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

Startup investors were busily closing on big rounds this week, with AI and defense among their favored target sectors. The biggest financing went to , a defense tech startup developing a hypersonic missile. Other sizable rounds went to companies developing AI inference technology, a video-creation platform, data centers and voice-to-text tools.

1. , $800M, defense tech: Castelion, a defense tech startup developing a hypersonic strike missile, raised new Series C funding consisting of $800 million in equity capital along with $250 million in debt financing. , and led the equity financing, which set a $13 billion valuation for the Torrance, California-based company.

2. , $700M, semiconductors: San Jose, California-based Etched, a developer of inference clusters to accelerate AI computing, secured $700 million in a new funding round led by and joined by a long list of prominent investors. The financing set a $21 billion valuation for the 4-year-old company.

3. , $400M, AI video tools: AI video- and image-creation platform Higgsfield closed on $400 million in Series B financing at a $5.4 billion valuation. led the round for the San Francisco-based company, with the financing drawing at least 18 investors.

4. , $350M, data centers: Groq, an operator of 13 data centers across the globe, pulled in $350 million in a new fundraise led by , with planned participation from .The fundraise, which values the San Francisco-based company at $3.5 billion, comes on the heels of a $650 million in June.

5. , $280M, voice-to-text AI: Wispr Flow, a provider of an AI-powered voice-to-text tool called Flow, picked up $280 million in Series B funding at a $2 billion valuation. led the financing, joined by a long list of new and existing investors.

6. , $250M, satellites: Muon Space, a designer, builder and operator of satellite constellations, closed on $250 million in Series C funding led by . The Mountain View, California-based company also recently opened a manufacturing facility in San Jose, California, designed to produce up to 500 satellites annually by 2027.

7. , $150M, micromobility:聽 Also, a spinout that makes electric bikes and small four-wheeled micromobility vehicles, secured $150 million in Series D funding led by . The Palo Alto, California-based startup said the financing will go in part toward accelerating development of its autonomous vehicle platform.

8. , $110M, AI computing: Velaura AI, a developer of AI compute infrastructure focused on ultra-low-power silicon and software technologies, picked up $110 million in Series A funding. led the financing, which set a valuation of over $1 billion for the Silicon Valley-based startup.

9. , $100M, agentic finance: Rillet, a developer of AI-powered enterprise resource planning tools, landed $100 million in Series C funding led by . The round, which sets a $1 billion valuation for the San Francisco company, is Rillet鈥檚 third financing in the past year.

10. , $75M, sleep testing: Happy Health, and Austin-based developer of a ring device for diagnosis and treatment of sleep apnea, raised $75 million from and .

Methodology

We tracked the largest announced rounds in the SA国际传媒 database that were raised by U.S.-based companies for the period of Aug. 15-21. Although most announced rounds are in the database, there may be a small time lag, as some rounds are reported late in the week.

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This month鈥檚 installment of this column is all AI, though applications for the technology range widely, from two startups that apply AI to trash or recycling, to another that promises to help people breathe and sleep better, to a company that says its AI can help architects and builders spot commercial projects before they鈥檙e even announced. Let鈥檚 jump in.

$27M to help recycling plants see what鈥檚 in trash

For decades, the recycling industry has relied on sampling and educated guesses to understand what moves through its facilities. But wants every discarded bottle, carton and wrapper to become data.

The London-based startup said last month that it has raised a 拢20.3 million ($27 million) Series B led by technology investor . The company installs AI-powered camera systems above conveyor belts in recycling plants, then uses computer vision to identify materials, products and brands in real time. Greyparrot says that data helps operators recover more valuable materials, improve sorting efficiency and comply with increasingly strict recycling regulations.

Its systems are now deployed in more than 20 countries and have analyzed more than 1 trillion waste objects, per the company. It counts large waste-processing companies such as and among its customers.

The data gathered at plants also feeds Greyparrot鈥檚 Deepnest platform, which it says consumer brands including , and use to understand what happens to their packaging after consumers throw it away, helping to inform redesigns and comply with Extended Producer Responsibility rules in places such as Canada and the EU.

The fresh funding will help expand the company’s footprint across North America and Europe and support its goal of preventing more than 1 million tons of waste by 2030.

The raise reflects growing investor interest in applying AI in the physical world rather than behind computer screens. Companies in the physical AI sector raised nearly $47.3 billion in the first half of 2026, SA国际传媒 data shows, up nearly 80% year over year, as startups increasingly apply artificial intelligence to settings such as factories, recycling plants and other 3D environments.

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$17M to help robots navigate where GPS can’t

For a recently funded robotics company, the next frontier for physical AI is underground: in mines, tunnels and other places where GPS doesn’t work.

Australian startup said last month that it secured $17 million in new funding. That includes a $10 million equity round backed by , , , and as well as a $7 million venture debt facility from the country鈥檚 National Reconstruction Fund Corp. The company plans to scale manufacturing and expand its AI autonomy and cloud mapping platforms.

Emesent is best known for Hovermap, a LiDAR scanning payload that mounts to drones, vehicles or backpacks to create detailed 3D maps of mines, industrial sites and other hazardous environments. But increasingly, the company’s focus is software. Its Cortex AI platform enables robots to navigate autonomously in environments without GPS, while its Aura cloud platform processes and analyzes the resulting spatial data.

The company says its technology is already deployed at more than 200 mine sites worldwide and that it is expanding into the defense, critical infrastructure and construction sectors.

Its raise is another example of increased interest and investment in physical AI. As industries grapple with labor shortages and increasingly dangerous operating environments, startups that combine robotics, computer vision and autonomy are attracting fresh capital to automate work that’s difficult, dirty or unsafe for humans.

Robotics investment funding overall has been on a tear in recent quarters. Startups in the category raised $15 billion globally in 2025 鈥� an annual record that has already been eclipsed partway through 2026 鈥斅燬A国际传媒 data shows.

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$12.25M for AI that treats congestion with sound

We鈥檝e covered AI that can do dirty work like help sort through trash or navigate underground mines. What about AI to help people breathe?

San Francisco-based medtech startup recently raised an oversubscribed $12.25 million Series A led by . The company develops FDA-cleared, noninvasive devices that it says use AI and acoustic resonance therapy to treat congestion and improve sleep without drugs.

The company said its flagship Sonu band personalizes sound waves based on a user’s facial anatomy to open nasal passages, while its newer Spatial Sleep device aims to help users fall asleep faster and stay asleep longer.

The raise comes as investors continue to back AI-powered medical devices that combine software with regulated hardware. Companies that intersect SA国际传媒鈥檚 AI and medical devices industries raised more than $629 million in the first half of this year, our data shows, up about 33% year over year.

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$3.85M to turn unrecyclable trash into fuel

Trash and recycling emerged as an unexpected theme in this month鈥檚 column. While Greyparrot helps companies better understand what鈥檚 in landfills and recycling plants, another recently funded company, , says it鈥檚 working to turn unrecyclable garbage into industrial fuel.

The Nashville, Tennessee-based company last month announced a $3.85 million round co-led by and to commercialize technology that converts hard-to-recycle plastics and other waste into industrial fuel. The startup says its engineered fuel can replace coal in cement, steel and other heavy industries without requiring factories to modify existing equipment. The new funding will help it build its first commercial U.S. biofuel facility outside Las Vegas.

Global venture investment into cleantech-related startups has been steady but not record-breaking in recent years, SA国际传媒 data shows. Around $15 billion went into rounds for companies in SA国际传媒鈥檚 cleantech-, EV- and sustainability-focused categories in the first half of 2026, putting this year鈥檚 funding on track to slightly exceed the 2025 tally, which was the lowest in several years.

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$3.5M to predict construction projects before they’re announced

The biggest construction opportunities often surface months before the first request for proposals. promises to use AI to spot them first.

The New York-based startup last month raised $3.5 million in seed funding from 鈥檚 accelerator, , and others to build an AI platform for architecture, engineering and construction firms. The startup promises to give such companies an edge over their competitors by helping them discover projects earlier and identify the best path to winning them. Instead of searching public bid databases, Cascade says its tech can analyze signals such as bond filings, property transactions, capital budgets and meeting minutes to identify projects while they’re still taking shape.

Overall funding to real estate-related startups has trended higher in recent quarters, and the sector emerged as a bright spot for seed funding in the first half of 2026, an analysis of SA国际传媒 data shows. Other seed-funded real estate startups this year have spanned areas ranging from streamlining planning and building processes to real estate investing to reducing power consumption in buildings.

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• Sector Snapshot: Cleantech Startup Funding Stabilizes As Energy Demand Grows

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spent much of his childhood in his family鈥檚 St. Paul, Minnesota, convenience store, where he packed cigarette cartons and watched his father run a business seven days a week, 365 days a year.

Hussain was the son of a first-generation immigrant who arrived from Karachi, Pakistan, and worked his way from employment at a to owning his own corner store. That experience instilled in Hussain a work ethic that stuck with him. But his father made a clear trade-off with him in high school.

鈥淢y dad didn’t want me to necessarily come back to the store,鈥� Hussain recalls. 鈥淗e’s like, ‘Look, like this is what I did and built. Go use school as a mechanism to leave.鈥� 鈥�

Ultimately, Hussain went on to form , a New York-based AI startup that automates parts of finance and accounting. Founded in 2023, the company has raised around $90 million, employs about 180 people, and was last valued at $400 million, according to Hussain.

But unlike many tech startup founders, Hussain didn鈥檛 study computer science in college. Instead, he earned a humanities degree at , won a Marshall Scholarship to , left academia abruptly to work at , and spent six years learning the operational ropes at early-stage startup before launching Tabs in 2023.

From St. Paul to Oxford

Hussain leveraged a scholarship from the to attend Cornell, where he fell in love with comparative politics and history. Fixated on academia, he graduated and immediately headed to Oxford to pursue a Ph.D. Two months in, reality hit.

鈥淚 realized this is a terrible idea,鈥� Hussain admits. 鈥淚 grew up … way too scrappy packing the cooler to survive through a postdoc and potentially a very structured 10-year career, which seemed very hard and long and not in my control.鈥�

Deciding to reset his trajectory at 23, Hussaini took a chance on management consulting at BCG in the Midwest. Though it provided an intensive crash course in business operations, spreadsheet modeling and corporate processes, the structured corporate hierarchy lacked the agency he had seen in his father’s store.

By 2015, he decided to embed himself directly into tech, taking a massive pay cut to join Latch 鈥� then a 10-person seed-stage startup 鈥� as its first operations hire.

鈥淗ad I tried to do this directly out of Oxford or out of BCG, I think [it] would have been impossible,” Hussain told SA国际传媒 News in an interview. 鈥淥ne of the things that often keeps many non-traditional founders out is … the ability to access capital, but also understand the playbook of how to build, how to design around a real problem, and build a team.鈥�

Over six years at Latch, as the company grew to tens of millions in revenue, Hussain picked up a few lessons about building venture-backed companies. He learned to pursue large markets, to surround himself with people whose strengths complement his own, and to build for major shifts in technology.

Humanities vision meets deep tech

In 2023, Hussain applied those principles to start Tabs, an AI platform that automates revenue recognition, billing and collections. From the beginning, the founder knew he had to leverage his strengths. He also knew his weaknesses. Hussain recognized that he brought commercial vision and operational execution, not the ability to write code, to the table. So he partnered with a deeply technical co-founder, , to balance his own background.

鈥淚 came from the humanities,鈥� Hussain noted. 鈥淭abs is a deeply technical and complex problem to solve, and so having someone who could augment my vision … was a very important part.鈥�

Investors took notice. Early relationships and the operational credibility Hussain built during his “apprentice” years paid off. Tabs quickly raised a $4 million pre-seed round co-led by and . Since then, the startup has grown to roughly 180 employees, raised about $92 million in total capital, reached a $400 million valuation in its last round, and maintained triple- to quadruple-year-over-year revenue growth.

To Hussain, non-traditional backgrounds in tech are a strategic advantage that fosters the resilience required to survive early-stage uncertainty.

鈥淚 think a lot of non-traditional folks 鈥� have to embrace a ton of volatility, even ahead of being a founder, to make the sacrifices to learn,鈥� Hussain said. “Sometimes it’s just the non-traditional background that allows you to embrace non-traditional ways of learning that ultimately get you into entrepreneurship.”

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• 鈥楴obody Wanted to Give A Former Principal Money鈥�: How An Educator Built An Edtech AI Startup With $63M From VCs
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On the SA国际传媒 Unicorn Board, we track active investors over all time. Here, we look at the investors in the companies that gained horns in the most recent funding cycle to see which firms predominate.

New unicorn counts have picked up significantly year over year. So far this year, 250 companies have joined the board through Aug. 15, up from 2025’s 193 companies. Leading sectors included robotics, AI labs, healthcare and biotech, financial services, AI infrastructure, and AI deployment, among others. Of the companies, 139 (56%) are U.S.-headquartered, and 47 (19%) are from China.

An analysis of SA国际传媒 data finds that most of the funding these companies raised came in 2026: a whopping 75% of all funding 鈥� $74 billion out of $98 billion. By contrast, 30% of deals took place in 2026, the highest count so far by year, with 329 deals. Nonetheless, most deals occurred in prior years, with seed investments starting in 2012, Series A in 2014, and Series B rounds in 2017, though the pace has picked up since 2024.

The Top 10 most active investors in this cohort by investment count were Sequoia Capital, Khosla Ventures, Y Combinator, , , , , , , and .

Y Combinator is the only accelerator on this list and BoxGroup the single seed investor to make the Top 10. (formerly Sequoia Capital China), headquartered in Hong Kong with offices across China, is the notable investor from Asia on this leading list of 29 investors. Private equity firms and are in this leading list, and on the corporate venture capital front and are featured.

Seed portfolio

Y Combinator and Sequoia Capital had the largest seed portfolio counts, with investments of $20 million or less. Seed investor BoxGroup, headquartered in New York, had the third-largest count of seed portfolio companies, a significant achievement since it invests in far fewer companies than Y Combinator and its funds are a fraction of what Sequoia Capital raises.

Also impressive were with five companies at seed, and , Lux Capital and Founders Fund, each with four portfolio investments at seed. Among this cohort, Lux Capital and Founders Fund had the largest crossover, sharing three portfolio companies out of four.

Series A leaders

The most active Series A lead investors were Andreessen Horowitz, with Khosla Ventures and tied with Sequoia Capital at six investments each. Series A investment sizes show a wide range, from $6 million to $500 million. Larger Series A rounds were not dominant but noticeable for many of these firms, except for , Founders Fund and Bessemer Venture Partners.

As funding activity, unicorn creation and valuations accelerated in 2026, the investors with the largest portfolios were those with early-stage access and the resources to continue backing companies as they scale. Established multistage firms dominate the rankings, while only a handful of accelerators, seed specialists, corporate investors, private equity and Asia-based firms break into the leading group.

The next test will be whether this year鈥檚 newly minted unicorns can turn rapid capital formation and lofty valuations into durable, category-defining businesses.

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Venture investors appear to increasingly see physical AI as the next leg of the broader AI boom. Notably, according to a recent article in , many firms known for early bets on software, internet services and social media companies are writing more checks to companies building 鈥減hysical technologies and materials tied to the artificial-intelligence boom.鈥�

SA国际传媒 data backs this up.

In the first half of 2026, global venture funding in the space totaled $47.4 billion across 521 deals, per our data. That鈥檚 up dramatically 鈥� almost 4x 鈥� compared to the second half of 2025 when physical AI startups raised $12 billion across 470 deals. It鈥檚 also up significantly 鈥� by nearly 80% 鈥� from the $26.4 billion raised across 436 deals in the first half of 2025.

To give you an idea of just how much more money is going into physical AI companies, here’s a comparison. In the three years spanning 2022 to 2024 combined, venture investors put a total of $41.9 billion into physical AI companies 鈥� still several billion less than we鈥檝e seen raised in just the first half of this year alone.

And before we go any further, I should clarify that by our criteria, physical AI includes industries such as robotics, autonomous vehicles, aerospace, drones, industrial automation and sensors.

Noteworthy deals

Several multibillion-dollar megadeals drove the spike in H1 investment. One very large deal in particular accounted for nearly one-third of all venture dollars: Mountain View, California-based 鈥檚 raised in February. , , and co-led the financing, which was raised at a staggering $126 billion valuation.

Other companies that have brought in large rounds this year include:

• In May, defense tech startup raised another $5 billion in funding at a $61 billion valuation 鈥� double the $30.5 billion valuation it received less than a year earlier.
• San Diego-based in March landed a $2 billion Series G round co-led by and . Its valuation jumped to $12.7 billion.
• In March, Austin-based , a defense tech startup focused on autonomous sea vessels, raised $1.75 billion in Series D funding, bringing its total funding to around $2.6 billion. led the round, which set Saronic鈥檚 valuation at $9.25 billion 鈥� more than double its Series C level in 2025.

Exits

The physical AI space has also produced several notable exits so far in 2026, although activity has been more concentrated in aerospace, defense and drones than in areas like robotics.

has been the clear outlier, raising $75 billion in its June IPO at a $1.77 trillion valuation. Other notable public debuts include Herndon, Virginia-based space intelligence company , which raised $416 million, and Arlington, Virginia-based autonomous drone maker , which raised $320 million. On the M&A side, one of the most notable deals was roughly $900 million acquisition of Tel Aviv鈥檚 humanoid robotics startup , a transaction the company explicitly tied to its push into physical AI.

Investor POV

, general partner at , told SA国际传媒 News via email that while funding in physical AI has historically been concentrated in robotics and humanoids, defense, and foundational models, he sees the opportunity as much broader. Physical AI, in his view, represents the convergence of software, hardware, sensors and IoT, and services across a wide variety of real-world applications. What is changing, according to Ziegler, is AI’s ability to process data from those systems at such a scale and speed to generate useful operational insights, while the underlying hardware becomes cheaper and more accessible.

鈥淓ven our mobile phones now have LIDAR scanners on them,鈥� he noted, 鈥渄emocratizing the ability to map objects and spaces.鈥�

For Edison Partners, the appeal is particularly strong in high-value, traditionally analog industries where physical AI can become mission-critical infrastructure. Ziegler pointed to manufacturing, supply chain, utilities, agriculture, transportation, government, and physical and spatial intelligence as areas of interest. Many of these companies resemble vertical software businesses, he said, with 鈥渁ttractive unit economics, large deal values and multi-year deployments,鈥� while their combination of software, sensors and hardware can generate proprietary datasets that become increasingly valuable over time. Edison is especially interested in applications where the return on investment is measurable through predictive maintenance, risk management, asset integrity, security and autonomous operations.

The economics of building these companies have also improved considerably over the past two years. Ziegler compared the shift to what cloud infrastructure did for SaaS.

鈥淭he costs to build these companies have come down, and AI infrastructure and multi-modal tech to do so is now available,鈥� he said.

Meanwhile, compute and foundation-model capabilities have become more accessible, reusable models and physics-based simulation have improved, training data is more plentiful, and sensor and hardware costs have declined. At the same time, companies are increasingly bundling hardware into recurring or mixed-revenue models and moving toward outcome- or usage-based pricing. That combination, Ziegler said, makes the hardware itself a distribution mechanism for software and data, with 鈥渉ardware [as] the distribution model for creating a data intelligence flywheel.鈥�

, partner and head of growth at , told SA国际传媒 News via email that while physical industries remain capital intensive, AI and other enabling technologies are changing how efficiently companies can build and scale. Historically, the capital required to reach meaningful scale made investors wary, but he argues that 鈥渢ech barriers are plummeting, experienced talent is pouring in, and market demand is rising.鈥�

That convergence is driving more investment into areas including energy, robotics and autonomy, inference, chips and compute, and data center infrastructure. As a result, he said, funding is increasingly shifting away from experimentation and toward companies that can hit production milestones, land customers and scale efficiently.

For Eclipse, physical AI is not a new theme but a core investment thesis dating back to the firm鈥檚 founding in 2015. Fath said the opportunity has become more compelling because 鈥渢he technical and economic conditions are now catching up to that longstanding conviction,鈥� allowing companies to iterate, deploy products and reach customers faster.

Eclipse defines physical AI broadly as 鈥渋ntelligence embedded in systems that perceive, reason, and act in the real world,鈥� while generally avoiding investments in standalone large-language-model providers. Fath described the firm鈥檚 focus as investing on the 鈥渟houlders,鈥� rather than the 鈥渉ead.鈥� This means that Eclipse backs both the infrastructure that enables generative AI, such as chips, compute, energy and data centers, and the companies applying AI to build new businesses in the physical world.

He views the current landscape as the result of technology, talent, capital, demand and policy finally aligning. More powerful compute, foundation models, simulation and developer tools are allowing smaller teams to build faster with less capital and labor, Fath points out. Looking ahead, he expects value to accrue throughout the physical AI stack, but believes the strongest moats will belong to companies that vertically integrate and own multiple layers.

Ultimately, he said, 鈥渃ustomers value operational efficiency, reliability, and revenue, not technical sophistication alone.鈥� The companies that can turn technical capability into dependable systems at commercial scale 鈥� and then use their data and infrastructure to expand into additional products 鈥� are likely to capture the most value.

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In turn, semiconductor giants are investing record sums in startups. So far this year, the sector鈥檚 most valuable companies have participated in rounds collectively valued at over $250 billion, per SA国际传媒 data. That鈥檚 multiples above prior high marks.

Large cap chip companies are also leading and co-leading some of the biggest financings. This includes 鈥檚 record-breaking $122 billion March funding round, in which was one of eight lead investors.

The other big deals

There鈥檚 no getting around that the OpenAI megaround really skewed the 2026 totals. That one deal accounts for over 95% of the value of all semiconductor company-led financings.

Still, there are plenty of other big rounds with semiconductor backing this year that, by any other comparative benchmark, would also be considered enormous. Take July鈥檚 $5 billion corporate financing from Nvidia for foundational AI startup .

So far this year, corporate semiconductor giants have invested in more than 60 startup financings of $100 million or more. Of those, 16 rounds were valued at $1 billion or more, which we list below.

Most active and highest spending semiconductor investors

It should surprise no one that Nvidia is the most active and highest spending corporate investor in the semiconductor space. The AI chip architect has participated in a record 59 known funding rounds so far this year, per SA国际传媒 data, up from 53 in all of 2025.

With a market cap around $5.4 trillion and a continued reign as the world鈥檚 most valuable public company, Nvidia certainly has the financial resources to invest heavily in startups. The company is also active as a lead investor, having led or co-led at least 11 private company financings this year, per SA国际传媒 data.

, with 19 private company financings this year, is also upping its startup investment activity in tandem with what鈥檚 been a strong year for its own shares. This year鈥檚 tally includes at least four rounds valued at $1 billion or more.

Another standout is , with at least 17 known startup investments so far this year. The South Korean megacap has a lengthy history of active participation in seed and venture deals.

The corporate investment tallies also don鈥檛 represent the full extent of semiconductor companies鈥� involvement in the venture funding ecosystem. Additionally, some invest through backing outside venture funds.

Is this peak?

With semiconductor companies raking in profits from the AI boom, and shares soaring alongside, it鈥檚 worth considering whether we may be close to a peak for semiconductor startup investment. On the other hand, if industry leaders鈥� shares keep rising, the sums spent on startup dealmaking look comparatively small relative to semiconductor giants鈥� swelling valuations.

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

is back raising another $5 billion, after it raised that amount eight months ago. The largest fundings also went to an AI neolab, data center and electricity storage, defense, coding and biotech. Let鈥檚 take a look.

1. , $5B, data platform: Databricks has surpassed a $7 billion revenue run rate, with more than 80% year-over-year growth in Q2. The San Francisco-based company raised $ 5 billion in a funding round led by with participation from , , and new investor . Databricks was valued at $134 billion back in December 2025 when the company announced it had surpassed a $4.8 billion revenue run rate. From its Series A funding of $13 million in 2013, the 13-year-old company has raised around $25 billion in funding over all time, per SA国际传媒 data.

2. , $1.1B, AI reinforcement learning: Founded earlier this year, River AI raised $1.1 billion across its seed and Series A rounds led by and , with strategic investment from and . Its founder, , has been at the center of AI developments at , and over the past decade. The Palo Alto, California-based company seeks to build AI that is personalized and trained directly on what a company or person needs to accomplish, giving the end user control.

3. , $750M, electric grid: Form Energy raised a Series G funding round led by . The Massachusetts-based company builds longer-lasting 100-hour batteries for grid electricity storage. A host of investors participated, including private equity, venture and angels, and infrastructure and climate-focused investors , , , , , , and the .

4. , $250M, defense: Neros Technologies, a defense drone manufacturer and drone interceptor, raised a $250 million Series C led by and . The Los Angeles-based company, founded in 2023, has raised $370 million to date, per . The company announced that by 2028 it will be building 1 million drones per year. It has contracts with the U.S. military and half a dozen allied countries across Europe, Asia and the Middle East.

5. , $143M, AI code review: CodeRabbit, which has developed an open-source AI code review technology used by 150,000 open-source projects and 17,000 customers, according to the company, is on a roll. London-based and Los Angeles鈥� led its Series C, and the Walnut Creek, California-based company plans to set up a London office based on customer interest across Europe. As coding becomes increasingly automated, code review is critical to determine which projects meet production standards.

6. , $136M, datacenter networking: Point2 Technology, which builds interconnect solutions for AI data centers, raised an extension of its Series B led by Korea-based , including a strategic investment from and participation from existing investor . The San Jose, California-based company raised $136 million in the Series B.

7. , $110M, organ preservation: Bridge to Life, a 21-year-old organ preservation company, raised a $100 million Series C funding led by and . The Illinois-based company is developing an organ viability assessment tool to expand the market and will use the proceeds to extend its VitaSmart technology to U.S. transplant centers.

8. (tied) , $100M, protein therapeutics: Aureka Biotechnologies, an AI-native drug discovery platform, raised $100 million in Series B funding led by . Based in Shanghai and California, the 3-year-old company has raised $200 million to date. Proceeds will go toward training its model with its lab-in-the-loop feedback mechanism.

8. (tied) , $100M, loyalty rewards: PointsKash, a loyalty reward mobile app, raised private equity funding led by . The Florida-based company provides in-store kiosks for cash, loans and rewards.

10. , $90M, biotechnology: Epicrispr Biotechnologies, a developer of genetic medicines, raised a $90 million Series C led by and . The San Francisco-based company develops treatments for neuromuscular disease through modulating genes.

Large non-US deals:

Several startups based outside the U.S. also raised notable rounds this week. They include:

, $400M, automated applications: Lovable raised a $400 million Series C funding led by and , valuing the company at $13.3 billion. The Stockholm-based company claims 900 million visits each month and 60 million projects created. Lovable鈥檚 Series B raise in December 2025, co-led by Menlo Ventures, valued the company at $6.6 billion.

, $300M, defense: Cambridge Aerospace, a U.K. defense tech company, raised a $300 million Series C led by . The 2-year-old company raised a $200 million Series B in April led by and . Since its Series B funding, the has committed to purchasing its Skyhammer air defense system to intercept drones and low-speed missiles.

Methodology

We tracked the largest announced rounds in the SA国际传媒 database that were raised by U.S.-based companies for the period of Aug. 8-14. Although most announced rounds are in the database, there may be a small time lag, as some rounds are reported late in the week.

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Leading sectors by count were financial services, robotics, AI orchestration, multimodal AI, energy and the semiconductor industry.

In the past two months, the board added more than $100 billion each month in value from newly minted unicorns. Three companies joined the board at decacorn values. , and together added $49 billion in the past month.

The U.S. counts 19 new unicorn companies, just under half of the newly minted unicorns in July. China, the second-largest country, numbered eight. From the U.K., there were three companies, and from Singapore, two. Lithuania, Germany, Spain, Hungary, Australia, India, Israel and Hong Kong each count one.

Among the newly minted unicorns, 15 were less than 3 years old. And seven companies were more than 10 years old.

So far this year, the count of new unicorns has accelerated. A total of 195 companies joined in H1 this year, already exceeding the total for all of 2025.

New unicorns in July

Here are July’s new unicorn companies:

Financial services

• Singapore-based , an affiliate of the private payments company , raised a $1.2 billion Series A funding round with participation from Ant Group and . Ant International was spun out in 2024 and was valued at $11.2 billion in this recent funding.
• , a digital banking platform for banks and credit unions, raised $115 million in private equity funding led by . The 9-year-old San Ramon, California-based company that supports customer retention and services was valued at $1.6 billion.
• Budapest-based , an auto insurance provider using AI, raised a $23 million Series B funding round led by . The almost 2-year-old company, founded by a Serbian team, was valued at $1.6 billion.聽 Ominimo reports $350 million in gross written premiums and is approaching 1 million customers. It operates in Hungary, Poland, the Netherlands and Sweden, and plans to expand across Europe and to the U.S. in 2027.
• , an AI-native private bank for high net worth business owners, raised a $70 million Series B led by . The 4-year-old San Francisco-based company was valued at $1.2 billion.
• , a membership and savings app for U.S. consumers, raised $65 million in Series D funding led by . The 10-year-old San Francisco-based company was valued at $1.2 billion. Surpassing $200 million in net revenue in 2025 from membership and transactional revenue, the company says it is growing 50% year over year and is approaching 1 million members.
• London-based , a savings app which has become a digital wealth management platform, raised a $60 million secondary market transaction led by . The 11-year-old company was valued at $1.1 billion. The secondary sale is to provide liquidity for long-term employees. The company is profitable and has helped 200,000 people buy their first home.

Robotics

• Guangdong-based humanoid robotics company raised $200 million in pre-IPO funding. The 4-year-old company is focused on entertainment, hospitality, and service for humanoid robotics, not manufacturing, with half of its orders coming from outside of China. The company was valued at $2.2 billion.
• Shenzhen-based , a builder of precision tactile sensing technology for robotics, raised $148 million in Series E funding. The 10-year-old company was valued at $1.5 billion.
• London-based , a humanoid robotics company for manufacturing, retail and logistics, raised a $152 million Series A funding led by . The 2-year-old company was valued at $1.4 billion and plans to roll out its wheeled beta version robots to customers in Q4. It has also developed a software brain, KinetIQ, to reason and execute complex tasks alongside humans.
• Full-stack physical AI company emerged from stealth with a $300 million seed funding led by and . The less-than-1-year-old Cambridge, Massachusetts-based company focused on manufacturing and logistics was valued at $1.1 billion.
• , an embodied intelligence company, raised a $147 million seed funding round led by and . The less than 1-year-old Nanjing, China-based company is focused on closed-loop learning, building robotics for manufacturing with the ultimate goal of building a general-purpose robot for the home. The company was valued at $1 billion.
• Dexterous hand robotics company raised a $74 million Series A funding led by . The 1-year-old Hangzhou, China-based company was valued at $1 billion.

AI

• Lithuania-based , a public data web scraping service useful for AI applications and agentic AI, raised its first external financing, a $130 million Series A led by . The company reports $350 million in ARR serving 350,000 tech teams. The 11-year-old company was valued at $3.6 billion.
• Spain-based , a compression technology for AI that improves efficiency and cost, whether on device or in the cloud. It raised a $570 million Series C led by , and . The 7-year-old company was valued at $2.3 billion.
• , creator of synthetic users for consumer research, raised a $200 million Series B led by and . The company raised a $100 million Series A five months earlier. The 1-year-old Palo Alto-based company was valued at $2 billion.
• runs a full-stack platform for companies to train models and agents. It raised a $130 million Series A funding led by . The 2-year-old San Francisco-based company was valued at $1 billion.
• , an enterprise infrastructure management platform for AI, raised a $100 million Series D led by . The 7-year-old San Jose, California-based company was valued at $1 billion.

Multimodal AI

• Beijing-based , a text prompt-to-AI short video startup, raised a $2.8 billion funding round led by , , , , and . The 2-year-old company, a subsidiary of with plans to spin out, was valued at $18 billion.
• , a company that creates 3D visualization from text or image prompts, raised a $400 million Series B funding led by , and . The 5-year-old Sunnyvale, California-based company, used in gaming, 3D printing and design, was valued at $1.5 billion.
• , which provides access to leading models for text, video, image and audio while retaining user privacy, raised a $65 million Series A led by . The service stores communication on a user鈥檚 device. The 2-year-old Wyoming-based company was valued at $1 billion.
• Beijing-based , a multimodal model developer, raised a $222 million Series C led by ,, and . The 3-year-old company, used for film, marketing, and social media content creation, was valued at $1 billion.

Energy

• Munich-based nuclear fusion company raised a $470 million Series B led by , , and . The company has offices in Munich, Zurich and Oxford. The 3-year-old company was valued at $2.7 billion.
• a provider of thermal energy storage for data centers, raised a $550 million Series C funding led by and. The 8-year-old San Jose, California-based company was valued at $2.5 billion.
• , a hydrogen-boron fusion company, raised an undisclosed seed round led by , and . The less-than-8-year-old China-based subsidiary of the was valued at $1.6 billion.

Semiconductor

• Israel-based , a fabless semiconductor company building data processing units and chips for data centers and computing systems, raised a $300 million Series E led by . The 9-year-old company was valued at $2.8 billion. The next generation of will be routing via the company鈥檚 X2 chip, according to VP of Starlink engineering, .
• Shanghai-based developer of a satellite communication baseband chip for 6G communications, raised an undisclosed amount following a $216 million Series C round earlier this year. The 6-year-old company was valued at around $1.5 billion.
• , a chip company that connects smaller chips to make them more efficient, raised a $145 million Series C led by . The 5-year-old Santa Clara, California-based company was valued at $1 billion.

Cryptocurrency

• Singapore-based , a regulated app for buying, trading, and spending cryptocurrencies, raised a $400 million corporate round. Led by , this marks the company鈥檚 first institutional funding. The 10-year-old company was valued at $20 billion.
• , a U.S. stablecoin digital clearing bank for international financial institutions, raised a $180 million Series B led by . The 4-year-old San Francisco-based company was valued at $1 billion.

Defense

• Former Doge employees founded to provide AI-driven cyber capabilities to the U.S. military. Cathedral raised a $160 million Series A led by and . The less-than-1-year-old Washington, D.C.-based company was valued at $1.4 billion.
• London-based , a maritime defense company, raised a $175 million Series B led by . The 6-year-old company was valued at $1 billion.

Marketplace

• , a technology platform for service businesses, raised a $44 million Series D led by . The 10-year-old New York-based company was valued at $1.2 billion. Genius AI operates in the wellness, beauty and health sectors and is approaching a $200 million revenue run rate.

• , a platform for travel advisers, raised a $60 million Series D led by and . The service has 15,000 travel advisers and has booked more than $3 billion in travel over time. The 5-year-old New York-based company was valued at $1 billion.

Data center

• Mumbai-based , a data center service hosting GPUs, one of the largest GPU compute providers in India, raised $150 million in funding. The 7-year-old subsidiary of the was valued at $3.9 billion.

Insurance

• , an insurance platform for some of the largest e-commerce customers, raised $100 million in funding. The 12-year-old New York-based company was valued at $1.9 billion. Its customers include , , , , and , to name a few.

Quantum

• Quantum computing company raised a $300 million Series A led by , and . The less than 1-year-old South Pasadena, California-based company was valued at $1.5 billion.

AI coding

• Autonomous app building startup raised a $130 million Series C led by , and . The 2-year-old Pleasanton, California-based company was valued at $1.5 billion. The company launched a year ago and has enabled non-coders to build applications, with 12 million built on the platform.

Legal

• , an AI legaltech firm that pairs lawyers with agentic AI, raised a $120 million Series C led by . The service is client-oriented, with payments based on outcomes rather than billable hours. The 3-year-old New York-based company was valued at $1.2 billion.

Security

• , an endpoint security firm for the AI era, emerged from stealth, announcing a $100 million Series B led by , , and . In 2025, ahead of launching out of stealth, Glow raised large seed and Series A rounds. The 1-year-old Palo Alto, California-based firm with offices in Tel Aviv was valued at $1.2 billion.

Wearables

• Hong Kong-based smart glass company raised a $150 million Series B led by and . Founded by ex- engineers, the startup is not camera-based but rather a display that beams information visible to the wearer.聽 The 2-year-old company was valued at $1 billion.

Related SA国际传媒 unicorn lists:

• (1,850)
• (644)
• (245)
• (193)
• (117)
• (102)
• (953)
• (546)
• (251)
• (39)
• (491)

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• Global New Unicorn Counts In The First Half Of 2026 Have Already Surpassed 2025鈥檚 Totals

Methodology

The SA国际传媒 Unicorn Board is a curated list that includes private unicorn companies with post-money valuations of $1 billion or more and is based on SA国际传媒 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 鈥� such as those set via a 409a process for employee stock options 鈥� as these differ from, and are more likely to be lower than, a priced funding round. We also do not adjust valuations based on investor writedowns, which change quarterly, as different investors will not value the same company consistently within the same quarter.

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

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

Please note that all funding values are given in U.S. dollars unless otherwise noted. SA国际传媒 converts foreign currencies to U.S. dollars at the prevailing spot rate from the date funding rounds, acquisitions, IPOs and other financial events are reported. Even if those events were added to SA国际传媒 long after the event was announced, foreign currency transactions are converted at the historic spot price.

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Before founding , an AI startup for the construction industry, spent more than a decade working in construction. She grew up in a low-income household in Austria, where her father was a carpenter. When the family needed extra money he would take his children to job sites, and Buchner began working as a carpenter as a teenager.

鈥淚鈥檓 a blue-collar worker by background,鈥� she explained.

Buchner never really left the industry. She worked her way up and eventually became a general contractor, managing large construction projects in Europe. But her career took a turn after a worker died on one of the sites she was running.

Experiencing the fatality changed the way she thought about her work.

鈥淥nce you realize that people die under your management, you just look at life differently,鈥� Buchner said.

She decided to build a health and safety app for construction workers. That company was separate from (and before) Trunk Tools, but the project pulled Buchner into software and eventually led her to pursue a Ph.D. focused on data science in construction and early artificial intelligence.

While doing that research, she realized something that would later become central to Trunk Tools: Construction companies produce huge amounts of information, but much of it is fragmented across different systems and buried in documents, making it difficult to analyze.

鈥淭he data was there,鈥� Buchner said, but it was 鈥渟o messy and so unstructured鈥� that traditional data analytics could only go so far.

Turning construction data into an AI business

Buchner saw an opportunity to make that information more useful. She also decided she wanted to build the company in the U.S. rather than Europe.

In 2019, she moved to California to attend . She founded Trunk Tools in 2021 while she was still in business school, graduating in 2022. The early years were messy, as they often are for startups, and Buchner said the company did not really find its first meaningful product and market until 2023.

By then, advances in large language models were beginning to make it more practical to work with large quantities of unstructured information.

That was particularly relevant in construction. Buchner estimates that an average construction site can involve 3 million to 4 million pages of documentation spread across numerous systems. Trunk Tools integrates with those systems and creates a layer on top that can analyze the information and use it to carry out various tasks.

The company sells primarily to general contractors and subcontractors, and has also begun working with some project owners.

Trunk Tools鈥� AI agents can review contracts and construction drawings, flag inconsistencies and help with specifications, submittals and bidding, and pass that information among different workflows. For example, one agent can uncover an issue in a drawing and give that information to another agent to figure out next steps and how any changes might affect other parts of a project.

Such an ability to connect information across a project is important because construction projects are unusually complex, Buchner said.

鈥淔or a human brain, it鈥檚 impossible to calculate the second- and third-order effects of changes because of how complex and connected it is,鈥� she said.

In one case, Buchner said, a project owner requested a change that a construction company might otherwise have simply begun implementing. Trunk Tools calculated that the change would add nearly $4 million to a roughly $100 million project. Once the contractor presented the cost to the owner, the owner decided not to proceed.

In another instance, a worker got chemicals in their eye, and someone nearby used a Trunk Tools agent to ask what to do. The system returned step-by-step instructions for responding to the exposure.

鈥淲ith stuff like that, you have to act fast,鈥� Buchner said, calling it a particularly meaningful example for the company.

From early product to rapid growth

New York-based Trunk Tools now has more than 100 employees. Buchner is a solo founder and said her Ph.D. gave her enough of a technical background that she did not feel she needed to seek out a technical co-founder. She did, however, hire experienced AI engineers early and has since built out a larger technical leadership team.

The startup has also expanded the number of products it offers. Buchner said Trunk Tools had two live AI agents about a year ago and now has more than 10. The pace of development has become fast enough, she said, that the company sometimes struggles to train its own sales and customer-success teams on new products as quickly as they are being released.

The company has raised about $70 million in funding from investors such as , and . Revenue grew fourfold last year and is on track to grow roughly 3.5x this year, according to Buchner. Its most recent funding round was a $40 million Series B in 2025 that valued Trunk Tools at $325 million.

An unconventional founder advantage

Fundraising was more difficult at the very beginning, Buchner shared, in part because she did not fit the mold investors often associate with startup founders.

鈥淚 think it was hard very early on because I might not look like the traditional tech founder,鈥� she said.

But after Trunk Tools gained traction, Buchner believes her industry background became an advantage. She had spent years doing the work her customers do and could answer detailed questions about construction in investor meetings.

鈥淚 walk into a room full of investors, and I know that 鈥� I鈥檓 definitely the smartest person in the room when it comes to my industry,鈥� she said.

Bringing AI to a tech-wary industry

Historically, the construction sector has been slower than others such as finance and legal services to adopt new software or technologies. One reason for this, Buchner believes, is that there is often a long distance between the person buying a product and the person expected to use it.

Executives may make purchasing decisions while sitting in an office. Meanwhile, the actual users are often out in the field working on job sites and under constant pressure to keep projects moving. Contractors also typically operate on relatively thin margins. So if a bad decision is made around purchasing technology, the potential cost is greater.

Still, Buchner believes that AI is being adopted faster than other technologies she has seen enter the construction industry.

Over time, Trunk Tools has also learned that simply selling the software is not always enough. The company now provides training and change-management services for customers trying to roll out AI across large organizations.

It鈥檚 another area where having an industry background makes a difference, in Buchner鈥檚 view. Rather than sticking to a model of what a conventional software business is supposed to look like, she said, she is more focused on what construction companies actually need.

鈥淚鈥檓 just thinking about solving a problem,鈥� she said.

Looking back, Buchner said she always expected to start a business someday. For years, she assumed it would be her own construction company.

Instead, the carpenter-turned-contractor ended up building a software company for the industry she had already spent much of her career working in.

Related SA国际传媒 query:

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

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

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

Unlike a traditional parcel carrier, ClearJet doesn鈥檛 own the planes transporting those packages. Instead, its asset-light 鈥淯ber for cargo鈥� model taps available capacity on flights that are already traveling between cities. The startup says its approach can cut shipping costs by as much as 35% while speeding deliveries by one to three days.

鈥淲e鈥檙e basically connecting with the already moving aircraft,鈥� Guggenheim told SA国际传媒 News in an interview. 鈥淭hese flights are going from A to B city. We鈥檙e taking those same routes, and that鈥檚 just why we鈥檙e so fast. That鈥檚 also why we鈥檙e so cost efficient.鈥�

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

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

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

How it works

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

鈥淲e call it the super carrier because it truly is that, and it gives all the power back to the retailer,鈥� Guggenheim said in an interview with SA国际传媒 News.

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

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

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

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

鈥淲e looked at a few supply chain businesses over the years,鈥� Ziegler said. 鈥淐andidly, most of them went bankrupt because they took an asset-heavy approach to the middle mile.鈥�

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

鈥淲hen you think about what they built, it is a very unique aviation infrastructure platform, and it鈥檚 difficult to replicate,鈥� he said. 鈥淗e鈥檚 [Guggenheim] proven the business model, and the unit economics work.鈥�

Backstory

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

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

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

Shipping had become the second-largest cost of goods outside of the product itself for his business, he said. And in 2019, after spending $55 million with , Guggenheim said he received an email giving him five days鈥� notice that his account was being canceled because it wasn鈥檛 profitable enough.

鈥淎nd so I said, 鈥榯here has to be a better way,鈥� 鈥� he said.

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

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

鈥淚 said, 鈥業 want to start flying packages from LA to New York. Do you have any flights?鈥欌�� Guggenheim recalled. 鈥淎nd he put his arm around me and said, 鈥榊ou and I are going to be best friends.鈥欌��

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

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

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

AI component

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

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

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

This includes features such as responding to weather disruptions by moving packages onto a different flight or through a different city, something ClearJet can do because it isn鈥檛 tied to just one airline.

鈥淲e鈥檙e building an entire agent team, an army of agents that do everything that the humans were doing,鈥� Guggenheim said.

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

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

鈥淲e have a really big appetite for giving consumers a better visual experience with their packages,鈥� he said.

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

鈥淲e saw this as an opportunity to actually create a category-defining business,鈥� he said.

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

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