Several multibillion-dollar megadeals drove the spike in first-quarter investment. That signals investors aren’t just paying for research anymore, but betting on companies that are ready to scale up and put their AI technology into actual cars people can buy or hail.

So far in 2026, we鈥檝e seen a shift to a small number of autonomous vehicle companies capturing a disproportionate share of global capital, with a handful of giants, including ,听 and , getting the lion鈥檚 share of funding.

The broad trend: It appears that investors are no longer spreading small bets across dozens of startups. Instead, they are pouring billions into the three or four players they believe will own the market. And while North America remains the largest hub for overall funding volume, the Asia-Pacific region 鈥� specifically China 鈥� is seeing the fastest growth in deployment. Chinese startups are also raising some of the largest rounds in the space.

The numbers: Autonomous vehicle startups raised a record $21.4 billion across 34 deals through April 15, . That鈥檚 up a staggering 262.17% compared to the $5.9 billion raised across 99 investments globally in all of 2025. It鈥檚 also about 77% higher than the $12.1 billion raised across 127 deals in 2024.

Noteworthy deals

Exactly three-fourths of the $21.4 billion raised in 2026 thus far is attributable to Mountain View, California-based Waymo鈥檚 raised in February. , , and co-led the financing, which was raised at a staggering $126 billion valuation.

But it wasn鈥檛 the only outsized round.

San Diego-based Shield AI landed a $2 billion Series G round co-led by and . Its valuation jumped to $12.7 billion.

And London-based Wayve raised a $1.3 billion Series D round co-led by , and , achieving an $8.6 billion valuation.

Interestingly in 2025, three of the four largest autonomous vehicle rounds were raised by Chinese companies: an $897.7 million Series C by ; a $600 million Series D by , and $527.8 million by .

IPO outlook

We didn鈥檛 see any IPOs in the space in 2025, but some are on the horizon for this year.

Beijing-based confidentially in March. Backed by , and , it is seeking a valuation above $14 billion.

secured $24.7 million in pre-IPO funding in March and is as it expands its AI-led logistics projects.

Because Waymo is a subsidiary of Alphabet (), it doesn’t need to go public for cash, but industry observers are increasingly discussing a potential spinoff. With a $126 billion valuation, it would instantly become one of the most valuable transportation companies in the world if it hit the public market.

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In fact, SA国际传媒 data shows the extent to which venture funding this year has been a case of more capital concentrated into a select few companies and a single industry. Last quarter, a handful of large, well-funded AI companies, almost all based in the U.S., captured the vast majority of venture dollars, even as global startup deal count fell.

AI takes 80% of global venture funding

AI startups for the first time captured half of global venture funding in Q4 2024. Since then, that percentage has hovered around 50% 鈥� until Q1 of this year, when 鈥檚 record-setting round, along with a small handful of other enormous deals, pushed AI鈥檚 share to 80% of the quarterly funding total.

Top 4 vs. everyone else

It wasn鈥檛 just that AI as an industry captured the lion鈥檚 share of venture funding last quarter. Just four companies took nearly two-thirds of the entire pie, SA国际传媒 data shows.

Four of the five largest venture rounds ever recorded were closed in Q1 2026, with frontier labs OpenAI ($122 billion), ($30 billion), ($20 billion) and self-driving company ($16 billion) collectively raising $188 billion, or nearly 65% of global venture investment in the quarter.

Deal count falls even as dollars surge

And while last quarter set an all-time record for venture dollars invested, more money went to fewer companies, continuing an overall downward trend for deal count we鈥檝e seen since the beginning of 2021.

That was the case not just in North America, where dollars invested surged 190% year over year, even as deal count dropped 26%. It also held true in Europe and Latin America. Only Asia saw a modest 5% bump in deal count along with more dollars invested.

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Related reading:

• Q1 2026 Shatters Venture Funding Records As AI Boom Pushes Startup Investment To $300B
• North America Q1 Funding Surges Across Stages To Record Level
• Global Investors Help Boost Latin America鈥檚 Late-Stage Funding Boom In Q1
• China Leads Asia鈥檚 Startup Funding To Its Highest Level In More Than 3 Years
• AI Drives Europe鈥檚 Second Straight Quarter Of Funding Gain As Deal Volume Falls Sharply

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“We have this saying between the two of us,” explains CEO , referring to CTO and co-founder . “If there鈥檚 anything he can鈥檛 do, I can try to figure it out. And if there鈥檚 something I know I can鈥檛 do, I know he can do it.”

That combination 鈥� a blend of deep technical tradecraft and business intuition 鈥� first bore fruit in 2020 with the launch of a digital onboarding startup called . They went on to scale that venture (raising just 1.5 million EUR) before it to the Canadian identity verification company in under two years for more than $50 million.

After the sale, the pair took a brief hiatus before “getting the band back together” to start Spektr in the summer of 2023. This time, they brought along key team members from their previous journey 鈥� CPO and CRO 鈥� to tackle a persistent, expensive problem: the manual drudgery of financial compliance.

Put simply, their new venture, Spektr, provides infrastructure for compliance teams in financial services. It combines configurable workflows with AI agents that execute tasks such as document reviews, ownership mapping and risk analysis 鈥� work that has traditionally been manual and time-intensive.

Today, Copenhagen-based Spektr has raised $20 million in a Series A funding round led by , the company tells SA国际传媒 News exclusively.

Existing backers , and Tech also participated in the financing, which brought Spektr鈥檚 total raised to just under $26 million. The company declined to reveal its current valuation, saying only that it is a significant step up from its February 2024 seed round.

Building bridges

Compliance remains a stubbornly manual field. Analysts spend countless hours cross-referencing documents, researching registries and manually assessing risk. Spektr鈥檚 founders saw a massive misalignment between this sort of rule-based labor and what modern AI was suddenly capable of achieving.

The startup aims to serve as a bridge between the two worlds through its layer of agentic structures that sit atop old-school processes for onboarding, risk assessment and monitoring sanctions lists.

鈥淢ost compliance tools help you manage workflows,鈥� Skarnager said. 鈥淪pektr actually executes the work inside those workflows.鈥�

Its AI agents don鈥檛 just assist, he added. They perform specific compliance tasks end-to-end while maintaining 鈥渇ull transparency鈥� and a human-in-the-loop configuration, so teams 鈥渟tay in control.鈥�

Unlike legacy platforms that offer incremental improvements, such as better data organization, Spektr鈥檚 agents actually perform the analysis, said Skarnager.

“It鈥檚 not just about gathering data,” the CEO told SA国际传媒 News in an interview. “It鈥檚 about making the determination so the human can make the final decision.”

Momentum and market fit

Since launching “spektr 2.0” last August, which fully integrated these agent capabilities, the company has seen a boom in customer adoption.

“Clients really relate to that way of thinking,鈥� Skarnager said. “They鈥檙e used to building an onboarding journey, but now, in the same tool, they have the ability to create agents inside that same structure.”

Companies operating in this space include , and .

These systems play an important role in managing workflows, cases and data across the compliance lifecycle, Skarnager noted.

But, he said, Spektr sits one layer deeper.

鈥淲e automate the underlying execution of compliance work itself through specialized AI agents,鈥� he said.

Scaling the vision

With a headcount of 45 and growing, Spektr is currently focused on the heavy lifting required to serve banks and Tier 1 financial institutions. While the company is rooted in Copenhagen, its footprint is increasingly global.

Its new capital is earmarked for expansion. Plans include building out its engineering team to manage the complex needs of large banks and fintechs. The company also plans to open offices in London and New York to better serve a client base that already includes clients such as , Santander Leasing, , , and 鈥渕ajor鈥� U.S. marketplaces.

NEA partner believes that in a market where AI can mass-produce functionality, Spektr wins through “taste” and deep domain expertise.

The co-founders possess a “rare level of cohesion” and “operate at an instance speed,” allowing them to forgo slides for live demos that directly address use cases, according to Pappas.

Spektr鈥檚 product is architected for a shift where “software screens everything continuously” and experts “handle the exceptions,鈥� he said.

鈥淭his end-to-end automation leads to better decision making and error reduction,” he wrote via email.

Rather than forcing a total replacement of legacy tech at once, Spektr is “the only system that can coexist with existing solutions,” Pappas believes, providing the orchestration needed until “buyers can easily just switch over to spektr to handle everything in one place.”

Fintech startups, particularly those that apply AI to traditionally manual or burdensome processes, have benefited from increased investment in recent quarters. Total global funding to

VC-backed financial technology startups totaled $53.8 billion in 2025, per SA国际传媒 . That鈥檚 a more than 29% increase from 2024鈥檚 total of $41.6 billion raised.

Related reading:

• Fintech Startups Globally Raise More Money In Far Fewer Deals In Q1 2026

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In October 2024, my co-founders and I set out to make our Ph.D. research useful in the real world. We had built AI models that could interpret medical images such as X-rays and CT scans across tens of thousands of potential diagnoses, generating comprehensive radiology reports that mirror how radiologists reason in clinical practice. At a time when AI in radiology was limited to flagging a handful of specific conditions, this marked a fundamental shift.

Less than a year later, we faced a critical fork in the road: raise venture capital and continue independently, or accept an acquisition offer from , the world鈥檚 largest radiology practice.

The conventional wisdom in tech is that real ambition means staying independent. But in asking ourselves what it would truly take to transform healthcare, the answer was different.

Clinical AI is highly regulated with long sales cycles and complex stakeholder dynamics, where structural advantages tend to harden market positions and compound over time. We decided that joining forces 鈥� carefully structured to protect our velocity 鈥� would dramatically improve the odds that we realize our mission of significantly increasing the world鈥檚 access to healthcare.

Research success is not clinical readiness

During my Ph.D., I trained radiology AI foundation models on what, at the time, felt like massive research-scale datasets; tens to hundreds of thousands of studies. These models make for strong academic demonstrations, prototyping new capabilities across a range of tasks. In real clinical settings, however, they would not yet have met the standards required for production-level safety and consistency in patient care.

Despite the persistent narrative that AI will make radiology obsolete, the reality is that the problem is extraordinarily difficult. A single CT study, for example, can contain 10 high-resolution volumetric series, effectively 3D videos. Add prior studies for the same patient, and you can have a billion pixels of data.

Those billion pixels encode entire medical textbooks worth of information. On top of this, real-world radiology is defined by edge cases where rare but critical pathologies are encountered regularly. We learned a hard truth early on: Models that work in controlled research environments often fall apart when exposed to real-world complexity.

Think about self-driving cars. A decade ago, progress looked impressive. But the real world kept introducing new failure modes. After more than a decade of significant capital investment, only a handful of companies have approached true reliability.

Components required to build reliable models

Key patterns emerged. The companies that made the most progress controlled the entire system and achieved scale early. They owned the vehicles, the sensor stack, the data collection pipeline, the simulation environments, and the deployment infrastructure. That integration, operating at scale, allowed them to continuously collect rare edge cases, retrain models, validate improvements and redeploy safely.

Radiology is no different. Success in the real world requires massive, diverse historical datasets and live data feeds that continuously surface rare edge cases and distributional shifts. It requires vast clinical resources and operational infrastructure to redesign clinical workflows around AI, engineer systems that perform reliably at scale, conduct large-scale research studies, secure regulatory clearance, refine models safely, and continuously monitor performance post-deployment.

Additionally, frontier language models have clearly demonstrated that continuous, high-quality and extensive human feedback is the secret sauce in making models useful. This is no different in radiology. In a world where radiology reports are drafted by AI, every draft must be reviewed, edited and signed off by a human radiologist.

Those edits become high-quality signals that can be leveraged for improving the AI models. Better models elevate radiologists’ accuracy and capacity. Improved radiologist accuracy increases the quality of future training data. Increased capacity allows radiologists to take on additional contracts.

That, in turn, generates more data and high-quality corrections, setting a powerful flywheel in motion. Access to this correction data is rare in AI and can only work meaningfully at a massive scale. These capabilities would be incredibly difficult to achieve as a standalone AI startup.

In healthcare, growth follows evidence

In healthcare, trust is hard earned. It rests on demonstrated clinical efficacy, reliability, security and regulatory rigor. For a health system or radiology group to adopt technology from a new startup, particularly in workflows that directly affect patient care, requires rigorous, real-world evidence.

Evidence in healthcare is not generated in small pilots. It is built through sustained performance across diverse sites, patient populations, modalities and edge cases. If a system proves itself within the world鈥檚 largest radiology practice, it establishes credibility across multiple dimensions at once 鈥� efficacy, reliability, security and scalability.

In sectors where lives are at stake and the goal is to build something that endures, the way to build it is from within the system you鈥檙e trying to improve. Selling early didn鈥檛 shorten our journey, it accelerated it. It gave us the foundation required to deliver on our mission of significantly increasing the world鈥檚 access to healthcare.

is the CEO and co-founder of , the AI business unit of at . During his undergraduate studies in physics and electrical engineering, he became driven by a singular mission: increasing the world’s access to healthcare through technology. Convinced that AI was the most promising technology to make this happen, but not yet good enough for real-world clinical use, he pursued a Ph.D. in AI at where he focused on foundation models for radiology. His doctoral work produced Merlin, a 3D vision-language model for CT interpretation published in 鈥淣ature鈥� in 2026 and recognized as one of the most important papers in the field.

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And as was the case in the Q4 as well, Q1 was well above the prior five quarters by funding amounts, signaling that European venture funding may be gaining momentum.

Table of contents

• AI above 50%
• UK and France grew YoY
• Europe by stage
• In summary
• Methodology
• Glossary of funding terms

Still, Europe saw more capital going into fewer companies in Q1, with deal volume plummeting 40% year over year. Much of the decline was at seed stage (down 44%) and early stage (down 30%), while late-stage deal volume was in-line with the previous four quarters.

AI above 50%

Funding to Europe-based AI startups increased significantly last quarter, reaching $9.2 billion, or more than half of total venture funding to the region. That marks the sector鈥檚 highest proportion in a quarter on record.

The largest four rounds to startups based in Europe in Q1 were for AI-related companies. Data center builder , autonomous driving developer , and frontier lab for physical AI raised more than a billion each, and AI legaltech 鈥檚 funding totaled more than $500 million.

UK and France grew YoY

Startups from the U.K. and France raised more funding in Q1, totaling $7.4 billion and聽 $2.9 billion, respectively. Germany-based startups raised $1.9 billion, flat year over year.

France has emerged as the European leader for AI frontier labs. Last quarter, it saw Paris-based , founded by former AI chief , raise $1 billion in the continent鈥檚 largest seed funding round on record. The deal also marked only the second billion-dollar-plus funding deal for a European frontier lab, following s $2 billion round last year.

Europe by stage

In Q1, late-stage funding to Europe-based startups nearly doubled from a year ago. The largest rounds were across a variety of sectors, including AI hardware, fintech, agentic AI, productivity software, sensors, defense, e-commerce and energy.

A total of $9.2 billion was invested at late-stage across 83 deals, up 91% by amounts year over year.

Early-stage funding to the region鈥檚 startups fell from a year earlier 鈥� by around 20% 鈥� SA国际传媒 data shows. Early-stage investment totaled $5.3 billion in Q1 across more than 240 funding rounds. Within early-stage funding, larger Series A rounds predominated in semiconductors, energy and healthcare.

Seed funding reached $3.1 billion in Q1 across more than 790 deals. The funding total was up 50% year over year, but largely due to the $1 billion round for Advanced Machine Intelligence.

In summary

Larger rounds into critical sectors in AI drove European startup funding up in Q1. A mix of Europe- and U.S.-based investors led the largest fundings last quarter into AI infrastructure, frontier labs, autonomous systems and applications.

Overall, Europe is in-line with global trends as capital concentrates into the largest deals in sectors that are surging due to AI.

Related SA国际传媒 query:

Methodology

The data contained in this report comes directly from SA国际传媒, and is based on reported data. Data is as of April 2, 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. SA国际传媒 converts foreign currencies to U.S. dollars at the prevailing spot rate from the date funding rounds, acquisitions, IPOs and other financial events are reported. Even if those events were added to SA国际传媒 long after the event was announced, foreign currency transactions are converted at the historic spot price.

Glossary of funding terms

Seed and angel consists of seed, pre-seed and angel rounds. SA国际传媒 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. SA国际传媒 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 鈥淪eries [Letter]鈥� 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 鈥渧enture鈥� round. (So basically, any round from the previously defined stages.)

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Overall, investors put $27.4 billion to work across seed- through growth-stage financings for Asian companies in Q1, per SA国际传媒 data. That鈥檚 up about 20% from the prior quarter and nearly double year-ago levels.

Total funding also hit its highest level in more than three years, as charted below.

Funding went to bigger rounds, not more of them. Per SA国际传媒 data, deal counts were flat with the prior quarter and up incrementally from prior year levels. In general, deal counts haven鈥檛 fluctuated widely from quarter to quarter over the past few years, as seen in the chart below.

Table of contents

• Most gains go to China
• Funding rose across stages, with most going to later stage
• Early stage was strong too
• Seed also showed an upswing
• A record quarter for AI
• Looking up
• Methodology
• Glossary of funding terms

Most gains go to China

An estimated $16.5 billion 鈥� or 60% of all Asian startup funding 鈥� went to China-based startups in Q1. It was also the third consecutive quarter for increased Chinese venture funding, which hit a multiyear low in the first half of 2025.

AI funding drove the gains in China. The quarter鈥檚 largest rounds all went to AI-focused companies, including foundational model startup , agentic AI company , and AI-enabled robot developer .

After China, the next-largest venture funding recipient in Asia was India, with $3.8 billion in reported Q1 investment, the highest number in the past four quarters. A big chunk of the funding went to the quarter鈥檚 largest equity round, a $600 million financing for AI systems developer .

Below, we chart out venture funding by country to seven leading investment hubs in Asia, showing how regional funding has trended since 2023.

Funding rose across stages, with most going to later stage

Later-stage, early-stage and seed funding all rose sequentially in the first quarter.

Of these, later-stage and technology-growth deals captured the highest share of funding, estimated at $11.7 billion in Q1. The quarter鈥檚 largest late-stage round by a long shot was a $2 billion Series C for Singapore-based data center company .

Overall, it was the largest later-stage tally in five quarters, as charted below.

Early stage was strong too

Early-stage investment also rose in Q1, hitting its highest point in two years.

Per SA国际传媒 data, an estimated $11.2 billion went to Asian companies around Series A and Series B stages. That鈥檚 nearly double year-ago levels and up about 17% from the prior quarter, as charted below.

Seed also showed an upswing

Investors also poured more money into seed-stage companies, with AI as a core driver.

Around $3.6 billion went to reported seed and angel rounds in Q1, up 85% year over year and 45% quarter over quarter. Reported deal counts dipped a bit, indicating concentration of capital among a smaller subset of hot startups. However, we expect this number to rise over time, as seed deals are often added to the dataset weeks after they close.

A record quarter for AI

It would be remiss to close out a quarterly report these days without some mention of how much investment went to artificial intelligence.

For Q1, Asian startups in AI-related categories pulled in about $11.2 billion, per SA国际传媒 data, the highest sum we鈥檝e tracked to date.

Looking up

Overall, the quarterly numbers show increasing momentum in China鈥檚 startup ecosystem, fueling much of the rising funding totals in Asia. Investment to startups in India, Singapore and South Korea also rose sequentially in Q1, while funding to Israel declined some.

In sum, it was a solid quarter, peppered with signs of optimism about the regional startup pipeline going forward.

Methodology

The data contained in this report comes directly from SA国际传媒, and is based on reported data. Data is as of March 31, 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. SA国际传媒 converts foreign currencies to U.S. dollars at the prevailing spot rate from the date funding rounds, acquisitions, IPOs and other financial events are reported. Even if those events were added to SA国际传媒 long after the event was announced, foreign currency transactions are converted at the historic spot price.

Glossary of funding terms

Seed and angel consists of seed, pre-seed and angel rounds. SA国际传媒 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. SA国际传媒 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 鈥淪eries [Letter]鈥� 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 鈥渧enture鈥� round. (So basically, any round from the previously defined stages.)

Illustration:

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

While no billion-dollar rounds led this week鈥檚 list, we nonetheless saw a variety of startups in industries ranging from semiconductors to aerospace to biotech raise sizable rounds. The week鈥檚 biggest deal was $400 million for SiFive, a semiconductor startup challenging incumbent with chip designs built on an open rather than proprietary standard.

1. , $400M, semiconductors: San Mateo, California-based semiconductor startup SiFive raised a $400 million Series G round led by . SiFive makes the blueprints used by companies such as to develop their own internal chip designs, on an open standard called RISC-V. CEO Reuters he expects the raise to be SiFive鈥檚 last funding round before an IPO, though didn鈥檛 say when an offering would take place.

2. , $200M, aviation: Hermeus, an El Segundo, California-based startup developing autonomous military aircraft, raised $200 million in equity in a -led round. The company, which is developing what it says will be the fastest unmanned defense aircraft, also raised $150 million in debt as part of the round, which pushes its valuation to $1 billion. Other investors in the deal include , and

3. $137M, biotechnology: San Diego-based Sidewinder, a biotech startup developing cancer drugs to target difficult-to-treat tumors, raised a $137 million Series B led by and . The company is developing聽next-generation cancer drugs called antibody-drug conjugates, or ADCs, which are designed to act like 鈥済uided missiles鈥� by using engineered antibodies to deliver toxic payloads directly into tumor cells. The company said its new funding will be used to push its lead drug candidates into clinical trials.

4. , $125M, AI infrastructure: Palo Alto, California-based Aria Networks raised $125 million in a -led Series A funding round. The company develops an AI-driven networking platform that monitors, analyzes and optimizes data center performance.

5. , $111.7M, aerospace: Starfish Space, a Seattle-based startup developing and manufacturing autonomous space vehicles that perform in-orbit, satellite servicing missions, raised $111.7 million. The Series B round was led by , and . Starfish鈥檚 spacecraft dock to satellites already in orbit to service and reposition them. They can also remove defunct satellites and debris from space.

6. (tied) , $100M, biotechnology: Cambridge, Massachusetts-based Stipple Bio raised a $100 million Series A round to advance its precision cancer therapies. The round was led by , and . Stipple aims to develop highly targeted cancer treatments that selectively attack cancer cells while minimizing damage to healthy tissue.

6. (tied) , $100M, health insurance: led the $100 million Series E for Chapter, a New York-based startup offering a Medicare navigation platform that provides advisory services for seniors seeking health coverage. Other investors include 鈥嬧��, and 1.

8. , $85M, fintech: Modus, a Philadelphia-based startup, raised $85 million in a -led seed and Series A round. The startup describes itself as a tech鈥慹nabled audit platform that acquires CPA firms and equips them with AI鈥慸riven audit tools to deliver higher鈥憅uality audits. and also participated in the deal.

9. , $80M, medical devices: and led the $80 million Series C for Menlo Park, California-based Endovascular Engineering, also called E2, which has developed a device called H膿lo for the treatment of venous thromboembolism, or VTE. The company secured clearance for H膿lo in December.

10. , $80M, biotechnology: Boston-based Life Sciences, which aims to develop drugs to promote longevity and find treatments for age-related diseases, says it raised $80 million in Series D funding. The company says it will use the funding to advance human trials of its cellular rejuvenation therapy, called ER-100, which aims to make older, damaged cells act younger again. Investors in the round were not disclosed. The company has previously been backed by , , , and.

Methodology

We tracked the largest announced rounds in the SA国际传媒 database that were raised by U.S.-based companies for the period of April 4-10. 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.

Illustration:

Global venture funding to financial technology startups totaled $12 billion across 751 deals in 2026 as of April 6, per SA国际传媒 . That鈥檚 a 5% increase in dollars raised compared to the $11.4 billion raised across 1,097 鈥� or 31.5% fewer 鈥斅燿eals during the same time period in 2025.

This trend signals larger deal sizes. Indeed, late-stage or growth funding in the first quarter of 2026 totaled $6.9 billion, up 8% compared to $6.4 billion raised at those stages in the 2025 first quarter.

However, sequentially, the $12 billion raised is down 33% compared to the fourth quarter of 2025, when fintech startups raised $17.8 billion globally. The $6.9 billion raised in late-stage or growth funding is also down markedly 鈥� by 43% 鈥� compared to the $12.1 billion raised by fintech startups in Q4 2025.

The trend in the first quarter also mirrors what we saw in 2025 as a whole, with global venture funding to fintech startups climbing to its highest level in several quarters, boosted by later-stage deals.

Total global funding to VC-backed financial technology startups totaled $53.8 billion in 2025, per SA国际传媒 . That鈥檚 an approximately 29.3% increase from 2024鈥檚 total of $41.6 billion raised.

US booms

U.S.-based startups have historically raised more fintech funding than any other country in the world, and the first quarter of 2026 was no different.

Of the $12 billion raised by startups globally, just over half 鈥� or $6.3 billion 鈥� flowed to fintech companies based in the U.S. That was an impressive 47% increase compared to the $4.3 billion raised by U.S. fintech startups in the 2025 first quarter. However, it was down 50% from the $12.6 billion that U.S. financial technology startups raised in the fourth quarter of 2025.

The United Kingdom was the second-largest recipient of venture capital, with startups in the region raising a total of $1.2 billion. India came in third, raising $900 million.

Big deals for unicorns

Several fintech startups raised nine-figure rounds in the first quarter, with some doubling their valuations since their last venture financings.

Predictions marketplace was the largest recipient of capital in the first quarter. In March, the company doubled its valuation to $22 billion in just three months with a $1 billion raise led by . The New York-based startup had just raised $1 billion in Series E funding at an $11 billion valuation in December.

In February, , a digital savings platform, raised $385 million in a Series E funding round co-led by and . The New York-based startup said its new valuation was $2 billion, double it achieved when raising its $125 million Series D round in December 2023.

And in January, , which is building infrastructure for payments with stablecoins, raised $250 million in a Series C funding round led by . Its post-money valuation was $1.95 billion, up 17x from last March.

Investors remain bullish

, partner and head of U.S. at , said his firm has been investing at a slightly slower pace so far in 2026 than in years past. But he cited it as 鈥渕ore a quirk of deal flow鈥� and where it gets conviction, rather than a decision to slow the firm鈥檚 investing pace.

鈥淚t’s certainly true that macroeconomics and geopolitics play a role,鈥� he told SA国际传媒 News, 鈥渂ut mostly we’re just focused on finding high-conviction companies to back.鈥�

QED is extremely bullish on the application layer for AI in fintech and stablecoin opportunities, and has backed several startups that Gerety said 鈥渉arness the power of LLMs with the security and reliability guarantees that finance needs.鈥� (, which raised a $45 million Series B in January and is building an AI assistant for financial advisers, is one of those companies.)

鈥淛ust in the last few months, agents are now actually able to be effective in many processing tasks, but the stakes in finance are too high for LLMs to conquer financial workflows alone,鈥� Gerety said. 鈥淔inance runs on trust, not probability.鈥�

Looking ahead, he said QED remains bullish on fintech overall for the year. Part of the excitement is around the fact that larger companies are 鈥渢ransforming鈥� their operations with agentic workflows, Gerety noted.

鈥淢ore and more transformation is moving from the 鈥榗o-pilot鈥� phase, and we鈥檙e moving into the ‘OpenClaw’ phase, when reasoning agents will start to actually do all the work that was too tedious and slow to be done manually,鈥� he added.

The geopolitical situation will likely hinder some companies from taking the IPO plunge, in Gerety鈥檚 view, although a few companies in QED鈥檚 portfolios are 鈥渂ubbling.鈥�

, partner at , said his firm is on track to make eight to 10 core investments in Seed or Series A companies this year 鈥� about the same number as in previous years.

鈥淲e鈥檙e investing in AI-enabled applications while maintaining patience and focus in our deployment of capital,鈥� he said. 鈥淲e look for durable, enduring businesses that we believe will withstand the current hype cycle and investment frenzy.鈥�

While TTV is investing in AI-enabled companies, Kapur said it also agrees with that 鈥渁n AI reset is coming.鈥�

鈥淢any investors have already made their money by getting in on the ground floor, and others are trying to replicate their success,鈥� he told SA国际传媒 News. 鈥淲e鈥檙e focused on investing in the application layer of AI, and we鈥檙e still in the early days with more widespread prosperity and a democratization of enterprise value creation yet to come.鈥�

In particular, TTV sees the biggest opportunity in early-stage AI-native companies that are solving problems in mission-critical workflows 鈥渨hile building durable moats.鈥�

鈥淭hese platforms will earn the right to be distribution endpoints for financial products 鈥� and are even more valuable in the age of AI,鈥� he said.

He believes we may see some fintech IPOs in 2026, but that they will largely depend on how the potential mega IPOs (from the likes of , and ) perform.

鈥淚f those IPOs underperform, others may opt to stay private longer,鈥� Kapur said.

Looking ahead, he predicts we鈥檒l continue to see accelerated adoption of AI in financial services, first through straightforward applications, then more operationally complex use cases.

鈥淢ore broadly, we鈥檙e watching how the foundational LLMs further move up into the application layer, which is imperative to the long-term sustainability of their business models,鈥� Kapur said. 鈥淲e think financial services and fintech are unique enough categories where de novo startups and standalone businesses will beat platforms building experimental applications.鈥�

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Related reading:

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• Digital Savings Startup Vestwell Lands $385M, Doubles Valuation
• Stablecoin Startup Rain Raises $250M Series C at $1.95B Valuation 鈥� Its Third Round In Less Than A Year
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鈥淚 recognized both the massive potential AI brought to the tax world, as well as the risks to firms and clients by making mistakes and hallucinations,鈥� he told SA国际传媒 News.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

鈥楢 huge, obvious pain point鈥�

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

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

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

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

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

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

Of that total, $761 million went into late-stage and growth deals, up 158% compared to the $295 million that flowed into such deals in the first quarter of 2025. It鈥檚 also up 203% compared with the $251 million in late-stage and growth rounds that were raised by LatAm startups in the 2025 fourth quarter.

Table of contents

• Mexico leads
• Fewer deals
• Some big rounds
• Investor POV
• Methodology
• Glossary of funding terms

Mexico leads

Nearly one-third of the total amount raised in the first quarter went to one startup. Mexico City-based , an online used car marketplace, secured a $300 million Series F financing led by and in February.

Notably, mostly due to that outsized round, Mexican startups outperformed their Brazilian counterparts in the first quarter, raising a total of $404 million compared to Brazil鈥檚 $240 million.

Historically, Brazil has been the powerhouse in Latin America for venture capital funding. But it鈥檚 not the first time in recent quarters that Mexico has topped Latin America鈥檚 largest country. Mexico also raised more funding in the second quarter of 2025.

Overall, the first quarter marks only the second time since Q2 2012 that Mexican startups raised more venture capital than their Brazilian counterparts in Latin America, our data indicates.

Fewer deals

Round counts and total dollars raised decreased substantially sequentially and year over year across angel, seed and early stages. Of the $1.03 billion raised by Latin America鈥檚 startups in the first quarter, less than 9% 鈥� or $92 million 鈥� was raised across the angel and seed stages.

That compares to $161 million raised across those stages in the fourth quarter of 2025, and $152 million in the same first quarter last year.

Just over 17%, or $179 million, was raised at early stages, significantly lower than the $690 million raised in the fourth quarter and $472 million in the same period last year.

We expect the Q1 deal counts to rise somewhat over time, however, as seed rounds in particular are commonly reported weeks or months after they close.

Some big rounds

While Kavak鈥檚 round was the largest financing in Latin America in the first quarter, it was not the only nine-figure raise the region saw in Q1.

Argentinian fintech raised $195 million at a $3.2 billion valuation in March in a round led by .

Other large deals that took place in Q1 include:

• Mexico City-based , a financial app built around stablecoins, raised $70 million in a round co-led by and .
• Buenos Aires-based , a payments infrastructure startup, landed a $55 million Series C financing co-led by and.

Notably, the largest rounds included participation from high-profile global funds, including Andreessen Horowitz, Founders Fund, Sequoia Capital and Insight Partners.

Investor POV

, managing partner of New York-based , said his firm has made more than 60 investments in Latin America since 2022 鈥� steadily increasing its investment pace every year from 11 deals in the region in 2023 to 20 in 2025.

In his view, many of the global investors who began putting more funding into Latin America鈥檚 startups in recent years are still writing checks there. However, he acknowledges that some 鈥渕omentum鈥� investors have slowed down.

Still, 鈥渁lmost all of the long-term smart capital investors have remained very active,鈥� he said.

Last year was 鈥渁ll about stablecoins and fintech infrastructure鈥� for the region. We should expect more of that this year, along with increased AI use across all sectors and strong enterprise growth in Brazil, he told SA国际传媒 News.

Brazil continues to be Endeavor Catalyst’s top market, but it is watching startups across the region, including in countries such as Mexico, Argentina, Colombia, Chile and even smaller markets such as Ecuador, Peru and Uruguay.

Endeavor Catalyst has reason to be bullish on Latin America. Startups it has backed in the region are among the top performers of the firm鈥檚 portfolio. More than one-third (34%) of its 2026 Outlier class, which comprise roughly the top 10% best performers in its network, are from Latin America, according to Taylor.

, general partner at S茫o Paulo-based seed-stage firm , told SA国际传媒 News that his firm鈥檚 pace in Latin America has remained constant and 鈥渋ntentionally selective.鈥�

鈥淲e’ve always believed that seed in Latin America works best when you’re deeply involved with a small number of exceptional founders and not try to index the market,鈥� he noted.

But like many other investors, OneVC is also investing at an earlier stage.

鈥淥ne notable shift is that, as founding teams move faster than ever, often reaching product-market signal with leaner teams and AI-native tooling,鈥� Cartolano said, 鈥減re-seed is taking a larger share of our investments, and we expect that to continue being the case for this cycle.鈥�

Like Endeavor Catalyst, Brazil is OneVC鈥檚 primary market. It has a home court advantage, but as Cartolano notes, the country also has a lot going for it including being the largest economy in Latin America, one of the world’s most active early-adopter communities for new technology (, -native commerce, AI), and a regulatory environment 鈥� particularly in financial services 鈥� which in his view 鈥渢hat fosters innovation鈥�

As a secondary focus, interestingly, his firm is tracking an increasing number of strong Latino founders relocating to the United States to build companies.

鈥淲e like that,鈥� he said. 鈥淭hey combine deep operational instincts from LatAm with access to the largest addressable market and most liquid exit environment.鈥�

He agrees with Taylor that global interest appears to be renewing in Latin America startups.

鈥淭here is no shortage of capital for the best companies in the region, regardless of the state, and we are seeing some large firms investing in LatAm for the first time or coming back after a long period,鈥� he said.

And while fintech has historically dominated when it comes to venture funding in Latin America, Cartolano said that fintech is now unsurprisingly giving way to AI-first companies that sell services, particularly to enterprises.

鈥淭he broader market is also shifting from consumer-facing models toward B2B, as enterprise companies are more incentivized than ever to adopt new technologies,鈥� he added. 鈥淥neVC is especially focused on GenAI companies that 鈥榮ell work,鈥� replacing headcount and outsourced services with AI-driven delivery at a fraction of the cost.

Related reading:

• In Q2, Mexico Surpasses Brazil In Venture Dollars For First Time In Over A Decade

Methodology

The data contained in this report comes directly from SA国际传媒, and is based on reported data. Data is as of March 31, 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. SA国际传媒 converts foreign currencies to U.S. dollars at the prevailing spot rate from the date funding rounds, acquisitions, IPOs and other financial events are reported. Even if those events were added to SA国际传媒 long after the event was announced, foreign currency transactions are converted at the historic spot price.

Glossary of funding terms

Seed and angel consists of seed, pre-seed and angel rounds. SA国际传媒 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. SA国际传媒 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 鈥淪eries [Letter]鈥� 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 鈥渧enture鈥� round. (So basically, any round from the previously defined stages.)

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