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’s 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 — carefully structured to protect our velocity — would dramatically improve the odds that we realize our mission of significantly increasing the world’s 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’s largest radiology practice, it establishes credibility across multiple dimensions at once — 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’re trying to improve. Selling early didn’t shorten our journey, it accelerated it. It gave us the foundation required to deliver on our mission of significantly increasing the world’s 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 “Nature” 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’s 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 ’s 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  $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’s 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’s startups fell from a year earlier — by around 20% — Crunchbase 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 Crunchbase query:

Methodology

The data contained in this report comes directly from Crunchbase, 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. 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.)

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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.

While no billion-dollar rounds led this week’s list, we nonetheless saw a variety of startups in industries ranging from semiconductors to aerospace to biotech raise sizable rounds. The week’s 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’s last funding round before an IPO, though didn’t 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 next-generation cancer drugs called antibody-drug conjugates, or ADCs, which are designed to act like “guided missiles” 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’s 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 ​​, 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‑enabled audit platform that acquires CPA firms and equips them with AI‑driven audit tools to deliver higher‑quality 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 Hēlo for the treatment of venous thromboembolism, or VTE. The company secured clearance for Hēlo 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 Crunchbase 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.

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In a quarter when nearly two-thirds of global venture capital went to just four companies, it’s easy to lose track of the many other companies getting funding to tackle interesting problems. Nonetheless, we spotted five companies in just the past month working on issues from cleaner ferries and trains to foundational AI for plants. Let’s take a closer look.

$55M for a mineral rights-backed credit card

Natural resources can be incredibly valuable financial assets, but you can’t exactly buy your weekly groceries with oil or water rights.

That’s an issue that a Dallas-based fintech startup aims to solve. recently raised $50 million in a debt round from to provide a credit card to U.S. households holding mineral rights to natural resources such as oil, natural gas, solar, wind or water.

“For the millions of mineral rights owners in the United States, these rights are one of the most valuable assets the family owns. But these families are just like the rest of Americans and often are carrying revolving credit card balances at more than 25% [interest],” Frontlands CEO said in a statement. “Historically, owners have had few options to access the value trapped inside their mineral rights without selling.”

Its AI system combines machine learning, production data, royalty payment histories, lease terms, commodity price forecasts, geologic data and traditional to automate the underwriting process, the company says. While it’s historically been difficult for traditional lenders to assess natural resources as collateral, Frontlands says its process typically delivers a same-day credit decision.

The company’s recent credit facility is in addition to a announced in December from venture investors including , , and .

Frontlands said its average credit line in early markets — Texas, Pennsylvania, New Mexico, North Dakota, Wyoming and Oklahoma — is more than $30,000. It plans to launch its credit card product this summer in partnership with Texas-based sponsor bank .

Frontlands said it also expects to raise a Series A round later this year.

“Our goal isn’t to pile on more debt,” Cotter said in a statement. “But the opportunity to help our customers move away from high-interest credit card debt — and provide a path toward greater financial stability — is compelling.”

Investment in fintech startups hit a multiyear high in 2025, Crunchbase data shows, though remains well below the peak. Many of the best-funded companies in recent quarters have brought AI to bear on traditionally more manual or cumbersome processes in the financial services industry.

Related Crunchbase query:

$32M for ‘flying’ electric commuter ferries

As of this writing, oil prices are hovering around $100 a barrel — down from an even greater peak a few weeks earlier, but still among the highest levels seen in years, as the U.S.-Iran war disrupts global energy markets.

So Swedish electric vessel maker ’s recent funding of €30 million (about $32 million) seems timely. The Stockholm-based company makes electric “flying” boats that are used as commuter ferries. They differ from traditional vessels by using computer-controlled hydrofoils to lift the hull above the water, an approach the company says dramatically reduces drag and cuts energy use by up to 80% — enabling faster, smoother, zero-emission travel compared to conventional diesel ferries that push through the water.

“From a physics perspective, ships have been essentially the same for hundreds of years,” Candela founder and CEO said in a statement. “We’re redefining waterborne transport by effectively creating a new category of vessel. This allows cities and municipalities to finally take full advantage of waterways — while escaping the fossil-fuel cost trap that has long prevented them from being used efficiently.”

Its P-12 vessels have already been deployed as commuter ferries in Stockholm, Gothenburg, Oslo and Trondheim.

The new funding was led by ’s arm and included previous investors , , and .

The capital will primarily be used to fund a second factory in Poland. Candela says it has more than 65 vessels on order and planned deployments across markets including India — where a fleet of 10 of its P-12s will reportedly cut travel times from Navi Mumbai Airport to the city center from around two hours to 35 minutes — the Middle East and Southeast Asia.

The startup’s funding defies an overall downturn in clean-tech funding. Funding for clean-tech related startups totaled $26.9 billion in 2025, down 23% year over year and the lowest annual amount since 2020, Crunchbase data shows.

Related Crunchbase query:

$30M to electrify trains with batteries and microgrids

Let’s now turn from waterways to train tracks, with another company that recently raised significant funding aimed at giving centuries-old transportation systems a green overhaul.

, a Philadelphia-based startup, said last month that it raised $30 million in seed funding led by Australian mining company and Israeli venture firm to develop a new way of powering freight rail that avoids the high costs of traditional electrification.

The startup positions its technology as a way to decarbonize one of the world’s most efficient but still fossil-fuel-dependent transport systems. It’s targeting a major pain point for the rail industry: its heavy reliance on diesel. In North America alone, the six largest freight rail operators spend roughly $11 billion annually on diesel fuel, while full electrification of rail networks could cost more than $1 trillion, according to Voltify.

Instead of relying on overhead wires, Voltify says it’s building a system that combines battery-equipped railcars with technology that allows trains to recharge while moving. The goal is to help rail operators cut emissions and fuel costs without requiring massive infrastructure overhauls.

Its approach — using mobile batteries and distributed charging via microgrids — aims to sidestep those costs by retrofitting existing trains and building localized energy systems rather than rebuilding entire rail networks.

CEO and co-founder that the company has signed a paid pilot agreement with a Class 1 railroad, though she declined to name the customer, citing a confidentiality agreement.

She noted in a that raising funding for a transportation company in the current market was difficult. “Securing capital in the hardware space and traditional industries is challenging,” she wrote. “It is not the ‘in’ space; there is no FOMO at play, so we need to focus on metrics and execute quickly. With some of the top 5 largest rail companies globally and a large order pipeline, we are determined to keep moving at lightning speed.”

Related Crunchbase query:

$7M for foundation AI for biology

Funding to foundational model AI startups surged last quarter, reaching $178 billion, per Crunchbase data. But the vast majority of that funding went to AI giants like and that are building general-purpose GenAI models.

Such models are fundamentally lacking for hard sciences, argues , a startup based in Paris and Berkeley, California, that last month raised $7 million in seed funding to develop foundation AI for biology trained on DNA, RNA and data from other “” fields, rather than human text.

The company’s first family of transformer models is called Botanic and is trained on data from 43 plant species. Living Models noted that it’s starting with the commercial crop industry, a massive global market that has abundant data, well-established research infrastructure, and fewer regulatory concerns and faster commercialization timelines than the pharmaceutical industry.

“Plant biology combines three properties that make it an ideal first domain for biological foundation models: genomic data is abundant and largely unrestricted, the commercial need is acute and quantifiable, and the feedback loop between computational prediction and real-world validation is well established through existing breeding infrastructure,” the company said in a statement.

The global seed industry is also dominated by a handful of incumbents, it noted: , , , and — companies that already spend billions of dollars a year on breeding research.

“Biology is an information problem at every scale, from a single cell to an entire ecosystem. The genomic data exists across many domains; what’s been missing is a model architecture capable of learning from it at scale,” , Living Models’ CTO and co-founder, said in a statement. “We start with plants because the data is rich and the breeding cycle is a clear bottleneck, but the same approach applies wherever sequence data meets slow, empirical discovery.”

The company’s recent funding was led by , , and . Other included and

Related Crunchbase query:

$2.1M for a brain-stimulating consumer wearable

Billions of dollars a year are spent on therapy and other mental-health treatments, yet measuring progress can be elusive.

That’s one of the issues that San Francisco-based aims to take on with a neuromodulation wearable headset that it says can reduce stress, improve attention span and mood, and more quantitatively measure mental health scores.

Mave’s device uses transcranial direct current stimulation, or tDCS, a noninvasive technique that delivers a low electrical current to the brain through electrodes placed on the scalp, with the aim of modulating neural activity. The technology is when used by adults as directed in controlled settings.

The company last month raised $2.1 million in seed funding led by , with participation from individual investors including Autopilot AI lead .

Crucially, Mave says it does not plan to pursue medical-device approval for its product, which sells for $495. Instead, it is positioning the gadget as a wellness tool that consumers can use on a daily basis to improve their mental well-being and better measure the outcomes of talk therapy or other treatments.

“If you ask a psychologist how do you know if a person is making progress, their response to it is very standard, which is that it’s not about progress. It’s about process […] But for somebody with depression who is spending a lot of time in therapy, progress is important. So how do you know whether they’re making progress or not? And even these basic questions were not being answered,” co-founder .

Mave’s funding comes amid an overall downturn in investment for wellness and fitness-related companies, although select wearables makers including and have raised significant funding in recent years.

Related Crunchbase query:

Related reading:

• 5 Interesting Startup Deals You May Have Missed: Blood-Drawing Robots, Inboxes For AI Agents, Franchised Defense Manufacturing, And More
• 5 Interesting Startup Deals You May Have Missed: Plant-Based Clothing Dyes, A Shoebox-Picking Robot, And Power Generated On The Moon
• 5 Interesting Startup Deals You May Have Missed In December: A Hospital-Grade Wireless Heart Monitor, AI-Designed Proteins For Manufacturing, And More

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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.

The pace of large-scale dealmaking picked up some this week, led by ’s disclosure that it raised another $10 billion to add to its record-setting megaround announced last month. Other big financings went to startups and growth-stage companies in sectors including defense tech, enterprise AI, autonomy and even laundry.

1. , $10B, foundational AI: OpenAI $10 billion in additional funding for its record-setting megaround announced in late February, reportedly bringing the total fundraise to the San Francisco-based company to over $120 billion. Backers in this latest financing include , , , and .

2. , $2B, defense tech: San Diego-based defense tech unicorn Shield AI said it secured $2 billion at a $12.7 billion valuation. The round consists of $1.5 billion in Series G funding led by and along with $500 million in preferred equity financing backed by . Part of the proceeds will help pay for the planned acquisition of , a defense software company whose technology is used to train pilots and test advanced aircraft and autonomous systems.

3. , $350M, transportation safety: Cambridge Mobile Telematics, a telematics and AI company focused on enabling safer mobility, picked up $350 million in a new financing  led by and . Founded in 2010, the Cambridge, Massachusetts-based company has raised over $850 million to date, per Crunchbase .

4. (tied) , $200M, legal tech: Harvey, the fast-growing provider of AI-enabled tools for law firms and in-house legal teams, closed on $200 million in fresh financing at an $11 billion valuation. and led the round, which brings total funding to 4-year-old San Francisco-based Harvey to around $1.2 billion.

4. (tied) , $200M, healthcare: eMed, a provider of GLP-1 programs for employers that counts as chief wellness officer and backer, said it raised $200 million in new funding. led the round, which set a $2 billion plus valuation for the Miami-based company.

6. , $170M, satellite tech: Xona secured a $170 million Series C round led by . The funds will go to scaling satellite production for a planned constellation of next-generation navigation satellites. Founded in 2019, Burlingame, California-based Xona has raised over $320 million to date.

7. , $140M, laundry tech: Cents, a provider of software and payments technology for the laundry industry, secured $140 million in Series C funding led by . The New York-based company said the round represents “the largest single software investment in the laundry vertical to date.”

8. , $125M, AI health tools: Palo Alto, California-based Qualified Health, developer of an enterprise AI platform for health systems, locked up $125 million in Series B financing led by .

9. (tied) , $110M, data observability: Dash0, an agentic observability platform, announced it closed on $110 million in Series B funding led by . Founded in 2023, the New York-based company has raised over $154 million to date.

9 (tied) , $110M, drones: Huntsville, Alabama-based Performance Drone Works, a startup that designs, engineers and manufactures drones for defense and law enforcement, secured over $110 million in Series B funding led by .

Methodology

We tracked the largest announced rounds in the Crunchbase database that were raised by U.S.-based companies for the period of March 21-27. 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:

Venture firms that set up shop in the Texas capital city included , , and 1, among others. famously moved ’s headquarters to Austin in 2021, while also purchasing a house and establishing a residence there.

But as more employees returned to in-office work, Austin slowly seemed to fall out of favor with the tech community, some of whom said it had been overhyped as a startup hub.

There were reports of tech workers who had moved to the city during the pandemic and , saying they were going back to places like the Bay Area. Musk back to California in 2023.

Funding tops pandemic peak

Undeterred by the “tourists,” the startup and venture community in Austin kept plugging away. And those efforts are reflected in a surge in funding to startups headquartered there last year, with 2025 posting an all-time high for Austin venture investment, Crunchbase data shows.

Investment into Austin-based startups spiked 64.8% to $7.19 billion in 2025 as more investors poured money into companies based in the region, according to Crunchbase . That’s compared with the $4.37 billion raised by Austin-area startups in 2024 and tops even the $6.1 billion raised in 2021, at the height of the venture funding frenzy.

Notably, deal counts actually decreased from 312 in 2024 to 272 year over year, signaling an increase in later-stage deals. Indeed, the data corroborates that with $4 billion of the total raised in 2025 classified as late-stage rounds.

Last year’s totals were also more than double — 130% higher — than the $3.1 billion raised in 2023. That money was raised across 403 deals, signaling much smaller round sizes at the time and a more mature market.

A tech scene decades in the making

, managing partner of , doesn’t believe that the Austin funding performance in 2025 was anomalous.

Rather, he calls it “the payoff from decades of compounding.”

“Talent density in venture categories such as software, fintech, health tech, defense and  robotics has reached a critical mass, driven by waves of Bay Area relocations, both full HQ moves and satellite offices, that brought technical, product and operational talent into the market,” Flager said.

That talent eventually left to build new companies, he said, and the cycle repeated.

“On the capital side, the stack has matured across all stages, from pre-seed through growth, with local firms that have now cycled through multiple funds and understand the market deeply,” Flager said. “Layer in a business-friendly regulatory environment, a relatively lower cost of living, as well as a lower effective tax rate, and Austin becomes an attractive place to start and scale a company.”

Former Austin Mayor saw so much potential in the city’s startup scene that he began a career in venture investing after his tenure ended in early 2023. (He now works for New York-based ).

Part of the city’s success as a startup hub stems from its reputation as a haven for mavericks and risk-takers, Adler has said.

“Most cities in the world, you try something, you fail; it’s hard to have access to the capital the second time,” he told co-founder in a in 2022. “In Austin, the civic folk heroes are the people that tried something and it didn’t quite work out and they worked on it until it did.”

, founder of , a solo GP venture firm based in nearby San Antonio, said that it feels like Texas and the Austin metro area specifically are becoming more attractive to manufacturing- and engineering-heavy businesses.

“Some of that may be thanks to Tesla, and some of it may simply reflect the physical advantages of the state,” he told Crunchbase News. “Either way, this [surge in financing] feels less like hype returning and more like capital concentrating around a narrower set of serious, technically differentiated companies.”

Deal sizes grow

That diversity among funded startups is reflected in last year’s investment totals for Austin, which were boosted by several large, late-stage deals across a broad range of industries.

The largest was a $1 billion Series C round for energy provider in October. New York-based led that financing, which valued the 2-year-old company at $4 billion.

Looking back, February in particular was a busy month for venture funding. That month alone saw the second-, third- and fourth-largest rounds in Austin for the year. They included:

• A February Series C round in which autonomous surface vessels maker raised $600 million at a $4 billion valuation. led the round for the defense tech startup.
• Also in February, , which provides endpoint management, security and monitoring, raised $500 million in Series C extensions at a $5 billion valuation — more than doubling its value from just 12 months prior. The funding came in separate tranches led by and ’s , with participation from other investors.
• Robotics company in February raised $415 million in Series A financing led by  and accelerator (A $520 million extension to that Series A was raised in February 2026, taking the total round to over $935 million.)

The findings correspond with Flager’s observations.

“A good chunk of the capital raised in Austin was driven by several large deals. Similar to what we saw across the U.S. in 2025, venture funding in Austin was more concentrated than it has been in the past,” he told Crunchbase News. “Roughly 38% of the capital deployed went to the top five venture financings in Austin. I believe the top 10 deals nationally accounted for more than 40% of the capital raised last year. We’ll see if this trend continues into 2026 and beyond. The start of the year suggests it will.”

, founding partner of , agrees, noting that from a dollars perspective, the surge in financings was driven by a handful of outsized capital-intensive deals in newer categories such as defense and deep tech.

“These companies require a combination of technology, land for manufacturing facilities, and talent for manufacturing tasks. Austin has unique skillsets for that,” he said. “It has a density of three things: talent in deep tech with , and many others moving to Texas in light of favorable business conditions with expertise in these industries; expansive land around Central Texas that is inexpensive, especially compared to California; and lower cost manufacturing-related labor especially given the surge in manufacturing jobs such as at Tesla in recent times.”

Burgeoning industries

Once upon a time, Austin was better known as home to software and CPG companies. And while those types of companies certainly still exist, a number of other industries are growing increasingly robust, as the local investors have pointed out.

As with many top tech markets, Flager said Austin has long been strong for application and infrastructure software, which is currently being challenged by AI. In his view, that talent has migrated to building “quality” vertical agentic software and AI-native businesses.

“We are seeing these companies grow quickly and build scale, while using less capital — which is exciting,” he added. “The domain experts who built and scaled application software companies here over the last two decades are spinning out to build the next generation of native AI businesses.”

The market overall is also broadening in interesting ways. Defense and autonomy have emerged as breakout categories, with Austin becoming one of the stronger markets in the country for dual-use and autonomous systems companies, noted Flager.

“The combination of software and hardware skills now in Texas, along with a business-friendly regulatory environment, has allowed Austin to take a leadership position in these important and developing markets,” he said. “Energy tech is also a natural fit given Texas’ grid scale and the surging power demands of AI infrastructure.”

Finally, robotics and advanced manufacturing are also gaining momentum, driven by deep engineering talent and the ability to scale manufacturing near Austin cost-effectively, allowing engineers, executives and other factory employees to coexist and collaborate in close proximity.

Srinivasan noted that his firm is seeing strong activity in vertical AI companies, or companies that serve vertical markets with AI that is tuned on specialized proprietary vertical data, often targeting the services and labor expenditures by their customers.

“These companies deliver ‘Services as Software’ with close to software gross margins and pricing models that are based more on usage and outcomes as opposed to the traditional seat-based models,” he said.

Srinivasan also expects the city to continue to see large funding deals in defense and deep tech, given the combination of local strengths and robust global demand for such products.

Continued momentum

Investors and companies continue to be drawn to Austin. In late December, San Francisco-based venture firm in the city. One of the firm’s founders, , also announced that he had personally moved to Austin. The firm’s other founder, , had lived and worked in the city since 2022.

In late March of this year, Musk to build two semiconductor factories totaling 100 million square feet in Austin to supply advanced chips for and Tesla. The venture, known as Terafab, aims to manufacture 1 trillion watts of computing power per year, he said. Media outlets valued the initiative at nearly

Also this week, Barcelona-based AI health tech startup announced it will open an office and hire in Austin.

CEO told Crunchbase News that with the company’s New York office already established, the next step was not just expansion, “but choosing the right place to build.”

“And we chose Austin for one reason above all: talent,” he said. “As an AI health tech company, our success depends on attracting exceptional people across engineering, data and life sciences. Austin has rapidly become one of the most competitive talent markets. The city is one of the fastest-growing in the United States. This brings together deep tech expertise, entrepreneurial energy and a growing concentration of healthcare innovation. Ideal for our goal of building an R&D hub. “

Coelho also points out that Biorce has witnessed a “trend” of people moving from the Bay Area to Austin, noting that “the quality of life has gained notoriety.”

“But for us, this isn’t about following a trend,” he added. “It’s about building where the best people are — and where they want to be.”

Related Crunchbase query:

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• Only 2 States Saw Their Share Of US Venture Funding Rise Last Year
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• Lower Costs, Laid-Back Lifestyle Continue To Draw Tech Companies To Austin, Texas
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The fundraise includes $1 billion for KP22, a fund to back early-stage companies, and $2.5 billion targeted for growth-stage investments.

It’s a considerable increase in capital commitments compared to the last time the Silicon Valley-based firm raised a flagship fund, back in 2024. In that raise, Kleiner just over $2 billion for funds to back early- and later-stage startups.

This time around, Kleiner believes market fundamentals look particularly attractive for scaling up.

“The AI super-cycle is one of the most important company-building moments in our lifetimes, and we are still in the early innings,” its fundraising announcement states. Kleiner also notes that AI is enabling today’s startups to iterate and grow faster than in past cycles.

Founded in 1972, Kleiner has long been known as a cross-industry investor, active in virtually every popular sector for venture dealmaking. For its latest fund, the firm also identified a broad array of focus areas, including professional services, healthcare, autonomy, security, financial services and the physical economy.

Recent investments

Most recently, Kleiner, like most venture heavyweights, has been focused on AI startups. Beyond that, however, its portfolio companies are a highly varied lot.

To illustrate, we used Crunchbase data to put together a list of the latest reported rounds in which it served as a lead or co-lead investor. It spans healthcare, accounting and cybersecurity, among other areas.

Large lead investments

While it’s active in seed- and early-stage dealmaking, Kleiner also leads quite a few larger rounds. Over the past year, it’s been lead investor in at least five valued at $150 million or more, which we list below.

Of these, the largest was a $600 million Series F for , a developer of autonomous vehicle technology. The next-largest include a $356 million Series D for , focused on secure open-source software for AI systems, and a $300 million Series E for , the AI legal tech unicorn.

Exits too

Kleiner has also seen a few sizable recent exits for portfolio companies that it backed as lead investor. This includes last year’s largest software IPO — — which counted Kleiner as Series B lead investor.

The firm was also an early lead investor in business credit card provider , which agreed to acquire this year for $5.15 billion.

Of course, Kleiner also has much more famous portfolio investments in its more distant past, including , and , to name a few. You don’t last 50 years in the venture business without at least some of those too.

Related Crunchbase queries:

Related reading:

• Capital One To Buy Fintech Startup Brex At Less Than Half Its Peak Valuation In $5.15B Deal

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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.

In insecure times, security looks like an appealing sector for investment. That’s one interpretation of this week’s tally of the largest startup funding rounds.

The size of the largest U.S. deals was smaller than in recent weeks, and heavily featured cybersecurity- and privacy-focused startups. This includes the week’s biggest round — a $375 million Series B for consumer privacy and security platform . Other areas that attracted good-sized financings included AI infrastructure, biotech, healthcare, and robotics.

1. , $375M, privacy: Cloaked, a provider of consumer privacy and security tools, raised $375 million in Series B funding led by and . Founded in 2020, the Massachusetts-based company sells monthly subscriptions for individuals and families.

2. , $143M, AI infrastructure: Frore Systems, a developer of integrated cooling architecture for AI computing and networking hardware, announced that it closed on $143 million in Series D funding. led the financing, which set a $1.64 billion valuation for the 8-year-old, San Jose-based company.

3. (tied) , $120M, cybersecurity: Seattle-based XBow, a provider of autonomous security testing technology, picked up $120 million in Series C funding. and led the round, which values the 2-year-old company at over $1 billion.

3. (tied) , $120M, cybersecurity: Oasis Security, a developer of identify security tools with a focus on AI agents, secured $120 million in a funding round backed by , , and . The 4-year-old company, which is headquartered in  New York and has a presence in Israel, has raised $195 million to date, per Crunchbase data.

5. (tied) , $100M, medical devices: Imperative Care, a medical device company focused on treatment for stroke and vascular diseases caused by blood clot formation, secured $100 million in convertible note financing. and led the investment for the Campbell, California-based company.

5. (tied) , $100M, social media: Seattle-based social network Bluesky this week that it raised a previously unannounced $100 million Series B round that closed last spring, led by .

5. (tied) , $100M, privacy and security: Cape, a recently launched privacy-focused mobile network, landed $100 million in Series C funding. and led the financing, which set a $900 million valuation for the Arlington, Virginia-based company.

8. , $80M, healthcare AI: Latent, an AI platform aimed at helping move patients from clinical decision to therapy, picked up $80 million in a Series A round. and led the financing for the San Francisco-based company.

9. , $77M, biotech: Cambridge, Massachusetts-based Crossbow Therapeutics, a biotech startup focused on developing new antibody therapies to treat a broad range of cancers, raised $77 million in Series B funding. and led the round, which will support a Phase 1 clinical trial of the company’s lead program.

10. , $52M, robotics: RoboForce, a startup focused on developing AI-enabled robot labor for industrial environments, said it $52 million in fresh funding, bringing its total raise to $67 million. led the financing for the Milpitas, California-based company.

Methodology

We tracked the largest announced rounds in the Crunchbase database that were raised by U.S.-based companies for the period of March 14-20. Although most announced rounds are represented in the database, there could be a small time lag as some rounds are reported late in the week.

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In that moment, “you’re in a very tough spot mentally and emotionally,” Gerstenzang recalled about the experience. “To feel taken advantage of — and then feel that the person you love isn’t being honored the way they should — it’s not a good feeling.”

The experience left the serial entrepreneur so disappointed that he felt compelled to offer others in similar situations better options. So in January 2024, he teamed up with to launch New York-based , which describes itself as a “contemporary funeral home without the home.”

When a person is overcome with grief, making so many decisions related to what is often the biggest unplanned purchase of many people’s lives can be daunting. Meadow aims to make it as simple as possible by allowing families to arrange funerals over the phone or online. The startup also partners with a curated set of venues so funerals can happen, for example, at a wedding venue that’s only booked on Saturday nights or at a local chapel rather than a funeral home.

“Because we’re software-enabled and not stuck in the way things used to be, we can offer honest pricing and unmatched hospitality,” Gerstenzang told Crunchbase News in an interview.

Meadow recently raised a $9 million Series A funding round led by and following a $2 million seed round in 2024, it told Crunchbase News exclusively. Uniquely, the initial capital for both Meadow and Moxie came from the founders’ own permanent capital firm, a vehicle they use to lead their own seed rounds.

Lower costs, more software

Meadow operates by stripping away the most expensive part of the business: the real estate. By forgoing physical storefronts and using software for administrative tasks, Meadow claims it can offer dramatically lower prices.

The national median cost of a funeral with a viewing and burial in 2023 was $8,300, while the median cost of a funeral with cremation was $6,280, to the .

Meadow says that its services are significantly more affordable. A typical funeral can cost around just $1,300, according to Gerstenzang.

“There are a lot of markups on coffins [at funeral homes], because of the increased rate of cremation,” he explains. “So a lot of funeral homes really want you to do a burial. They want you to do an elaborate service because that’s how they make their money. And there’s a ton of markup embedded in that.”

From fintech to funerals

Gerstenzang is no stranger to scaling complex systems. An alumnus of payments giant , where he led product teams for consumer payments, he and Gilsanz in 2022 also co-founded , which helps nurses open medspas. In founding both companies, Gerstenzang has noticed a pattern: highly regulated markets that impact millions of people but haven’t seen meaningful innovation in decades.

In the funeral industry, he saw a landscape dominated by private-equity rollups. He claims that some large corporations buy up local family funeral homes, keep the original names on the doors to build false trust, and then quietly hike prices.

Meadow’s business model seems to be resonating. The company grew its revenue 3x from 2024 to 2025 and is on track to triple it again in 2026, according to Gerstenzang. The company worked with more than 400 families in February alone, he said.

After becoming the largest independent funeral home in California, the company recently expanded into Texas and Washington, with Arizona and five other states on the horizon this year.

Today, nearly a third of Meadow’s business comes from “pre-planning” – from people who, for example, have just navigated the process of burying their own parents, and want to spare their children the same burden. It also offers both a direct cremation and a funeral, depending on a family’s wishes.

“We fundamentally care about the quality of what we do,” Gerstenzang said. “We believe we can actually increase quality as we scale because our software allows our team to spend their time working directly with customers, rather than dealing with paperwork the same way it’s been done for 50 years.”

, founder and general partner at Meadow investor Haystack, noted that that his firm was also among the earliest investors in and .

Backing ‘broken, unsexy’ industries

“We know when there’s a broken, unsexy industry that hasn’t adapted to serve the modern consumer,” he wrote via email. “Meadow’s combination of software operations with unmatched hospitality is exactly what the deathcare industry needs and what families deserve.”

Related reading:

• Startups Look To Streamline Tasks Around Death And End-of-Life Planning
• More Funded Startups Focus On Dying And Bereavement

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For venture firms, landing early investments in these companies is one of the clearest signals of long-term performance. An analysis of Crunchbase data shows and once again dominated the latest unicorn cohort, backing the most deals in companies that reached billion-dollar valuations in 2025.

But Crunchbase data also highlights a set of rising investors — including , 1, , 2�����Ի� — that appear to be gaining ground in the race to fund the next wave of category leaders.

Unicorns advance

Last year was a strong one for new unicorns — well above the post-pandemic lull and slightly ahead of pre-pandemic norms. The pace of new unicorn creation also picked up each quarter in 2025 and has shown no signs of slowing in 2026, per Crunchbase data.

Trending investors

AI-native companies accounted for 47 of last year’s new unicorns, or 25% of the total, and that percentage seems likely to grow in 2026 as companies in that sector continue to draw significant investment.

Notably, nearly half of the new unicorns are also very young: 94 of them are less than 5 years old.

The most-active investors in terms of deal count in last year’s new unicorn class were two VC heavyweights: Sequoia and a16z, which made 51 investments across 21 and 20 companies, respectively.

Notable investments for Sequoia — where the firm led early at seed or Series A rounds and continued to back later rounds — include , a clinician-focused medical AI platform, prediction markets platform , and frontier intelligence lab .

For Andreessen, three of its most-notable investments were for automated coding platform , health customer support service , and , which provides AI for customer support.

Following those two firms, was a close third with 49 investments across 23 companies, which was the highest count of companies for an investor in the unicorn class. Its  investments include trucking insurance startup , , an expert training data platform for AI, and , a frontier lab for visual content.

, and rounded out the leading six unicorn investors of 2025, with 37, 36 and 34 deals, respectively. Portfolio companies where these firms led early and kept investing include:

• Accel: (VPN network provider), (AI-powered presentations) and (visual website design platform).
• Y Combinator: (app development platform), (legal AI research service) and  (industrial inspections).
• Lightspeed: (commercial trucking insurance), (AI for large enterprises) and for (agentic AI).

Rounding out the top 10 were with 28 investments, seed investor 3�����Ի� growth investor , each with 23 and 22 deals, respectively.

Ribbit Capital and Felicis shared the top 10 spot, each with 20 deals.

Newer entrants

What’s compelling is not just the investors with a track record of backing formidable companies, but those that have climbed the ranks by identifying the next wave early.

The investors in the 2025 class of billion-dollar startups include quite a few firms who were not in the overall top 20 investors for current private unicorn companies.

Crunchbase data shows Redpoint, and moved up from the top 30 while Ribbit Capital, Felicis and 8VC made their move from the top 50.

, the single corporate investor on this list, and both moved up from the top 60.

vaulted up to the top 20 from the 175th-ranked investor slot in current unicorns. Its thesis is to invest in technical founders in applications, models, tools and infrastructure, and includes video and image generator , customer data platform , and workflow documentation platform .

Higher values, faster cycles

In 2025, The Crunchbase ������Ƶ expanded in both company count and total value as cloud and AI continued to unlock new opportunities. The leading companies have decisively separated from the pack, with billions in revenue and a strong runway.

The race to back the next generation of companies defining new opportunities has accelerated, but markets are moving faster than ever. Cutting-edge companies in today’s market risk being taken over by AI developments which erode their advantage and wipe away their lead.

Investors who want to back the next market winners need to keep investing.

Related Crunchbase unicorn lists:

• (1,712)
• (604)
• (68)
• (187)
• (117)
• (102)
• (884)
• (501)
• (230)
• (38)
• (470)

Related reading:

• Crunchbase Data: The AI Boom Has Drastically Changed Who’s Funding The Hottest Companies In 2025 Vs. 2021
• Hottest Deals In Tech Push Crunchbase ������Ƶ Toward $7T In Value
• What We Learned From 6 Active AI Investors Backing Startups Across The Stack
• Global Venture Funding In 2025 Surged As Startup Deals And Valuations Set All-Time Records

Methodology

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

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

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

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

Deal counts reported here reflect deals disclosed in Crunchbase. Crunchbase, like all databases of private-market transactions, has a documented pattern of reporting delays. It can sometimes take between weeks and months for some rounds to be announced publicly and subsequently get added to Crunchbase. As data is added to Crunchbase over time, some of the numbers in this report may shift.

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.

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