Herrin told Crunchbase News in an interview, “so that they can operate like a big brand.”

A change of direction

The decision to build Marklo followed a change in how Herrin thought about Stella & Dot’s future.

That company began as a way for women to earn money on their own schedules by hosting trunk shows in their own homes. It expanded into apparel and skincare and paid out more than $500 million to its sellers, Herrin said.

“For me, it was never about the jewelry,” she told Crunchbase News.

When COVID-19 put a stop to in-home gatherings, business dropped 80% almost overnight. Herrin also realized that women who might once have signed up to sell Stella & Dot products suddenly had other options. They could promote multiple brands as influencers or open their own Shopify stores.

She described Stella & Dot as “the COVID victim that had pre-existing conditions.”

Rather than rebuild the old model, Herrin sold the businesses and brands separately. Later, she bought back the Stella & Dot brand to sell through a different channel and test Marklo.

She was also reconsidering what she wanted to do next. As she approached her 50th birthday, Herrin questioned whether she would choose to start the same business again.

“As an entrepreneur, you don’t just start a business; you start a life,” she said.

She still wanted to help people build businesses. What had changed was the problem she wanted to solve: Opening an online store had become easier, but managing its marketing still meant gathering information from several systems and coordinating the next campaign.

“The mission was the same, but the solution needed to evolve,” Herrin said.

A return to venture capital

For Marklo, Herrin also returned to venture funding after relying more on profits to grow Stella & Dot.

She had raised venture capital for her first company, which became , but came away feeling that it had raised too much money. She took a different approach with Stella & Dot, building it with about $2 million in capital and a focus on profitability.

“Here’s a new growth strategy,” Herrin recalled thinking. “How about profits?”

With Marklo, she wanted to hire engineers and develop the software faster. Its 11-person team includes engineers who previously worked at Shopify and Google. She also sought investors with commerce experience.

“Raising capital isn’t just about having money for expenses,” Herrin said. “It’s about bringing a brain trust together.”

Experience as ‘the customer she’s building for’

, founder and managing partner of Forerunner Ventures, said Herrin’s experience building Stella & Dot was a central reason for backing Marklo.

“Jessica uniquely has been the customer that she’s building for right now at every stage, from starting a brand to having a brand at scale,” Green told Crunchbase News in an interview. That experience gives Herrin firsthand knowledge of where teams lose time, which decisions affect profitability and what brands need before trusting new technology, she added.

While AI in general makes it easier to produce marketing content, Green sees the greater opportunity in helping brands decide on what exactly to promote, as well as in understanding the impact on margins and how to grow in ways consistent with their identity. Marklo, she said, incorporates the judgment needed to turn business data into useful recommendations.

The opportunity comes as AI is taking a larger share of investment in the broader sales and marketing sector. Startups in sales, marketing and customer relationship management raised $7.5 billion across 830 rounds globally this year through mid-September, with most of that investment going to companies in Crunchbase’s AI-related categories. Funding is on pace to finish below 2025’s $11.1 billion, while deal volume could fall for a fourth straight year — a sign that investors are concentrating their bets in fewer companies.

“It’s one thing to collect the information; it’s another thing to understand how to present it and how to recommend an action against it,” Green added.

The investor also pointed to Marklo’s ability to serve businesses at different stages, noting that coordination becomes more complex and information harder to share as brands grow. As such, the prospect of software that can grow alongside its customers was another draw.

Green said she also valued Herrin’s decision to develop Marklo alongside brands already using it, giving the company customer feedback before its broader launch.

“I like the fact that she built this product while it was being used,” she said.

Related Crunchbase queries:

Related reading:

• Sector Snapshot: AI Takes A Growing Share Of Sales And Marketing Startup Funding

Illustration:

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.

As the AI startup boom progresses, investors appear to be leaving few niches unfunded. That was apparent in this week’s lineup of large funding rounds, which featured AI infrastructure providers, a foundational model developer, a content protection platform for the AI age, and other AI-focused startups among the top investment recipients.

The biggest investment, $2 billion, went to , a spinout focused on cloud and power infrastructure that is hoping to benefit from the AI buildout. Other large rounds went to , developer of a fast-growing new model, and , a quantum computing startup.

1. , $2B, cloud and power infrastructure: Axiom Solutions International, a private cloud and power infrastructure company spun out of manufacturing services provider , secured $2 billion in new financing. and provided the strategic investment by purchasing shares of Austin-based Axiom from Flex at an initial enterprise value of $37.5 billion. Flex says it plans to separate Axiom into an independent publicly traded company early next year.

2. , $870M, foundational AI: TypeSafe AI, developer of Jev, a recently launched AI model with a large and growing early following, raised $870 million in new funding with as the largest investor, according to a . also participated in the round, which reportedly set a $7.5 billion valuation for San Francisco-based TypeSafe.

3. , $475M, quantum computing: Pasadena, California-based Oratomic, a startup working on fault-tolerant quantum computers, raised $475 million in fresh funding led by , , , , and . The company previously raised $300 million in a July financing.

4. , $400M, data and content protection: SignSplit, a provider of tools for protecting, licensing and contributing real-world human data and other forms of human contribution, emerged from stealth with $400 million in seed funding. backed the round, setting a $1 billion valuation for the New York-based company, which was founded in 2024.

5. (tied) , $250M, AI for engineering: Vinci, developer of an AI computational platform for hardware engineers to design products, closed on $250 million in Series B funding at a $1.5 billion valuation. , and led the round for the Palo Alto, California-based company.

5. (tied) , $250M, micro-manufacturing: Emeryville, California-based Atomic Machines, a startup working on AI-native digital manufacturing systems to build micro-machines directly from code, emerged from stealth and said it has raised $250 million to date from a long list of investors.

7. , $225M, energy distribution: Voltus, provider of a distributed energy platform aimed at bolstering grid flexibility, picked up $225 million in Series D funding. , and led the financing for the San Francisco-based startup.

8. (tied) , $200M, fusion: Knoxville, Tennessee-based Type One Energy, a developer of fusion energy technology, secured $200 million in Series B financing led by and .

8. (tied) , $200M, insurance: Ledgebrook, an AI-powered specialty insurance platform, closed on $200 million in equity financing co-led by and . The round brings total funding to date for Boston-based Ledgebrook to around $315 million, per .

8. (tied) , $200M, AI evaluation: Arena, provider of a platform for evaluating AI models, pulled in $200 million in Series B funding and said it has exceeded a $100 million annual revenue run rate. and led the round, which set a $3.1 billion valuation for the company.

Methodology

We tracked the largest announced rounds in the Crunchbase database that were raised by U.S.-based companies for the period of Oct. 3-9, 2026. Although most announced rounds are in the database, there may be a small time lag, as some rounds are reported late in the week.