So far this year, investors have put about $7.8 billion into Boston-area startups, per Crunchbase That puts the region on track for a moderate annual gain and the strongest tally in about four years, as charted below.

Invidious comparison

Under normal circumstances, such numbers might be celebrated as pretty strong. But many Bostonians don’t see it that way.

“For the first time, startups in Texas raised more VC money than those in Massachusetts,” one headline this spring. Earlier this year, another correspondent concerns from local startup backers and builders that the tech startup scene is thinning out.

At root, the issue may not be that Bostonians are delivering so little investable startup talent, but rather that other places are swimming in unprecedented capital. This kind of invidious comparison is particularly stark in the AI realm.

Overall, North America venture funding hit a record high in the first quarter of this year, surging to $252 billion. Of that, more than 87% went to companies in Crunchbase AI-related categories.

Few of those AI mega-fundraisers were in Massachusetts. The biggest, most heavily funded names in generative AI, like , and others, are predominantly headquartered in the San Francisco Bay Area. That means Boston didn’t get a slice of history’s largest startup funding rounds.

By contrast, biotech, a traditional area of strength for the Boston area, hasn’t been on a funding tear. True, there’s no dramatic slump. But in a time when a single venture-backed AI company can snag $122 billion in a , biotech round sizes can’t compete for scale.

Standout rounds

Still, by pre-AI standards of venture funding, Boston has been scaling some heavy hitters.

Per Crunchbase , at least 12 companies in the greater metro area 1 raised rounds of $200 million or more this year, listed below.

The largest round went to , a provider of wearable fitness technology and a subscription platform that raised $575 million in Series G funding at a $10.1 billion valuation in March. The company says it is powered by more than 24 billion hours of physiological data and purpose-built AI models to provide predictive, personalized health insights.

, a provider of consumer privacy and security tools, came in second. It secured $375 million in Series B funding in March led by and .

Next on the list is , which provides healthcare plans to seniors on Medicare. The 9-year-old company disclosed in January that it had closed on $366 million across two Series F funding tranches.

Biotech startups, meanwhile, didn’t make the top 3 but were heavily represented on the list. Overall, more than half of funded startups in the list are focused on biotech or healthcare.

Why compare?

Boston isn’t the San Francisco Bay Area, and it certainly isn’t Texas. So it’s worth asking: What is the point of comparing startup ecosystems? Is a metro area flailing if it doesn’t keep up with a particular major innovation cycle, even if it maintains core areas of strength?

At risk of over-generalizing, we’d conclude that competitive rank still matters. A metro area can retain its crown as a startup innovation hub only if it continues to produce transformative companies.

For Boston, there’s no indication the region is losing its edge in biotech and other sectors where it’s long been an established powerhouse. However, in the generative AI era, it’s also evident that the region has not produced one of the most high-valuation players in the space, and that’s put some ding in the city’s reputation as a leading innovation hub.

Related Crunchbase queries:

Related reading:

• North America Q1 Funding Surges Across Stages To Record Level
• Whoop’s Wearable Fitness Tech Lands $575M From Athletes, Celebrities, Institutional Investors To Reach $10.1B Valuation

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.

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

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

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

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

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

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

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

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

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

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

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

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

Methodology

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

Illustration:

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

Physical tech is back, at least judging by this week’s largest U.S. funding deals. The biggest of all was a $1.5 billion corporate round for a medical device company that develops implants and treatment systems for musculoskeletal disorders. It was followed by an enormous Series A round, backed by a bevy of big-name investors, for , a 1-year-old artificial intelligence startup that says it’s developing personalized AI devices. Along with the usual heavy dose of AI, this week’s list also includes large deals for aerospace and defense, fintech, and retail technology. Let’s dive in.

1. $1.5B, healthcare: MiRus raised a massive $1.5 billion corporate round led by as strategic investors continue betting on next-generation orthopedic and spinal technologies. The Marietta, Georgia-based company has now raised $1.6 billion to date, . The deal comes with a 34% equity stake for Boston Scientific.

2. , $700M, artificial intelligence: AI startup Hark landed a huge $700 million Series A led by, with participation from a of investors including chip giants , , and , as well as ,, , 1Ěý˛š˛Ôťĺ . The San Jose, California-based company it’s building “advanced personalized intelligence and next-generation hardware” and plans to release some kind of product later this summer.

3. , $355M, AI infrastructure and developer tools: New York-based Modal Labs raised $355 million in a Series C round led by and , with participation from and . The company provides serverless cloud computing tools and GPU access for running AI models and testing AI-generated code. Its latest round is at a $4.65 billion valuation. CEO ​told Reuters that Modal’s ARR has soared to $300 million, up from about $60 million in September, as enterprise AI coding becomes widespread.

4. (tied) , $300M, artificial intelligence: Frontier lab Decart raised $300 million in a round led by that reportedly values it at nearly $4 billion. The deal also received backing from including venture firms and, AI researcher and corporate investors Nvidia, and . The startup, based in San Francisco and Tel Aviv, develops generative AI models and infrastructure, and has now raised roughly $456 million to date as investors continue pouring capital into foundational AI technologies.

4. (tied) , $300M, aerospace and defense: El Segundo, California-based Amca raised $300 million in a Series B led by, alongside investors including and. The company focuses on aerospace manufacturing and supply-chain technologies, an area drawing increased venture interest amid renewed defense-tech spending. Amca has raised $376.5 million overall, . Its latest round reportedly comes at a $1 billion-plus valuation.

6. , $250M, search and generative AI: AI search startup Exa secured $250 million at a $2.2 billion valuation in a Series C round led by Andreessen Horowitz. Based in San Francisco, the company develops AI-native search infrastructure designed for agents and large language model applications. The latest raise brings Exa’s total funding to $357 million and comes as competition intensifies around AI retrieval and search tools.

7. , $230M, edge computing and AI infrastructure: Armada raised $230 million in fresh funding at a $2.2 billion valuation. The Series B deal was led by , and, with participation from other investors including and . The San Francisco-based company develops edge computing and AI infrastructure systems designed for remote and industrial environments. The round brings its total funding to $469 million, .

8. , $200M, fintech: Mercury raised $200 million at a $5.2 billion valuation in a Series D round led by . Returning backers Andreessen Horowitz, , , , and also participated. The San Francisco-based company provides banking and financial workflow software for companies and has now raised about $657 million to date. Its latest round comes amid a broader uptick in fintech funding, including strong investor interest in digital banking platforms serving startups and businesses.

9. , $170M, retail technology: New York-based Radar secured $170 million in funding at a $1 billion valuation. The Series B round was led by and, with participating. The company develops AI technology for brick-and-mortar stores that uses overhead RFID sensors, software and analytics to give retailers real-time inventory visibility with item-level tracking accuracy. The company said its platform is deployed in more than 1,400 stores for customers including and . It has raised nearly $310 million to date, .

10. , $150M, wealth management: Farther raised a $150 million Series D led by as investors continue backing platforms modernizing financial advisory services. The San Francisco-based company provides technology-enabled wealth management tools and has raised approximately $268 million to date. Farther didn’t reveal its valuation with the latest raise, only that it is “now a unicorn.”

Methodology

We tracked the largest announced rounds in the Crunchbase database that were raised by U.S.-based companies for the period of May 18-22. 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:

When and his wife were navigating the complex world of fertility treatment, the process was marked by stress and financial strain. But after finally achieving a successful outcome, AlSalim recognized how different his experience was from many others in his position.

Despite the ordeal, he noted, having a child afterward “is much better than a load of people who don’t have anything to show for it.”

The experience sparked a business idea to help others in the same situation his wife and he were in. “My son was 1 week old,” he said, recalling the exact moment the concept took hold.

AlSalim officially registered the company name, , in 2019, but the business’ true inception came later, as the founder refined the idea and sought investors.

Gaia is working on building what AlSalim believes is a fundamentally new category in the . The company uses artificial intelligence and machine learning — trained on millions of anonymized historical data points and fertility outcomes — to better understand risk and probability for fertility treatment.

The platform analyzes variables such as age, hormone levels, ovarian response, treatment protocols, embryo development and clinical outcomes to direct patients to “optimal” clinics based on their data profiles, and to generate personalized forecasts around fertility success. It also uses AI and machine learning to underwrite personalized outcome-based “flexible” financing plans for IVF, egg freezing and embryo transfer procedures.

“We tell you where to go, we protect your path, we finance your treatment, we support you,” AlSalim said in an interview with Crunchbase News. “No one else today bundles care, capital and financial protection into a single product.”

And today, the New York-based startup — led by AlSalim as its sole founder — tells Crunchbase News exclusively that it has secured a $100 million debt facility from to scale its operations across the United States.

The credit facility follows a $14 million Series A round raised in January 2025, led by , that brought Gaia’s total equity funding to $37 million across three rounds. Other backers include and .

Fertility remains a relatively niche area for healthcare startup investment. Last year, venture investors put $194.8 million toward startups in Crunchbase’s fertility categories. Since the peak year of 2021, when $229.6 million went to fertility-related startups globally, annual investment in the sector has ranged between about $100 million and roughly $200 million, .

Treatment with ‘outcome protections built in’

Today, the fertility industry operates almost entirely on a “fee-for-service” model. Patients pay thousands of dollars per individual procedure, regardless of whether that procedure actually results in a baby. If a cycle fails, the patient is left with heartbreak and a depleted bank account.

Gaia flips this dynamic on its head by pricing the probability of success rather than the number of procedures, its founder said.

“We are not just a financing company,” AlSalim told Crunchbase News. “We use data in order to create unique plans that are individualized with outcome protections built in.”

For an IVF cycle, which has a nationwide median cost of $22,000, Gaia says it offers complete predictability. If a member’s first IVF cycle fails, Gaia covers the next cycle at no extra cost. For embryo transfers, the plan includes unlimited transfers until a live birth is achieved.

The model works across other endpoints, too. For example, if a 30-year-old woman wants to freeze her eggs, Gaia uses its predictive engine to guarantee a target number of retrieved eggs based on her specific biomarkers. If she does not hit that number in the first round, Gaia funds a second cycle at no extra cost. Patients can choose to pay the fixed cost upfront or use Gaia’s financing to spread the cost over five years with monthly payments.

Closed-loop model

By owning the data and the risk from initial consultation to live birth, Gaia aims to build a closed-loop data asset that it believes will serve as a massive competitive moat.

Its model is resonating. Over the past 15 to 16 months, Gaia has experienced a significant growth inflection, according to AlSalim. The company has surpassed 1,100 memberships, with over 1,000 active members in the U.S., and has partnered with 200 clinic locations across 40 states.

The founder declined to provide hard revenue figures when asked about growth, saying that the company is “now developing a baby every 18 hours” while maintaining a of 85, which is considered “exceptional” in the healthcare industry by , creator of the customer loyalty benchmark.

Building a village

To sustain this velocity, Gaia has expanded its distribution channels beyond direct-to-consumer marketing to include local partnerships with acupuncturists and pharmaceutical companies, as well as direct clinic integrations.

Last year, the company launched an enterprise benefit product, marketing and selling directly to employers who want to offer comprehensive, risk-insulated fertility coverage to their workforce.

The corporate product has scaled rapidly, said AlSalim. Gaia’s enterprise client roster spans diverse sectors — from tech professionals in Silicon Valley to blue-collar manufacturing workers in Denver.

, managing director and head of U.S. Investments at Viola Credit, said his firm was drawn to Gaia because it believes the startup is addressing “a deeply important and underserved problem” with a model that is “both commercially compelling and mission-driven.”

Chen believes that Gaia stands out also because it is not “simply a financing product.”

Its approach, he said, “aligns incentives across patients, clinics, and financing in a way that feels genuinely differentiated,” he wrote via e-mail, “and we believe it can meaningfully improve access to fertility care.”

Related Crunchbase query:

Related reading:

• VC Investment Soars For Fertility Services Even As Birthrate Dips

Illustration:

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

This week, just half of the top 10 rounds crossed the $100 million mark, which is somewhat unusual in this high-flying era for venture megarounds. Nonetheless some large checks did get written, led by ’s $5 billion investment and partnership deal with . Other sizable rounds went to companies in sectors including aviation autonomy, vision therapy and AI analytics.

1. , $5B, foundational AI: AI giant Anthropic that Amazon is investing $5 billion in the company, with up to an additional $20 billion in the future. Previously, Amazon had invested $8 billion in the San Francisco-based company. The latest financing also includes a partnership with Amazon for training and deploying Anthropic’s AI assistant Claude.

2. , $160M, autonomous aircraft: Reliable Robotics, a developer of autonomous aircraft systems, raised $160 million in fresh financing led by . The 9-year-old, Mountain View, California-based company markets its technology for both commercial and defense aviation.

3. , $125M, vision therapy: San Diego-based Ray Therapeutics, a biotech startup focused on vision restoration therapies, secured $125 million in Series B funding led by . Founded in 2021, Ray has raised $247 million in venture and grant funding to date, per .

4. , $120M, AI analytics: Omni, developer of an AI-enabled analytics platform, closed on $120 million in Series C funding led by . The financing set a $1.5 billion valuation for the 4-year-old, San Francisco-based company.

5. , $106M, biotech: Framingham, Massachusetts-based Tortugas Neurosciences, neurology-focused biotech startup, scooped up $106 million in Series A funding. Founding investor co-led the round alongside and .

6. , $80M, medtech: AcuityMD, an AI-enabled data and research platform for medtech industry customers, picked up $80 million in Series C investment. led the funding for the 7-year-old, Boston-based company.

7. , $75M, foundational AI: that it purchased $75 million worth of San Francisco-based OpenAI’s common stock. The shares are owned by Robinhood Ventures Fund I, a publicly traded fund that provides investors exposure to a curated portfolio of private companies.

8. , $60M, workflow orchestration: Orkes, developer of an AI-enabled software workflow orchestration platform, secured $60 million in Series B funding. led the financing for the 5-year-old, Silicon Valley-based startup.

9. , $50M, health tech: Courier Health, a developer of tools to improve patient experience for people with chronic conditions or rare diseases, closed on $50 million in Series B funding. led the financing for the New York-based company.

10. , $50M, biotech: Cambridge, Massachusetts-based Serif Bio­med­i­cines, a biotech­ startup focused on Mod­i­fied DNA as a new class of med­i­cines, launched with $50 million in initial funding from .

Methodology

We tracked the largest announced rounds in the Crunchbase database that were raised by U.S.-based companies for the period of April 18-24. 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:

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.

Illustration:

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.)

Illustration:

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

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.

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$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.

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$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.”

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$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

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$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.

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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.

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