That was the intent of our latest 兔子先生传媒 News data dive into seed-stage trends. For this installment, we focused on mid-sized rounds of between $5 million and $10 million, analyzing around 800 global seed financings that closed this year.听

Why this range? In a startup investment climate characterized by the ascendance of megarounds, the idea was to focus on rounds more representative of the classic seed deal: a risky bet on unproven founders, technologies or business models.

Using this methodology we identified multiple popular investment themes and zeroed in on five. The first 鈥� cybersecurity 鈥� we tackled in a separate piece. Here we delve into the other four: proptech, cancer therapeutics, space tech and robotics.

No. 1: Proptech

Real estate is the world鈥檚 most valuable asset class, providing startups a huge and varied addressable market. By one estimate a few years ago, real estate accounted for a staggering two-thirds of global net worth.

Given the size of the space, actual venture investment tied to real estate and construction looks comparatively meager. Last year, per 兔子先生传媒 analysis, proptech startup investment totaled just over $10 billion, far below peaks hit several years ago.

Seed investors seem to believe there鈥檚 a good case for startup driven growth ahead. In particular, they鈥檙e funding a lot of rounds in the $5 million to $10 million range for companies looking to add efficiencies to the planning and building process, streamline rental operations, reduce building power consumption, and more.

To illustrate, below we put together a sample set of 15 companies that closed seed rounds in our target range this year:

A few standouts include , an AI-powered home management system, , a developer of software to support real estate decarbonization, and , an AI-enabled construction supply chain platform.听

No. 2: Cancer treatments

Startup founders don鈥檛 need persuasive superpowers to convince investors that cancer is a sufficiently serious area to address. Today, it鈥檚 that 39% of Americans will be diagnosed with cancer at some point in their lives. Cancer also ranks as the second leading , behind heart disease.听

Seed-stage companies aren鈥檛 expected to bring down numbers in the near term, but as they progress, it鈥檚 increasingly plausible. That鈥檚 the apparent mindset for investors at this stage, who鈥檝e backed a good-sized number of rounds in the $5 million to $10 million range this year for developers of cancer therapeutics and diagnostics, charted below:

Three California startups secured $10 million, the largest financing in our sample set. They include: , which is working on AI-driven discovery of undetected cancer targets, , a developer of targeted therapies for solid tumors, and , which is focused on cancer diagnostics.

No. 3: Space and satellite tech

This year鈥檚 most attention-getting event in space tech finance was obviously the IPO of sector pioneer . But while that debut may have dominated headlines, quite a few smaller, earlier, lower-profile deals were also getting done.

Per 兔子先生传媒 data, space tech was a popular area for seed financings in the $5 million to $10 million range. To illustrate, below we put together a sample set of nine such companies that raised rounds this year:

The largest fundraiser in our target range was , which is focused on developing reusable satellites. Next was , focused, as its name implies, on in-space propulsion systems, followed by , developer of an ML-native operations platform for satellite fleets.

No. 4: Robotics

Robotics is a perennial favorite in our seed-funding data dives, including the last one, focused on AI. This time, the sector made the ranking again, thanks to a bevy of intriguing seed-stage companies that met our parameters.

Turns out, you can jumpstart some highly ambitious ventures on a $5 million to $10 million seed round. To illustrate, below we aggregated a sample of 18 funded this year:

Robotics was also the most geographically dispersed sector in our lineup, with startups hailing from Asia, North America, Europe and Australia. A few that stood out include , a developer of what it calls 鈥渋ntimacy robots,鈥� , a maker of autonomous underwater robots, and , focused on robots for greenhouse harvesting.

Big picture: Midsized seed rounds for outsized ambitions

Overall, seed funding trends reviewed above may tell us more about the kinds of companies investors are willing to bet on than about the sectors attracting interest, which are already well-established.

Clearly, startup investors still believe that small, modestly funded teams with grand missions remain a worthwhile and viable wager. That鈥檚 particularly encouraging these days, when the venture and seed financings we most commonly hear about tend to be the largest ones.

That鈥檚 not to diss large rounds. Startups that are led by prominent serial entrepreneurs or have established traction hold obvious appeal, even at pricier terms. But for those of us who enjoy rooting for the underdog, it鈥檚 encouraging to see lower-profile companies with outsized ambitions are still in the game.

Related 兔子先生传媒 lists:听

Related reading:

• AI Seed Investors Flock To Cybersecurity听
• In Charts: Seed Deals Keep Getting Bigger As Odds Of Reaching Series A Fall Dramatically听
• AI Seed Trends: More Multimedia, Backend Automation, Agentic Security, And Yes, Robots

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has spent nearly two centuries adapting to successive industrial revolutions 鈥� evolving from a 19th century steel and heavy machinery company into a global leader in energy management and automation. Now, through its 1 billion Euro venture fund, , the company is betting that the next transformation will be driven by AI’s collision with the physical world, from data centers and power grids to robotics and industrial automation.

For , who joined SE Ventures in 2022 after leading corporate investments at , AI’s biggest opportunities extend well beyond software. As demand for compute strains energy infrastructure and accelerates reindustrialization, the firm is backing startups building the technologies that underpin the AI economy 鈥� investing in everything from data center infrastructure and grid resilience to robotics and industrial AI.

兔子先生传媒 News spoke with Chaturvedy about where those opportunities are emerging, why energy has become AI’s defining constraint, and how industrial technology is being reshaped by the AI era. 鈥淲e were set up with the intent to figure out where the market is headed,鈥� he said.

The significance of the energy and industrial sectors has grown with AI, and that has led even traditionally tech-focused venture investors to rush into the space. 鈥淭oday, the scarce resource in this entire space is the capacity to build 鈥� building, real estate, energy, power and electrification gear,鈥� Chaturvedy said.

SE Ventures , and has notched 12 exits including its most recent, , a 3D metal printing technology acquired by Tokyo-based electronic manufacturer

The firm will often take board seats or board positions and work to bring value to its portfolio companies.

Around 80% of the startups in its portfolio have some level of commercial relationship with a business unit of Schneider Electric. Most often that鈥檚 as a partner servicing Schneider’s customers, which is the holy grail, according to Chaturvedy. Sometimes it鈥檚 as a vendor, although that remains a smaller set of use cases.

In our conversation, we spoke about power scarcity, the electrical grid, workforce training, reindustrialization and notable portfolio companies.

The interview has been edited for length and clarity.

Gen茅 Teare: Which sectors or investments are you focused on? Where there is a lot of drive or interest because of what is happening in AI?

Chaturvedy: Three things come to mind, especially in terms of the areas we invest in versus the broader construct of the market.

First, AI is getting embedded, and you need to train models, whether open source or proprietary. Model training has upleveled to inference so you need AI infrastructure. is a great example of that.

Five years out, when this CapEx cycle starts to come down and new data centers are perhaps not getting created, data center efficiency will become a hot topic. We are also investors today in a company called , which focuses on that problem. That will come three, five or seven years out. It is going to come. It is not a problem today because we are on the upswing of the CapEx cycle.

Together AI and Hammerhead AI are very interested in partnering with Schneider Electric, because Schneider Electric is a leading electrification player in the data center space. It makes a lot of gear and equipment that go into these data centers. Today, the scarce resource in this entire space is capacity to build: buildings, real estate, energy, power and electrification gear.

The other market impacted by the emergence and growth of AI is the interplay with the grid. There are more demands on the grid beyond the electrification of vehicles, and it is 100x or 1,000x bigger than what we saw with vehicles needing to get charged from inside houses. The grid could not keep up with that capacity in the past, and it certainly cannot keep up with these demands today.

More project developers are coming in and setting up renewables or other types of capacity, but again, the interplay is still with the grid. Anything that helps with grid resilience is clearly an area for us to invest in.

The third thing is the transformative impact of AI on the world of industrials. That is where we are quite excited. Robotics is one clear area where a general-purpose model can allow the same robotics hardware to do multiple different tasks that were not possible in the past, because cognition and inference were not possible at the edge before the advent of large language models.

Companies like in our portfolio 鈥斕齱hich is one of the most exciting companies at the intersection of robotics and AI 鈥� are market-leading indicators of where this world is headed.

There is also an element of using AI to deliver better use cases in the field. Companies like in our portfolio essentially capture warranty data, analyze it and feed results back to design engineers in big corporations. There are a lot of OEMs and hardware companies looking for select use cases where AI can actually be very transformative.

That is what customers are looking for: How can AI be transformative for my business? Whichever startup is working with me in that transformation journey is the startup that will move from POC to adoption overnight. That is essentially the world of successful startups.

Overlaying on top of this is a confluence that we see and watch from our vantage point. When you think about the energy efficiency that needs to happen in these industrial worlds, energy technologies and industrial technologies have to collaborate and deliver those use cases while being energy efficient. That was not the case in the past. Energy was cheaper and more readily available.

Now industrial is taking off. There is more AI adoption. The workforce is getting older, and there is no way to overnight train a workforce in America, so you have to rely on AI. You are going to consume more and more AI for industrial use cases, which was never a business imperative in the past.

This is where the worlds of enterprise and industrial are colliding very quickly in the world of AI.

Increasingly, what I hear is that the bottleneck for AI at this point is energy. Are you seeing some short-term solutions that help with this? What about longer-term technologies?

Chaturvedy: It’s very clear that from a short-term basis 鈥� and this isn’t quite an energy-related solution 鈥� it’s more about tokens. If you think about the unit economics of an AI data center, it’s the tokens. To generate a token, it costs electricity. To train your model, or infer from a model, you need a lot of tokens. The bigger the model, the bigger the data set, and the more complex the use cases, the more tokens.

Ultimately, it’s a battle of producing tokens cheaply and also consuming fewer tokens through the models that exist today. That’s where optimization is happening, but that’s more in the enterprise space: How can I write clever versions of software that allow me to do essentially that?

The longer-term solution is going to be about 鈥� actually, maybe there is a middle layer also 鈥� beyond the tokens: When I’m running my data center, can I push inference to a different point in time so I’m not consuming peak electricity rates? Can I manage my HVAC better? You need cooling systems to cool your data center environment, and there are techniques that work really well there. Schneider has also bought some assets in the past.

Then the longer-horizon cycle is really about creating new generation capacity, largely through renewables, hopefully. That’s where I think the whole renewable story, at least in the U.S., becomes very interesting going forward. Related to renewables is storage, which we haven’t touched upon, but BESS 鈥� battery energy storage systems 鈥� is another space that we look at very closely.

There is a huge discussion in Europe and in America around reindustrialization. How do you see that playing out, given the sectors you’re focused on, industrialization and energy?

Chaturvedy: I don’t think America or Europe really have a choice other than to reindustrialize, given the geopolitical situation and a variety of other factors that I’m sure you fully track as well.

We know that technologically, the U.S. has a competitive advantage. We produce great software engineers, we move fast, and innovation is the lifeblood of U.S. society. There is a lot of innovation happening here, whether it’s robotics, newer models, setting up data centers, energy generation, and so on. That’s where the U.S. is going to lead as we think about reindustrialization: training the workforce, doing things more automatically, with the holy grail being AI startups that result in lights-out manufacturing facilities.

That becomes more of a possibility now. We are never going to be able, in my opinion, in the next three to five years, to replace an aging workforce and expect them to be trained to the same level that a technician with 30 or 50 years of experience was at. But it is now possible that every blue-collar worker with AI in their hands as an assistant becomes a knowledge worker.

Earlier, we used to think about knowledge workers as IT people or white-collar jobs. I think that’s changing. Everybody will be a knowledge worker. AI will be such an equalizer in that sense. There will be different use cases in different environments, but that doesn’t change the business reality. Everybody becomes a knowledge worker.

The second thing to note is that not every job will come back. There is a reality of inflation, cost of living, and the quality of living in America that people are used to, whether it’s base pay, hazardous environments, number of shifts or what have you. As a society, we’ve made certain choices. We’ll be smart about how we leverage more AI and more robotics to get what we want, and not try to emulate other manufacturing-heavy geographies.

But as an economy, as more AI comes, we will move to a different level in terms of what constitutes the GDP of America and the goods and services underneath.

How long do you think that takes to play out?

Chaturvedy: There are certain industries where it’s already happening, data centers being at the forefront. Mainly because the need is very urgent, and there are significant dollars at play today in the data center space, where people are willing to spend the money. In a capitalistic society, everybody is going to chase money. The data center happens to be that today.

But in the next three to 10听 years, depending on the CapEx refresh cycle of different industries, we will see more greenfield projects emerge that are natively robotics-oriented and natively industrial automation-oriented, because AI has already caught up.

Right off the bat, every new factory that gets online in the next seven to 10 years will have a basic level of productivity that is way higher than a new factory set up 30, 20 or 15 years ago. The ROI from that factory would be so strong that you would have to expand more capacity there. And by the way, capacity would also be more scalable.

On reimagining or thinking through the data center stack: is there anything you want to say about that as we close out?

Chaturvedy: We specifically invest in AI for energy and industry, looking across the full stack from data infrastructure to training and inference, through to AI agents solving real-world use cases. We also consider the enabling layers around that stack, like multi-cloud, multi-LLM, cybersecurity, and data governance.

Ultimately, every industry is going to build its own version of this stack, and we believe the most compelling companies will be the ones who drive tangible outcomes in enterprise and industrial environments.

Related 兔子先生传媒 queries:

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While financings of a few million haven鈥檛 gone away, today most venture capital actually goes to rounds of a billion dollars or more. Moreover, it looks like a rising trend.

So far this year, 60% of global startup funding across stages听1 听鈥� around $320 billion 鈥� went to rounds of $1 billion or more, per 兔子先生传媒 data. Such rounds were instrumental in pushing global funding for the first half of the year to record levels.

The U.S. funding tallies are even more tilted to megadeals this year, with 73% of funding going to billion-dollar-plus rounds. Of the $290 billion invested in these deals, just two rounds for AI leaders and account for more than half the total.

As you can see, the notion of billion-dollar-plus rounds accounted for a minority of funding before this year. The lone exception was the first quarter of 2025, when OpenAI closed a $40 billion financing.

Not just bigger deals, more of them too

Giant rounds aren鈥檛 just getting more ginormous. They鈥檙e happening with greater frequency too.

So far this year, U.S. startups have closed 23 known rounds of $1 billion or more, per 兔子先生传媒 data. That puts 2026 already on par with 2025, a record-setting year, and we鈥檝e still got about five months left.

Not surprisingly, these megarounds are generally later-stage rounds or corporate financings. Only two of this year鈥檚 billion-dollar-plus rounds 鈥� and 鈥� were seed or early-stage rounds, per 兔子先生传媒 data.

Lessons from the first crop of billion-plus financings

In the history of startups, meanwhile, the billion-dollar-plus venture funding round is a fairly contemporary phenomenon.

The first American example, per 兔子先生传媒 data, was 鈥檚 $1.2 billion Series D, in 2014. Over the next three years, a handful of others pulled in 10-figure rounds as well, including , , , , , , , and .

Most of those companies went on to go public and reach valuations that well-exceeded levels set for prior megarounds. SpaceX ($1.6 trillion recent market cap), Uber ($148 billion) and Airbnb ($87 billion) were the standout success stories.

Two of the megafund recipients 鈥� Argo AI and WeWork 鈥� did not fare so well, while a third, cancer diagnostics provider Grail, has been up and down. Fanatics, meanwhile, remained private and is still thriving.

If these early billion-plus fundings taught investors anything, it was that pouring unusually large sums into well-regarded unicorns can be quite lucrative but is far from a sure bet.

Uncharted territory

In the current funding cycle, it鈥檚 not enough to ask whether billion-dollar rounds have potential for high returns. With Anthropic and OpenAI, the question now applies to rounds in the tens of billions or even over $100 billion. As both have already filed confidentially to go public, it may not take us long to find out.

Related 兔子先生传媒 query:

Related reading:

• 兔子先生传媒 Data: Global Startup Investment Hit Record $510B In H1 2026 As AI Boom Accelerates Funding And Exits
• 兔子先生传媒 Data: Q2 Brought The Most Billion-Dollar Startup Exits Since 2021
• The $100M+ Round Is Now Just Your Typical Late-Stage Financing

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Ten of those companies were AI labs, collectively valued at $65 billion. The most well-known was Beijing-based open source model developer 鈥� at $50 billion, the highest valued new unicorn to join the 兔子先生传媒 this year.

The new unicorn frontier labs are focused on new architectures in AI model development in robotics, physics and self-learning, as well as on open source development, and in the case of one India-based startup, sovereign AI.

Other leading sectors with multiple companies were in robotics and AI infrastructure, with four companies in each.

Of the new unicorns, 16 are U.S-based, while eight are from China. Two new unicorns joined the board from India, Germany and the United Kingdom and one each from Netherlands, Belgium, Canada and Saudi Arabia.

Big exits remove a trillion

Despite the influx of newcomers, the total value of The 兔子先生传媒 兔子先生传媒 dropped by more than $1 trillion in June as , its most valuable company, went public.

Other notable exits from the board last month were , the maker of AI coding tool Cursor, which was acquired by SpaceX for $60 billion after last being valued at $29.3 billion. , an AI infrastructure company that operates as a layer on top of GPUs, was acquired by , and customer experience agent was purchased by 1, both for well above their last private valuations.

New unicorns in June

Here are June’s new unicorn companies:

AI labs

• Hangzhou-based raised a $7.4 billion Series A, its first external financing, in a deal led by CEO . The 2-year-old company was valued at $50 billion and is said to be planning to list in as early as Q2 2027.
• is building a new AI architecture based on neuroscience called Cortex AI that promises lower power use. It raised a $500 million Series A from , , and . The less than 1-year-old New York-based company was valued at $2.5 billion.
• London-based , an AI for physical product design in aerospace, defense, energy, automotive and semiconductors, raised a $300 million Series C led by . The 6-year-old company was valued at $2.4 billion.
• , a model developer for robotics trained on gaming videos from its sister company , raised a $320 million Series A led by . The 1-year-old New York-based company was valued at $2.3 billion.
• , an embodied robotics intelligence company, raised a $400 million Series B led by . The 2-year-old San Mateo, California-based company with researchers from and was valued at $2 billion.
• Shanghai-based , a听 robotics intelligence company, raised a $220 million seed round led by and . The less than 1-year-old company founded by an researcher was valued at $2 billion.
• , a builder of world models to simulate the real world impacting robotics, science, healthcare and defense, raised a $310 million Series B led by . The 2-year-old Menlo Park, California-based company was valued at $1.5 billion.
• Bengaluru-based , an Indian sovereign AI developer, raised a $234 million Series B first close led by . The 3-year-old company was valued at $1.5 billion.
• , an AI lab seeking to automate AI research for scientific use cases, raised a $200 million seed funding led by and . The less than 1-year-old San Francisco-based company was valued at $1 billion.
• Hangzhou-based , a 3D model developer used in gaming, entertainment and product design, raised a $200 million Series A led by . The 3-year-old company was valued at $1 billion.

Robotics

• Germany-based , a physical AI company building intelligent machines to to work alongside humans, raised a $1.4 billion Series C led by stablecoin issuer among other strategic and growth investors. The 7-year-old company, with $1 billion in its order pipeline and strategic deployments, was said to be valued at $7 billion.
• Shenzhen-based , a builder of humanoid robots, raised a $148 million Series B led by . The 3-year-old company was valued at $1.5 billion.
• Guangdong-based , a humanoid robotics company, raised a $147 million Series B. The 5-year-old company, which projects 1,000 shipments in 2026, was valued at $1.5 billion.
• , a builder of industrial arm robotics for manufacturing that said its technology learns through demonstration, raised a $200 million Series C led by and . The 9-year-old New York-based company was valued at $1 billion.

AI infrastructure

• , which pivoted from crypto mining to data center build out for AI, raised a $400 million funding led by , and . The 2-year-old Coral Gables, Florida-based company was valued at $2.4 billion. The company has filed for a direct listing on .
• Las Vegas-based , a cloud operator that offers customer AMD chips, raised a $350 million Series B led by and . The 2-year-old company was valued at $1.6 billion.
• Beijing-based , an inference solution offering customers API access to hundreds of models, raised a $296 million Series B. The 2-year-old company was valued at $1.2 billion.
• , an AI developer cloud to train, fine-tune and deploy AI, raised a $100 million Series A led by . The 4-year-old New Jersey-based company valued at $1 billion has 1 million developers using the platform.

Defense

• , a precision weapons company enabling existing weaponry to defend against unmanned drones, raised a $200 million Series B led by . The 4-year-old Austin-based company was valued at $2.2 billion.
• , a manufacturer of unmanned aerospace and defense systems, raised a $300 million Series C led by and . The 3-year-old Huntington Beach, California-based company was valued at $1.8 billion.
• , a cyber intelligence company building products for the U.S. military, raised a $100 million Series B led by , and . The 1-year-old Arlington, Virginia-based company was valued at $1 billion.

Proptech

• Montreal-based , a mortgage financing platform, raised a $217 million Series E round. The 8-year-old company was valued at $1.1 billion.
• India-based ,听 a property brokerage that also owns a mortgage marketplace, a property management platform, and a home interior brand raised a $95 million private equity and debt financing led by . The 13-year-old company was valued at $1 billion.

Data analytics

• Belgium-based , an intelligence platform for global physical trade, raised a $1 billion secondary market funding led by . The 12-year-old company was valued at $3.7 billion.

Biotechnology

• , a biotech company focused on reverse cellular aging, raised a $435 million Series C led by . The 4-year-old San Francisco-based company with plans for clinical trials next year for human liver cells, was valued at $3.1 billion.

Materials

• Cambridge, U.K.-based听 , building a network of labs using AI for new material discovery, raised a $450 million funding led by and . The 2-year-old company was valued at $2.6 billion.

Cryptocurrency

• , a blockchain and smart contract solution for global financial institutions, raised a $355 million Series F led by . The 12-year-old New York-based company was valued at $2 billion.

Image generation

• Beijing-based , a video generation company, raised a $300 million Series B led by , and . The 3-year-old company was valued at $2 billion and says it has built a creator community of more than 30 million users. As of May 2026 the company has $300 million in annual recurring revenue.

Financial services

• Saudi Arabia-based , a mobile banking company, raised a $400 million Series A. The 6-year-old company was valued at $1.6 billion.

Semiconductor

• Rotterdam-based , a 3D metrology inspection tool for semiconductor manufacturing, raised a $380 million Series D led by . The 10-year-old company was valued at $1.6 billion.

Aerospace

• Beijing-based , a space infrastructure and satellite company, raised a $207 million Series D. The 10-year-old company was valued at $1.5 billion.

E-commerce

• , an e-commerce provider that supports customer interactions post purchase, raised an $81 million Series B led by . The 4-year-old Utah-based company supporting 4,100 brands and 1,750 merchants was valued at $1.3 billion.

AI healthcare

• , an AI agent built for a patient’s healthcare journey and used by healthcare providers, raised a $120 million Series C led by . The 3-year-old San Francisco-based company was valued at $1.2 billion.

Transportation

• Munich-based , a car subscription platform operating in Germany and partnering with 25 brands, raised a $113 million Series D led by . The 7-year-old company was valued at $1.1 billion.

Related 兔子先生传媒 unicorn lists:

• (1,822)
• (637)
• (213)
• (190)
• (118)
• (102)
• (935)
• (539)
• (248)
• (39)
• (488)

Related reading:

• 兔子先生传媒 Data: Global Startup Investment Hit Record $510B In H1 2026 As AI Boom Accelerates Funding And Exits
• AI Services And Robotics Lead Diverse Crop Of 29 New May Unicorns As SpaceX, Anthropic And OpenAI Line Up Blockbuster Exits

Methodology

The 兔子先生传媒 兔子先生传媒 is a curated list that includes private unicorn companies with post-money valuations of $1 billion or more and is based on 兔子先生传媒 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. 兔子先生传媒 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 兔子先生传媒 long after the event was announced, foreign currency transactions are converted at the historic spot price.

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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.

It was not a holiday week on the funding front, as a raft of largely AI-focused companies closed big rounds. The largest of these was a $1.5 billion financing to enterprise AI startup and a Series D for meal and delivery provider . The week also included some big financings for enterprise tech, food delivery, drones and construction automation.

1. , $1.5B, enterprise AI tools: Fireworks AI, a developer of tools for enterprises to turn 鈥済eneral-purpose models into specialized intelligence trained on their own data,鈥� raised $1.505 billion in Series D funding. , and led the financing, which set a $17.5 billion valuation for the San Mateo, California-based company.

2. , $650M, meals and delivery: Wonder, an operator of kitchens and meal delivery services, closed on $650 million in Series D funding at a $9 billion pre-money valuation. Capital will go in part toward expanding operations for the New York-based company, which currently has 140 locations.

3. , $400M, life sciences AI: AI drug discovery startup Chai Discovery secured $400 million in Series C funding at a $3.8 billion valuation. led the financing, investing alongside , , and others.

4. , $300M, robots: Cambridge, Massachusetts-based Walden Robotics, a startup building general-purpose robots for work in manufacturing and logistics, launched out of stealth with $300 million in funding. and led the round, which values the company at $1.1 billion.

5. , $125M, drones: Seattle-based Brinc, a developer of drones for use in public safety and emergency operations, raised $125 million in fresh funding. led the financing, with participation from , and founder and CEO .

6. (tied) , $100M, construction automation: Austin-based TerraFirma, a developer of AI-enabled software and autonomous robotics technology for the construction industry, landed $100 million in new funding, bringing total investment to date to $115 million.

6. (tied) , $100M, enterprise AI: Spectro Cloud, a provider of AI infrastructure management software, said it raised more than $100 million in a Series D round led by . The financing brings total capital raised by San Jose-based Spectro Cloud to $260 million.

8. , $80M, defense tech: Singularity, a startup focused on developing air defense technology, emerged from stealth with $80 million in Series A funding. and 1听led the financing, which set a $400 million valuation for the Los Angeles-based company.

9. (tied) , $70M, fintech: San-Francisco-based fintech startup Flex, a private banking platform for high-net-worth business owners, raised $70 million in a Series B1 financing led by . The round follows the company’s $60 million Series B in December.

9. (tied) , $70M, AI and policy: State Affairs, an AI platform for policy and regulation, secured $70 million in Series A funding led by Khosla Ventures and .

Methodology

We tracked the largest announced rounds in the 兔子先生传媒 database that were raised by U.S.-based companies for the period of July 11-17. 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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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.

U.S. startups announced sizable funding rounds at a steady clip during a truncated holiday week, with energy and AI leading the way.

Houston-based energy startup secured the biggest round, a $1.75 billion strategic financing, followed by , a developer of infrastructure for companies running open source AI models, and , a provider of compliance tools for enterprises.

Other big rounds were for companies focused on therapeutics, homebuilding, and even lacrosse.

1. , $1.75B, energy: Houston-based Joulent, a provider of energy infrastructure focused on the demands of artificial intelligence and other compute-intensive industries, raised $1.75 billion in a strategic investment backed by through its arm.

2. , $800M, AI infrastructure: Together AI, developer of an infrastructure layer for companies running open source AI models, secured $800 million in Series C financing. led the round, which set an $8.3 billion post-money valuation for the San Francisco-based startup.

3. , $180M, compliance: LeapXpert, a provider of tools for tracking enterprise communications for compliance needs, closed on $180 million in growth financing. led the financing for the New York-based company.

4. , $135M, AI software development: Redwood City, California-based 8090 Solutions, developer of a platform for building enterprise software with coordinated AI agents under human-led oversight,听 picked up $135 million in a round led by 1. The company, founded in 2024, counts prominent startup investor as co-founder and CEO.

5. , $126M, biotech: Boston-based Beeline Medicines, a startup focused on precision therapies for autoimmune and inflammatory diseases, secured $126 million in Series A extension funding backed by , and . The financing follows a previously disclosed $300 million Series A.

6. (tied) , $100 million, professional sports: The Premier Lacrosse League, a men’s professional lacrosse league in North America, closed a $100 million Series E financing round led by and . New York-based PLL said the deal represents the largest capital raise in the history of professional lacrosse.

6. (tied) , $100M, video-based AI: Twelve Labs, a San Francisco-based startup developing AI systems trained on video archives, raised $100 million in a Series B round co-led by and .

8. , $95M, AI for homebuilding: Higharc, a developer of AI-enabled tools for designing homes and managing workflows around homebuilding, picked up $95 million in Series C funding. led the financing for the Durham, North Carolina-based company.

9. , $85M, biotech: Cambridge, Massachusetts-based Flare Therapeutics, a startup targeting transcription factors to develop treatments for cancer and other ailments, raised $85 million in Series C funding led by and .

10. , $65M, AI privacy: Venice, developer of a platform enabling private, surveillance-free access to a wide array of AI models, secured $65 million in Series A funding led by . The round set a $1 billion valuation for the 2-year-old Sheridan, Wyoming-based startup.

Methodology

We tracked the largest announced rounds in the 兔子先生传媒 database that were raised by U.S.-based companies for the period of June 27-July 2. 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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Existing backer (KIP) led the financing, which is described as a bridge round. (KBIC) also participated. The raise brings Santa Fe Springs, California-based Xpanner鈥檚 total funding to $38 million since its 2020 inception.

Xpanner turns construction equipment that customers already own into automated assets 鈥渨ithout replacing a single machine,鈥� according to , the company鈥檚 co-founder and CEO.听

鈥淭here鈥檚 no upfront investment, no rip-and-replace,鈥� Lee added. 鈥淟ike a smartphone gaining new capabilities through app updates, customers expand their automation through simple software updates.鈥�

The benefits for its customers include significant cost savings and shorter project durations, according to Lee.

Originally founded in South Korea, Xpanner moved its headquarters to the U.S. in 2023. Today, , , and are among its customers.听

Notably, all of Xpanner鈥檚 co-founders have deep industry experience. Lee spent two decades in executive positions at and , driving unmanned construction projects and corporate venture initiatives in the heavy equipment world. CFO spent over 12 years working in heavy equipment at Bobcat, followed by eight years in venture capital at Korea鈥檚 largest commercial bank. CTO led robotics and automation at for 20 years, becoming the first in the industry to commercialize semi-automation features for construction machinery.

Growth and a path to profitability

Xpanner is refreshingly transparent about its financials. The company grew revenue from $3 million in 2023 to $7 million in 2024 to $21 million in 2025, according to Park. It saw $8 million in revenue and $1 million in EBIT (earnings before interest and taxes) in the first quarter of 2026.

The startup is targeting $60 million in ARR by year鈥檚 end.

Impressively, the company says it maintains a gross margin above 80%, thanks mostly to its subscription-based AaaS model. It achieved monthly break-even in 2025, and Park said Xpanner is on track for full-year profitability this year.

鈥淥nce hardware is deployed, incremental subscription and service revenue flows at near-zero marginal cost,鈥� he said.听

The company plans to use its new capital in part to strengthen its development capabilities by advancing its next-generation physical AI hardware and software platform, deepening its core component engineering, and expanding its data and AI infrastructure.听

Some of its customers are still on a perpetual modular model, which includes the one-time purchase of its X1 Kit hardware paired with its software. Looking ahead, Xpanner expects to be fully on its subscription model by the end of the year.听

The company is also actively expanding into adjacent verticals, including battery energy storage systems (BESS) and AI data center construction.

鈥楽trong gross margins, near-zero churn鈥�

, managing director at KIP, told 兔子先生传媒 News via email that his firm was impressed by Xpanner鈥檚 commercial traction and unit economics.

鈥淪trong gross margins, near-zero churn, and rapid account expansion are signals that the value proposition is real and not pilot-driven,鈥� he said.

director at KBIC, believes that most construction automation companies hit a scalability wall because they automate entire machines end-to-end. However, he said that since Xpanner’s task-specific approach scales through software rather than hardware redesign, the company 鈥渃an expand wallet share inside accounts without proportional cost.鈥�

鈥淭hat’s a software-economics business operating in a hardware-dominated market, and it’s rare,鈥� he wrote via e-mail.

Physical AI funding smashes records

Xpanner sits at the intersection of two sectors that have received strong interest from investors in recent years.

Startups working on physical AI 鈥� real-world applications of artificial intelligence, including technologies such as automated hardware and robotics 鈥� have already hauled in more than $37 billion in venture funding globally this year, , shattering the full-year record of $21 billion set in both 2025 and 2021.

At the same time, venture investment in real estate and property-related startups rebounded last year, largely driven by funding to AI-centric companies.

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U.S. and Canadian companies secured a staggering $252.6 billion in seed- through growth-stage funding rounds per 兔子先生传媒 data. That鈥檚 more than 3x the total raised in the prior quarter, and the largest quarterly total of all time.

Predictably, artificial intelligence was the driver. More than 87% of Q1 investment went to companies in 兔子先生传媒 AI-related categories.

To say these are record funding tallies is somewhat of an understatement. It鈥檚 more like Q1 smashed the prior quarterly record 鈥� $95.7 billion 鈥� set in Q3 2021.

Just a single financing for was bigger than the prior quarterly record for all startup funding rounds put together. And the four next-largest financings totaled almost as much as the prior quarter, which at the time we considered a very strong period for startup funding.

So, in summary, it was a lot of money. For a more detailed picture, we drill down more deeply into how that largesse was distributed across stages and sectors. We also take a look at exits for the quarter, including both IPOs and acquisitions.

Table of contents

• AI
• Later stage and technology growth
• Early stage
• Seed
• Exits
• Big picture: A paradigm shift
• Methodology
• Glossary of funding terms

AI

We鈥檒l start with AI, since that鈥檚 where the overwhelming majority of the money went.

A staggering $221 billion went to North American companies in 兔子先生传媒 AI-related categories in the first quarter. That鈥檚 about 6x the AI investment total from the prior quarter, which was itself no slacker on this front.

For perspective, we charted out AI-related funding over the past 13 quarters to compare.

A few megarounds for high-profile companies accounted for most of the quarter鈥檚 AI funding, led by OpenAI, , and .

Later stage and technology growth

These same names factor heavily in tallies for late-stage and technology-growth funding, which comprised the vast majority of total startup investment.

Per 兔子先生传媒 data, $222.4 billion 鈥� or 88% of all North America startup investment 鈥� went to rounds at these stages. That鈥檚 more than 5x the prior quarter鈥檚 tally, and more than triple year-ago levels.

The gains were driven by bigger deals, not more of them. Later- and growth-stage round counts were actually down a smidge sequentially in Q1. For perspective, below we chart round counts and investment totals at this stage for the past five quarters.

Enormous rounds for AI companies accounted for a majority of the late- and growth-stage totals. The biggest of these was OpenAI鈥檚 record-setting $110 billion February financing led by , and . The generative AI giant topped it off with a raise in March.

Anthropic secured the quarter鈥檚 next-biggest late-stage financing 鈥� a $30 billion February Series G 鈥� followed by xAI, which announced a $20 billion Series E in January. landed another of the quarter鈥檚 very big deals, with a $16 billion February Series D.

Early stage

Early-stage investment was also running high in Q1, albeit not setting records.

Overall, investors put $25.1 billion into deals around Series A and Series B stage in the first quarter. That鈥檚 up 17% from the prior quarter and 56% from year-ago levels. It鈥檚 also the highest quarterly total in over three years, though still below peaks scaled in 2021.

Early-stage round counts, meanwhile, were down a bit, indicating investors鈥� increasingly concentrating their bets among perceived star performers.

As usual, a few jumbo-sized deals significantly boosted the early-stage totals. For Q1, this included four rounds of $500 million or more.

Of these, Austin-based humanoid robotics startup was the biggest fundraiser, pulling in $520 million in a February Series A. Three other companies secured $500 million financings: AI infrastructure developer , semiconductor startup , and industrial robotics-focused .

Seed

Seed-stage investment, meanwhile, did not show an upswing but remained at historically robust levels.

Per 兔子先生传媒 data, an estimated $5.1 billion went to seed and pre-seed investments in Q1. That鈥檚 roughly flat with the prior quarter and up a bit from year-ago levels.

Seed round counts declined in Q1, both sequentially and year over year. However, we expect these tallies to rise some over time, along with investment totals, as seed deals commonly get added to the data set weeks after they close.

Exits

Exit activity was fairly staid in comparison to the high-rolling startup fundraising environment.

That said, the IPO market did boast a few sizable startup debuts. Of these, the largest was the January IPO of construction equipment rental marketplace , followed by space tech company , and crypto platform .

Below, we aggregated a list of 12 private, venture-backed companies that carried out IPOs on U.S. exchanges.

Acquirers also announced several large deals to purchase venture-backed private companies.

The priciest planned M&A deal was 鈥檚 agreement to purchase business credit card provider for $5.15 billion. Biotech also delivered some large outcomes, including 鈥檚 planned acquisition of RNA therapeutics startup , and 鈥� purchase of allergy treatment startup .

Below, we put together a list of five of the quarter鈥檚 biggest M&A deals.1

Big picture: A paradigm shift

Having written many of these funding reports over the years, it鈥檚 common for one quarter to quietly blur into another. Not so for Q1 of 2026.

The just-ended quarter cemented a notion that startup insiders have been circling for some time: Private markets now have the capital stores and appetite for ultra-high valuations to rival public markets. For evidence, look no further than OpenAI鈥檚 $122 billion raise at a valuation higher than all but a handful of the largest large-cap technology companies.

IPO enthusiasts may pine for a future period when these most sought-after foundational AI names finally do make it to public markets. But for now, they鈥檝e demonstrated there are plenty of investors willing to shell out billions in private offerings as well.

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Methodology

The data contained in this report comes directly from 兔子先生传媒, and is based on reported data. Data is as of March 31, 2026.

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

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

Glossary of funding terms

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

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

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

Technology growth is a private-equity round raised by a company that has previously raised a 鈥渧enture鈥� round. (So basically, any round from the previously defined stages.)

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led the financing for the New York-based company. , , and also participated in the round.

Founded in October 2024, Rebar says it uses artificial intelligence to help commercial HVAC suppliers generate quotes on average 60% to 70% faster than traditional methods. Its proprietary computer vision models analyze construction blueprints and identify, categorize and count all HVAC equipment to produce a bill of materials and generate a quote, according to the company.

Rebar鈥檚 focus on the HVAC industry is intentional.

鈥淢ost companies either concentrate on other trades or try to cover all of them at once, which ultimately means they serve none particularly well,鈥� CEO and co-founder told 兔子先生传媒 News. 鈥淩ebar takes the opposite approach. Our AI is trained on millions of HVAC blueprints and mirrors the workflows real estimators use when building a quote.鈥�

Rebar doubled its annual recurring revenue in the first six weeks of 2026, according to Brown, thanks to dozens of new customers using the platform. It operates on a usage-based subscription model.

鈥淚f you’re able to increase your volume and build more proposals, the opportunity to win projects goes higher,鈥� Brown explained. 鈥淥n average, the companies that are using us [would] win around 5% to 10% of the proposals that they created, and those proposals could take up to a week to create before using Rebar.”

He noted that, while it’s still early and construction contracts often take years to finalize, initial conversations with customers suggest win rates may be increasing by roughly 2x to 3x using the new tool.

That same process can take minutes, according to Brown.

Today, Rebar has 40 clients, and notably, seven of them are investors in the startup.

While Rebar鈥檚 first product is AI quoting for HVAC suppliers, Brown said the startup plans to expand its product capabilities to plumbing and electrical equipment suppliers through additional agents.

Firsthand industry perspective

Brown鈥檚 interest in the HVAC industry stems from summers working with his uncle, the owner of a large HVAC commercial distributor. He then ended up working as an estimator and sales engineer at /, where he partnered with contractors, engineers and manufacturers to design, sell and support customized HVAC systems.

鈥淚 spent over five years in the space focused on designing and selling HVAC equipment and doing the manual process that we’re solving at Rebar many times,鈥� he recalled. 鈥淚’ve looked and built inventory lists off of a plan set by printing out blueprints, highlighters and rulers. I’ve used PDF editors. I’ve really used everything, and I never thought I would end up in tech, nor start a tech company.鈥�

When that company was acquired and became part of , Brown had the opportunity to explore the application of AI in day-to-day operations.

Eventually, he decided to branch out and founded Rebar along with .

What investors are looking for

, a partner on Prudence鈥檚 investment team, told 兔子先生传媒 News that Brown鈥檚 education in mechanical engineering combined with his experience working in the HVAC industry give him a 鈥渦nique,鈥� firsthand perspective.

Prudence is always looking for companies that leverage unique technology to automate historically manual processes, according to Viniar, often in industries where needs have never been addressed by purpose-built software.

鈥淩ebar fits the bill perfectly 鈥� HVAC, plumbing, and electrical are large but historically overlooked industries with dozens of manual workflows, none of which could be automated without AI,鈥� he wrote via email. 鈥淔or the first time, Rebar is delivering tools to their customers that, in many cases, are compressing the time to complete manual tasks by over 90%, leading to greater efficiency, lower costs, and more revenue.鈥�

Venture investment in real estate-related startups has rebounded in recent years after plunging from the pandemic peak. In 2025, startups in the sector pulled in approximately $10.5 billion in seed- through growth-stage financing globally, per 兔子先生传媒 . That鈥檚 up about 17% from $9 billion in 2024, with much of the recent investment going to startups that promise greater ROI through the use of automation or AI.

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• Sector Snapshot: Real Estate Tech Funding Sees Slight Rebound, But Still Far Lower Than Peak Years

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Nonetheless, the first couple months of the year have brought a steady stream of market entries from companies in sectors such as construction tech, space tech and biotech. Noticeably absent, however, are new offerings from SaaS companies, long an IPO market staple.

Per 兔子先生传媒 data, 11 venture- or seed-backed U.S. companies went public on major exchanges so far this year, raising just over $3 billion. Comparatively, that鈥檚 a fairly robust showing for the first couple months of the year, which tends to be a reasonably active period for IPOs.

Looking at recent years charted below, the first couple months of 2026 are well above the bottom ranks, but still far below the 2021 market peak for volume of offerings and total raised.

Leading offerings weren鈥檛 your typical VC-backed deals

The lineup of companies going public so far this year, however, includes many that don鈥檛 look like your typical VC-backed offering.

This includes the year鈥檚 largest VC-funded IPO: , a service that provides construction equipment rentals and support for building projects. The 11-year-old, Columbia, Missouri-based company raised more than $700 million in its January offering and had a recent market cap of over $7 billion.

The second-largest debut was also somewhat of an outlier: space tech company , which is majority-owned by private equity firm . It鈥檚 down from its initial trading price but recently valued around $3.4 billion.

Per 兔子先生传媒 data, there have been six IPOs of venture-backed companies this year that raised $200 million or more, which we list below.

SaaS squashed

It鈥檚 also noteworthy who isn鈥檛 on the list. For years, enterprise software companies have been among the more reliable IPO market entrants. This year, however, they鈥檝e been notably absent as the sector contends with an extended selloff fueled partly by concerns of AI-abetted disruption.

We鈥檙e also not seeing SaaS companies in the immediate IPO pipeline. A perusal of so far this year showed no venture-backed SaaS unicorns that submitted a new IPO filing in 2026.

It鈥檚 a sharp contrast to just a few months ago. One of last year鈥檚 splashiest IPOs 鈥� design software platform 鈥� is now down more than two-thirds from its peak. Another of the more recent big SaaS offerings 鈥� business travel and expense platform 鈥� has shed more than half its value.

Meanwhile, -backed , which provides tools for marketers and app developers, withdrew its planned IPO this month, amid the software route. It鈥檚 likely a delay, as that Liftoff filed a new confidential plan shortly afterward.

IPO market in an odd place

Overall, the IPO market is in an odd place at the moment. It鈥檚 an unfriendly scene for companies with business models viewed as vulnerable to AI-driven displacement. At the same time, there鈥檚 still continued buzz around the potential for record-setting offerings from , and .

Of those, the one rumored to be closest on the horizon is SpaceX, newly combined with at a reported $1.25 trillion valuation. The company is said to be eyeing a market debut as early as this summer.

If that happens, and the current SaaS squeeze continues, it wouldn鈥檛 be surprising to see a pattern of record-setting IPO returns coinciding with a very small number of actual debuts.

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• 兔子先生传媒 Predicts: IPOs Picked Up In 2025 And The Outlook For 2026 Is Even More Optimistic
• 兔子先生传媒 Predicts: 15 Companies That Could Go Public In 2026 As The IPO Market Gains Momentum
• SpaceX IPO At $1.5T Valuation Would Be 10x Larger Than Biggest VC-Backed Listing Of All Time
• Yes, I鈥檓 Biased. But Still, Leading Unicorns Like Anthropic Should Be Prepping For IPOs

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