From putting nuclear reactors on barges to grading how well AI models can control robots, this month鈥檚 crop of interesting startup deals takes AI and other emerging technologies well beyond the conventional software stack.

Other companies that caught our eye are applying automation to the decidedly old-school worlds of building-material procurement, commercial property maintenance and farm recordkeeping. Let鈥檚 take a closer look.

$50M to put nuclear power at sea

Nuclear power plants are famously difficult and time-consuming to build. thinks putting them on barges could offer another way.

The Long Beach, California-based startup raised what it says was an oversubscribed $50 million seed round led by , just two months after emerging from stealth with $10 million in pre-seed funding. The of investors in the deal included , , , and others.

Bluecore is developing compact, water-cooled small modular reactors designed to operate aboard floating barges. Rather than spending years constructing a new power plant and the accompanying infrastructure on land, the idea is to manufacture the systems and move them to where electricity is needed.

鈥淥ur focus is simple. Create and deliver zero-emission energy as safely and quickly as possible,鈥� CEO and founder wrote in a social media . 鈥淥ver 3 billion people live within an hour of water. We want to power them all.鈥�

Its first target is the Port of Long Beach, with other ports and power-hungry AI data centers among the potential customers. The company says it鈥檚 working with the and as it pursues certification.

Bluecore鈥檚 raise comes amid a broader nuclear funding boom. Nuclear fission startups alone pulled in roughly $2 billion in venture funding in 2025, per SA国际传媒 data, and investors have continued writing enormous checks this year. More broadly, cleantech-, EV- and sustainability-focused startups raised about $15 billion in the first half of 2026, with second-quarter funding reaching its highest quarterly level since 2024.

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$31M to bring AI to the building-materials business

Ordering cement and steel might not sound like an obvious AI use case, but Saudi Arabia-based sees a lot of room for improvement.

The Riyadh startup last week said it had secured $31 million in new capital, consisting of a $13 million Series B equity round co-led by , 鈥檚 venture arm, and , plus an $18 million growth-debt commitment from under a previously announced facility. The company has now raised more than $83 million, .

BRKZ operates a marketplace that connects construction companies with suppliers of building materials, while also handling sourcing, logistics and financing. More interestingly, it says it has amassed some 38 million structured data points that power an AI pricing engine trained on roughly 40,000 requests for quotes.

The company says 84% to 89% of its predicted prices come within 5% of the eventual transaction price. Another AI agent reads photos of cement delivery notes sent through , matches them to orders and verifies deliveries 鈥� with roughly three-quarters processed without human intervention.

BRKZ is riding a in Saudi Arabia even as startup investors remain selective about construction and property technology more broadly. Global proptech startups raised about $6.5 billion via roughly 640 deals in the first half 2026, SA国际传媒 data shows. That’s on pace to top last year鈥檚 dollar figures, even as deal count has dipped this year. Similar to other startup sectors, investors in proptech are increasingly directing capital toward companies using AI and automation to cut costs and streamline operations.

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$24M for robots to take care of commercial properties

Robots are already assembling cars and moving packages around warehouses. wants them to also mow lawns and sweep parking lots 鈥斕齛nd do security patrols of those properties while they鈥檙e at it.

The Santa Clara, California-based autonomous robotics startup last week said it has raised a $24 million Series A led by to scale its fleet of robots designed to handle outdoor property maintenance for commercial real estate owners and operators.

Its machines combine autonomous navigation with attachments that allow them to perform jobs like sweeping, debris removal and landscaping tasks 鈥� all while conducting 鈥渟oft security鈥� 鈥� across large campuses and commercial properties.

Rather than trying to build a general-purpose humanoid robot, Viabot is applying autonomy to repetitive jobs that property owners already pay people and contractors to perform. The startup, which operates on a 鈥渞obot as a service model,鈥� sees an opportunity to fill a labor shortage for what鈥檚 often considered 鈥渄irty, dull and dangerous鈥� outdoor work, , founding partner at , told SA国际传媒 News in 2021, when the company raised earlier funding.

Startup investors are pouring money into those sorts of real-world AI applications. Global venture funding to physical AI companies 鈥� including robotics, autonomous vehicles, aerospace, drones, industrial automation and sensors 鈥� reached $47.4 billion across 521 deals in the first half of 2026, SA国际传媒 data shows. That’s nearly 4x the $12 billion invested in the second half of 2025 and almost 80% above the year-ago period.

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$10M to give AI robots an independent report card

As frontier AI models move from controlling software to controlling robots and machines in the real world, wants the public to have an independent way to understand what they can actually do.

The 3-month-old San Francisco startup announced last week that it raised a $10 million seed round led by , with participation from , , and others.

Robocurve says it wants to act as an independent third-party auditor for physical AI, testing how well frontier models can control real robots and publicly reporting the results. The company says its own research has already found that general-purpose large language models can outperform specialized robotics vision-language-action models on some simple tasks.

Importantly, Robocurve isn’t positioning itself as a conventional robotics benchmarking startup. It is incorporated as a Public Benefit Corporation with a legal duty to independently evaluate the robotics capabilities of frontier AI systems and report those findings to the public.

The company says AI labs don’t dictate its research agenda, evaluation methodology or published results, and it plans to work with governments, policymakers and civil society as robot capabilities advance.

Academia is a big part of that model, too. Rather than developing every benchmark itself, Robocurve funds academic teams and supplies them with robot hardware to create open-source benchmarks. More than 200 institutions 鈥� including researchers from 19 of the world’s top 20 universities, according to the company 鈥� have signed up for its benchmarking program. Robocurve is offering a combined $500,000 in funding plus free robotic arms to participating academic groups.

Its funding is timely given the massive influx of capital pouring into robotics and physical AI. Within the broader physical AI sector, robotics startups alone raised more than $21 billion globally in the first half of 2026, SA国际传媒 data shows, already eclipsing the nearly $16 billion raised in all of 2025 and even the $15.3 billion invested during the venture market’s 2021 peak.

As ever more powerful models move from screens into machines capable of manipulating the physical world, figuring out what those models can 鈥� and can’t 鈥� safely do becomes a more consequential problem.

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$5M to let farmers talk instead of type

A lot of agricultural software has one basic problem: Farmers don鈥檛 spend their days sitting at desks.

With that in mind, this month raised a $5 million pre-seed round led by for a voice-first AI platform designed specifically for farmers, agronomists and other agricultural workers.

Instead of asking someone working in a vineyard or almond orchard to stop and fill out a form or type notes into a computer, Tellia enables them to leave a voice note, send a message, or even submit a photo to log records, generate reports and set reminders. It says its AI then turns that unstructured information into records associated with the correct field, crop and crew.

For example, for a livestock farmer that might mean a voice prompt like: 鈥淭ellia, the vet just checked Herd 3. All clear, next health check due in 6 weeks, log that.鈥�

Or a vineyard manager might ask: 鈥淭ellia, based on this year’s Brix and pH logs, what’s the projected alcohol level for the Cabernet lot?鈥� and receive an instant answer based on previously collected data.

San Francisco- and Paris-based Tellia was founded last year and says its technology is already deployed across 1 million acres, including at and wineries in the U.S., as well as agricultural organizations in Europe.

and also participated in its latest funding.

Its raise comes amid a much tougher environment for agtech startups overall. Venture investment in agriculture and farming remains in a correction from its 2021 peak, when startups in the space raised $10.5 billion across more than 1,400 deals, SA国际传媒 data shows. That makes companies applying increasingly cheap and accessible AI to specific, everyday farming problems an interesting corner to watch. Voice AI, in particular, has emerged as one of the hot spots in artificial intelligence funding in recent years.

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Related reading:

• Sector Snapshot: Robotics Startups On Fire As Venture Funding Surges To Record Numbers In 2026
• VCs Pour Billions Into Physical AI As The Next Wave Of AI Investing Takes Shape
• Sector Snapshot: Agtech Startups Face A Drier Funding Climate
• Why Big Investors Are All Ears For Voice AI Startups

Illustration:

The highest-valued new entrants were China-based humanoid robotics business , valued at more than $6.3 billion; San Jose, California-based photonics company , valued at $5.5 billion; and Palo Alto, California-based AI model platform , and San Francisco鈥檚 semiconductor manufacturing startup , both valued at $5 billion.

AI software featured prominently across model training, assistants, agentic and enterprise workflow automation, coding and voice transcription.

Semiconductors was the second-largest sector, with five new unicorns. Robotics and financial services each added three, while data centers, security and energy each added two.

The U.S. accounted for 16 of August鈥檚 new unicorns. China followed with four. South Korea, India, Singapore, the United Arab Emirates, Switzerland, Germany and Turkey each added one. Nigeria and Indonesia also each added one new unicorn 鈥� for both, their first new unicorn of the year.

Nine companies exited the Unicorn Board in August, per SA国际传媒 data: Three that went public 鈥� the most notable being 鈥� and six via acquisition, including , and .

New unicorns in August

Here are August鈥檚 new unicorn companies:

AI and software

• , a Palo Alto, California-based platform for training, fine-tuning and deploying custom AI models based on proprietary data, announced $1.1 billion in funding led by and . The less-than-1-year-old company, founded by former co-founder , was valued.
• San Francisco-based , an AI assistant that executes personal tasks, raised a $250 million Series B led by and . The 1-year-old company was valued at $2.5 billion.
• Shanghai-based , a builder of agents for digital and physical environments, raised a $220 million seed round led by and . The less-than-1-year-old company was valued at $2 billion. Its founder, , a researcher, left earlier this year.
• San Francisco-based , which builds AI-powered voice-writing and meeting-transcription tools, raised a $280 million Series B led by , who also led its Series A in 2025. The 5-year-old company was valued at $2 billion.
• San Francisco-based , which provides AI-powered code review and change-management tools, raised a $143 million Series C at a $1.5 billion valuation. and co-led the round. The 3-year-old company said it would commit more than $10 million to keep its tools free for open-source projects over the next year.
• San Francisco-based , which deploys AI agents across calls, email, documents and enterprise systems, raised a $150 million Series C at a $1.2 billion post-money valuation. and led the round. The company is 4 years old, started in logistics and has expanded to insurance, energy, telecommunications and airlines among others and counts 150 enterprise customers.
• Turkey-based , a developer of consumer mobile applications, raised a $50 million Series A led by . The 4-year-old company was valued at $1.25 billion. Its apps include AI chatbot Nova, diagnosing plants with PlantApp, and art generator DaVinci.

Semiconductors

• , a San Jose, California-based developer of photonic interconnects for AI computing infrastructure, raised a $700 million Series C at a $5.5 billion valuation. , , , and led the round. The 2-year-old company is already deployed within data centers.
• raised $400 million in funding led by hedge fund . The 1-year-old company was valued at $5 billion. The San Francisco-based company creates tooling for semiconductor manufacturing and was founded by researchers.
• South Korea-based , which develops edge AI processors for on-device inference, raised about $29 million in the first tranche of its Series D funding from existing investors. The 8-year-old company targeting robotics and electronics was valued at about $2.2 billion.
• Shanghai-based , an AI chip startup for inference, raised a Series A led by local state capital investors and . The 4-year-old company was valued at about $1.5 billion with plans to ship its product in Q4 2026.
• Santa Clara, California-based , which develops low-power silicon and software for AI data centers and physical AI, raised a $110 million Series A led by . The 4-year old company was valued at more than $1 billion.

Robotics

• China-based , which is building the general-purpose IRON humanoid robot, raised more than $900 million in its first outside financing at a post-money valuation exceeding $6.3 billion. led the round, with participation from and support from and Alibaba Group. The company, a subsidiary of public smart electric vehicle company , is 10 years old.
• Singapore-based , which develops robots to operate in real-world environments, raised about $669 million in funding. The 2-year-old company was valued at about $3.3 billion and is set to deploy robots in a Dairy Queen in Shanghai to handle the entire 55-step process of taking orders, preparing the food and handing it to a customer.
• Zurich-based , which develops autonomous technology for heavy construction machinery, raised a $200 million Series A led by . The 4-year-old company was valued at $1 billion and works across multiple construction brands.

Financial services

• Bengaluru-based , a financial-services company spanning payment, lending and insurance, raised $100 million in funding led by . The 7-year-old company was valued at $1.3 billion.
• Berlin-based , a finance AI platform for European mid-sized businesses to听 manage spend, card issuing and expenses, raised a $40 million Series C led by and . The 7-year-old company was valued at around $1.15 billion. The company says it has 5,000 businesses that use the service to give finance teams control.
• Palo Alto, California-based , an AI-native enterprise resource planning platform for accounting, raised a $100 million Series C led by . The 4-year-old company was valued at $1 billion.

Aerospace and defense

• Los Angeles-based , a manufacturer of autonomous military drones and counter-drone systems, raised a $250 million Series C at a $2.5 billion post-money valuation. and the co-led the round. The company is 3 years old. Neros has contracts with the U.S. military as well as half a dozen allied countries.
• Mountain View, California-based , which builds and operates satellite constellations for national security, civil and commercial customers, raised a $250 million Series C led by . The 5-year-old company was valued at $1.5 billion.

Data centers

• Palo Alto, California-based , a vertically integrated AI infrastructure platform, raised a $300 million Series A led by , , and . The less-than-1-year-old company was valued at $2.4 billion. Alongside the equity, Volta secured $5 billion in debt to fund data center buildouts.
• , a full-stack AI infrastructure and neocloud platform, received led by Doha-based broadband provider , which holds a 49% stake. Jakarta-based Zankore is less than 1-year-old and is valued at $1.6 billion. The platform is targeting 1 gigawatt of AI computing capacity.

Security

• San Francisco-based , an AI-native security company that provides autonomous penetration testing, raised a $250 million Series E led by and . The 7-year-old company was valued at $2 billion and is used by 7,000 organizations including defense, Fortune 10, banks and healthcare companies among others.
• Palo Alto, California-based , which provides security for AI agents and third-party applications, raised an $85 million Series D led by . The 9-year-old company was valued at $1.1 billion.

Energy

• China-based , a nuclear fusion company developing small modular reactors, raised about $179 million in seed funding. The 1-year-old company was valued at about $1.5 billion.
• Washington, D.C.-based , which develops software that adjusts AI data-center workloads based on power-grid demands, raised a $150 million Series A at a $1 billion valuation. and co-led the round. The 2-year-old company says the round brings total funding to more than $220 million.

Transportation

• Nigeria-based , a vehicle financing and autonomous fleet management infrastructure, raised a $250 million Series C led by , and . The 7-year-old company was valued at $2.1 billion. It operates a fleet of 42,000 vehicles 鈥� both human-driven and autonomous 鈥� across 29 cities, with annual recurring revenue of $420 million.听

Critical minerals

• Houston-based , which builds mines and refineries using its MarianaOS software platform, raised a $310 million Series B led by . The 2-year-old company was valued at $1.5 billion.

Web3

• Dubai-based , an AI-enabled stablecoin neobanking platform for cross-border payments and tokenized assets, raised a $68 million Series C led by Tokyo-based at a $1 billion valuation. The 7-year-old company says it processes more than $40 billion in annualized transaction volume.

Related SA国际传媒 unicorn lists:

• (1,862)
• (658)
• (276)
• (195)
• (119)
• (102)
• (961)
• (547)
• (254)
• (39)
• (489)

Related reading:

• Global Venture Funding Jumps 122% In August As Streak Of Billion-Dollar Deals Continues
• Which Investors Have Backed The Most 2026 Unicorns?
• 40 Companies Joined The Unicorn Board In July, The Highest Count In 4 Years

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.听

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.听

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

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

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.

Illustration:

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

AI infrastructure dominated the largest venture rounds this week, with two multibillion-dollar deals in the sector taking the top spots. Data center and cloud provider led with a massive $3 billion financing, followed by 鈥檚 $1.5 billion raise. Further down the list, AI inference startup landed $300 million, joining a diverse group of big fundings spanning cybersecurity, robotics, food, HR software, payments and healthcare.

1. , $3B, AI infrastructure: Denver-based Crusoe raised a $3 billion Series F co-led by and, with also participating. Originally founded to use stranded natural gas to power cryptocurrency mining, Crusoe has transformed into a major AI cloud and data center provider serving customers including , and . The company has raised nearly $7.2 billion to date, and the latest financing values it at $30 billion 鈥� triple its valuation less than a year ago 鈥� according to SA国际传媒.

2. , $1.5B, AI infrastructure: New York-based Fluidstack raised $1.5 billion in a private equity round led by, bringing the AI infrastructure company鈥檚 total funding to just over $2.6 billion. Fluidstack provides large-scale GPU and data center infrastructure for demanding AI workloads and has emerged as one of a growing group of companies spending heavily to meet soaring compute demand for AI. The financing values the company at $18 billion.

3. (tied) , $300M, AI infrastructure: San Francisco-based Gimlet Labs raised a $300 million Series B led by, with investors including ,, and . Gimlet is building an AI inference cloud that distributes workloads across different types of chips, an approach aimed at making the increasingly compute-intensive process of running AI models faster and more efficient. The company has raised $392 million to date and was valued at $3 billion in the latest round, .

3. (tied) , $300M, cybersecurity: San Francisco-based Upwind Security raised $300 million in new funding co-led by and. Other investors included 1,, and . The company鈥檚 platform uses real-time cloud runtime data to identify threats and vulnerabilities, putting it at the intersection of two particularly well-funded areas: cloud security and AI. Upwind has raised $730 million to date and was valued at $3.8 billion in this latest deal.

5. , $250M, food and nutrition: New York-based high-protein food company David raised a $250 million Series B co-led by and., and company co-founder also participated. Best known for its high-protein, low-calorie bars, David has expanded into other protein-focused foods as consumers continue gravitating toward products marketed around protein and metabolic health. The company has raised $335 million and was valued at $2.25 billion in the latest round.

6. , $166M, HR software: New York-based HiBob raised $166 million in a round led by, with also participating. HiBob鈥檚 Bob platform combines HR, payroll, benefits and employee-management tools, and the company is increasingly positioning its workforce data as a foundation for enterprise AI applications. The latest deal brings its total funding to $740 million and values the company at $3.2 billion.

7. , $165M, robotics and physical AI: Sunnyvale, California-based Lyte AI raised a $165 million Series C led by, with participation from,, and. Founded by former engineers, Lyte develops custom silicon, sensors and AI software that help robots perceive and understand their surroundings, the kind of technology that underpins the fast-growing physical AI sector. Lyte has now raised $272 million to date, , and was valued at $1.6 billion in the Series C.

8. , $155M, fintech and payments: Mountain View, California-based TabaPay secured $155 million in growth financing led by. The company provides money-movement infrastructure that helps banks and fintech companies instantly disburse, collect and transfer funds. The company announced the latest funding as it also of federally chartered , a move that could deepen its role in payments infrastructure. TabaPay鈥檚 new round follows a Series A of an undisclosed amount back in 2022.

9. , $125M, health care and oncology: Nashville, Tennessee-based Thyme Care raised a $125 million Series E led by , the healthcare investment arm of . Other backers included, and, among others. Thyme Care works with health plans, employers and providers to coordinate cancer treatment and manage oncology care, part of a broader shift toward value-based specialty care. The company has now raised $399 million in total and was valued at $2 billion in the latest round.

10. , $100M, AI cybersecurity: Austin-based HiddenLayer raised a $100 million Series B led by.,, and also participated. HiddenLayer builds security tools designed specifically to protect AI models, agents and workflows from attacks and vulnerabilities, a category gaining urgency as enterprises move AI systems into production. The company has raised $156.2 million to date, .

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. 29-Sept. 4, 2026. Although most announced rounds are in the database, there may be a small time lag, as some rounds are reported late in the week.

Related reading:

• Former Apple Engineers鈥� Physical AI Startup Lyte Raises $165M At $1.6B Valuation
• VCs Pour Billions Into Physical AI As The Next Wave Of AI Investing Takes Shape

Illustration:

The financing, led by , brings Lyte鈥檚 total raised to $272 million. , which led Lyte’s Series B, also participated in the Series C, along with , , (formerly Exor Ventures), and additional existing and new investors.

The Sunnyvale, California-based company was founded in 2021 by , and 鈥� a trio of former engineers who worked on the iPhone giant鈥檚 advanced sensing and perception technologies. Shpunt had also previously co-founded , a startup whose 3D-sensing technology powered Microsoft Kinect before Apple acquired the company in 2013.

The trio’s past work helped bring 3D perception to the mainstream and later became a foundation for Apple鈥檚 Face ID technology.

Lyte is building custom silicon, 4D sensing, RGB, motion awareness and AI software to help robots sense where they are and what is moving around them. Initially, its customers are primarily in the warehousing and manufacturing industries.

The startup operated in stealth until earlier this year when it and announced it had raised $107 million in Series A and B funding.

鈥楢 new kind of perception鈥�

鈥淧hysical AI will create entirely new categories of robots, and every one of them will need to understand the world around it,鈥� CEO Shpunt told SA国际传媒 News via email. 鈥淭hat requires a new kind of perception: precise, real-time understanding of geometry and motion that machines can trust enough to act on. We built Lyte to become the perception foundation for that future.鈥�

Funding in the physical AI space has exploded in recent years. In the first half of 2026, global venture funding in the space totaled $47.4 billion across 521 deals, per SA国际传媒 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.

, managing partner at Maverick Silicon, joined Lyte’s board of directors as part of the funding round.

鈥淟yte is building a foundational sensing platform that enables a wide range of robots to perceive and understand the world around them,鈥� he said in a release. 鈥淭he breadth and diversity of early customer demand strengthen our conviction that Lyte is poised to become one of the defining technology companies of the robotics era.鈥�

Related SA国际传媒 query:

Related Reading:

• VCs Pour Billions Into Physical AI As The Next Wave Of AI Investing Takes Shape

Illustration:

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

Most of this week鈥檚 largest funding recipients were AI-focused startups, with , a developer of AI assistants, pulling in the biggest round. Other sizable financings went to companies in areas including business software, physical AI, autonomous transport and even sea gliders. Overall, rounds skewed smaller than in recent past weeks.

1. , $250M, AI assistants: Instinct, a startup developing and beta testing an AI assistant, is raising $250 million in a Series B valuing the San Francisco company at $2.5 billion, according to a from citing founder . Lead backers include and .

2. , $240M, small business AI tools: Owner, a provider of AI tools for local businesses to automate things like building websites, online and phone ordering, mobile apps, and customer support, picked up $240 million in new funding. led the financing, valuing the 8-year-old San Francisco company at $2.3 billion.

3. (tied) , $200M, physical AI: San Francisco-based Generalist AI, a startup developing an AI foundation model that can work with a variety of robots, secured $200 million in fresh financing. The investment, an extension of its $400 million Series B in June, is reportedly led by 1.

3. (tied) , $200M, autonomous trucking: Gatik, an operator of driverless trucks, closed on $200 million in Series D funding. and led the round for the 9-year-old, Santa Clara, California-based company.

5. , $156M, predictive analytics: Socure, a provider of identity, risk and compliance tools, picked up $156 million in growth funding and acquired , an agentic platform for fraud and compliance operations. led the round, valuing the Incline Village, Nevada-based company at $5.2 billion.

6. , $150M, data center energy management: Emerald AI, a software platform that balances AI computational workloads and available energy resources, raised $150 million in Series A funding. The financing, led by and , set the Washington, D.C.-based company鈥檚 valuation at $1.05 billion.

7. (tied) , $120M, sea gliders: Rhode Island-based Regent Craft, a developer of high-speed winged sea vessels, closed on $120 million in Series B equity funding led by and . It also secured $120 million in debt funding from .

7. (tied) , $120M, biopharma: AusperBio, a San Francisco startup developing therapeutics for chronic hepatitis B and other diseases, picked up $120 million in Series C funding backed by new and existing investors. The funding will support clinical trials for its lead therapeutic.

9. , $76M, AI for creatives: Los Angeles-based Stability AI, a developer of AI products for professional creatives across music, gaming and entertainment, announced a Series B fundraise of $76 million backed by a long list of venture and strategic investors.

10. , $75M, coffee: Brooklyn-based coffee and matcha drink chain Blank Street has raised $75 million in fresh funding from investors including as it plans a West Coast expansion. The company also raised $30 million in secondary market transactions.

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. 22-28. Although most announced rounds are in the database, there may be a small time lag, as some rounds are reported late in the week.

Illustration:

has been operating in that market since 2013. The New York-based company operates a marketplace for shares of privately held companies, giving employees and other shareholders a way to sell stock before a company goes public or is acquired.

announced plans to acquire EquityZen in October 2025 and completed the deal in January 2026, bringing the company under the investment bank鈥檚 umbrella.

, who co-founded EquityZen and serves as its chief strategy officer, has had a front-row seat to the secondary market’s evolution. SA国际传媒 News spoke with Haslett about what secondary-market pricing says about today鈥檚 most sought-after startups, why AI companies are commanding premiums while many older startups trade at discounts, what the IPO market looks like beyond its biggest names, and why investors are taking a closer look at hard tech.

The following conversation has been edited for length and clarity.

SA国际传媒 News: The second quarter was one of the strongest venture-backed IPO quarters since 2021, but drove much of that activity. If you remove SpaceX, how open is the IPO market for the typical late-stage startup?

Phil Haslett: Generally, I鈥檇 say it鈥檚 better than it was three or six months ago. If you were a private late-stage technology company, you probably were going to wait until after SpaceX anyway, so that hurdle is gone.

Tech markets are also doing well. The stock market is at an all-time high, and there鈥檚 been a strong recovery in tech stocks overall. I assume that we鈥檙e gearing up for a busier summer than usual.

Another thing to consider is IPO performance beyond SpaceX. Some have had initial enthusiasm followed by a slowdown. has come down a bit. So companies may see it as a good time to go public, while post-IPO performance has been, in a word, 鈥渕eh.鈥�

But within AI, I think we鈥檝e seen that there鈥檚 opportunity up and down the production curve 鈥� from energy for data centers, to the technology inside them, to orchestration of compute, to efficient spending on training and inference. There are a lot of interesting companies along that spectrum, and I think that bodes well for companies in the space that want to go public.

A few companies entered your Top 20, including , , and . Does that reflect a durable shift away from traditional software, or are investors chasing a small group of scarce, high-profile hard-tech companies?

Haslett: I think it reflects a thematic shift. The companies entering that list generally fall into AI infrastructure, space tech and robotics.

If those are industries we think will have generational growth opportunities, the logical conclusion is that each sector will have winners. SpaceX gets people thinking about opportunities in space and space tech, and by extension defense tech.

The same applies to AI infrastructure. If the market is that big, and we鈥檝e seen companies go public over the last year or so, it stands to reason investors will be interested in other companies in that space. I think that鈥檚 more important than simply chasing scarce supply.

These businesses tend to be more capital intensive and may take longer to reach predictable revenue than a traditional SaaS company. How are secondary investors underwriting them?

Haslett: If a company needs more capital, investors have to decide whether the overall opportunity is big enough to justify waiting longer and having the company raise more.

If you have to build a factory or get regulatory approval, that can delay the company鈥檚 ability to increase its valuation or reach an exit. Investors discount that into what they鈥檙e willing to pay.

Secondary investors are making the same calculus as primary venture and growth investors, so you鈥檇 imagine much of that is already baked into headline valuations from primary raises.

What鈥檚 changed is that capital-intensive companies now have more financing options. Five or six years ago, a battery company or new chip manufacturer might have had little choice but to raise equity. In 2026, more credit and asset-based financing options are available.

That matters because if one of these companies underperforms or has a distressed asset sale, creditors and lenders get paid first. Secondary investors have to factor that in, too.

EquityZen says the average transaction occurred at a 38% discount to the last funding round, while many AI transactions traded at premiums. What does that say about how bifurcated the private market has become?

Haslett: I don鈥檛 know if it鈥檚 a mispricing. There are essentially two vintages of private companies right now.

Some companies weren鈥檛 built AI-first and have had to adapt. Many raised during the go-go years of 2021, at very high valuations, and may not have raised since. They鈥檝e had to rethink their strategies, which can slow growth and execution. That gets reflected in the discount.

Then there鈥檚 a new wave of companies, from 2023 and beyond, that were built with an AI-first mentality. They started from a clean slate, may operate more efficiently, and have a cleaner story for the market.

Some of those companies are raising rounds in quick succession at higher valuations. Secondary investors may pay a premium because they believe the company鈥檚 trajectory is clear and the next valuation increase could happen quickly.

is an example from the 2021 cohort. It raised at roughly a $10 billion-plus valuation and just sold for substantially less. It鈥檚 still a good business, but when investors compare 20% growth with newer companies going from zero to hundreds of millions in revenue in just a few years, you can understand why their appetite changes.

We may see more companies from that era sell for less than where they raised in 2021.

Over the past few years, many private companies have conducted secondaries because they weren鈥檛 ready to go public. When should founders consider establishing a company-approved secondary program?

Haslett: Historically, companies started thinking about liquidity programs after they鈥檇 been around five, six, or seven years, largely to reward employees for their patience and provide liquidity to early investors.

Now we鈥檙e seeing younger companies engage in controlled liquidity and tender offers.

One reason is talent retention. There are only so many engineers and data scientists, and companies need to compete for them. Secondary liquidity has become more normalized.

More solutions are available than before. Morgan Stanley, for example, has significantly grown its tender-offer activity as investor interest and available tools have expanded.

There鈥檚 also more investor appetite. Investors are increasingly willing to gain ownership through tender offers or secondary transactions. Five years ago, that was far less common.

Right now, it鈥檚 a very founder- and employee-friendly environment, and investors are willing to support secondary liquidity because they want access. If markets turn, that pendulum could shift back.

For investors considering private-company shares, what does a secondary-market price tell them compared with the valuation at the company鈥檚 last fundraise?

Haslett: I think it gives them the true price.

A primary valuation is a point-in-time measure of what investors were willing to pay, and those investors generally received preferred stock with additional rights and liquidation preferences.

The secondary market is more telling of what you could actually get in your pocket now. For companies that embrace secondary liquidity, those prices help employees, former employees and early investors understand what their shares are actually worth.

How does EquityZen calculate popularity and distinguish durable investor demand from curiosity or hype?

Haslett: Our platform allows investors, typically retail accredited investors, to tell us what they鈥檙e interested in. They can browse companies, review our analysis, and indicate which companies they would invest in, if shares became available, and at what size.

That gives us a real-time metric of what our user base wants to invest in and how much. It helps guide where we spend our time bringing opportunities to clients.

The last thing we want is to work with a shareholder when we can鈥檛 find a buyer, or with a buyer when we can鈥檛 find shares for sale.

What does the recent consolidation in the secondary market tell you about how the market is evolving?

Haslett: There was a lot of attention toward the end of 2025 around consolidation in the secondary-market space. went to , and EquityZen went to Morgan Stanley.

To me, that reflects market growth, increasing adoption of secondary liquidity, and the fact that the biggest financial institutions are paying attention. I don鈥檛 expect that to change.

Your data showed that some software companies began trading at premiums again in the second quarter. What separates those gaining investor confidence from those still trading at deep discounts?

Haslett: Execution. Leadership and execution.

It鈥檚 about a company鈥檚 ability to take a legacy SaaS business and turn it into something AI-enabled across the business. Are you using AI tools to improve internal tasks? Are you building AI into your product for clients?

Companies that can combine the stickiness and customer loyalty they鈥檝e already built with their domain expertise and AI are going to do just fine. The ones that are slower to adopt are going to get pummeled.

Six months ago, there was concern that when a company like announced a cybersecurity or legal tool, companies in those sectors would immediately lose value. I think some of that was a knee-jerk reaction.

Customers already using your software have some patience, but they also expect you to keep improving the product and give them a reason not to switch. The companies that are slow to react, or too proud to react, are the ones I think will get hit hardest.

, and 1听are examples of software that is deeply ingrained in large enterprises. If companies can keep their products working well and keep adapting them, they still have a shot at being successful standalone businesses. It comes down to management execution.

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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 鈥斕齋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 Las Vegas-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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Correction: The article was updated to reflect Forge Industries’ correct headquarters location.

Related reading:

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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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