led the round, which included participation from , , , , and others.

Founded in 2020, New York-based Capchase initially made a name for itself by providing revenue-based financing for SaaS companies. However, by late 2022, the company began to evolve into its current iteration: a vendor-financing technology platform. Capchase embeds itself directly into the sales workflows of companies such as original equipment manufacturers, software vendors and cybersecurity providers.

It has entirely discontinued its revenue-based financing, and instead now focuses on B2B buy now, pay later tools that help software and hardware vendors offer flexible payment terms while getting paid upfront.

The concept addresses a longstanding friction point in enterprise sales: vendors want cash immediately, while buyers want to preserve capital. Rather than forcing a buyer to pay $1 million upfront in 30 days, Capchase allows a sales rep to offer more flexible terms 鈥� say, $15,000 per month for up to five years. When the deal is signed, Capchase pays the vendor the full amount upfront, net of a financing fee.

鈥淲e started to see that there was a very big pull in the market,鈥� , co-founder and CEO of Capchase, said in an interview. 鈥淲e saw that sales cycles were expanding, CAC was going up, and all of this was driven by the high interest rates. Buyers wanted to pay as late as possible and pay installments.鈥�

He added: 鈥淲e shipped a product quickly to solve that need, and we started to get very strong market pull to the point that that ended up eclipsing the other product lines, and we decided to focus everything there.鈥�

Displacing a legacy market with AI

The pivot has unlocked impressive growth. Capchase says it has a 400% growth rate over the past 12 months and forecasts another 200% growth in the upcoming year. Its workforce has scaled alongside this momentum, expanding to 75 employees, up from 50 a year ago.

While legacy banks, independent financing firms and captive financing arms have dominated the $1.3 trillion equipment financing market for decades, Capchase says it differentiates itself by replacing 1980s-era workflows with real-time automation.

Traditional financing approvals often require an email-driven back-and-forth that can take four to 17 days, according to Fernandez. Capchase claims to compress that timeline into seconds.

Capchase uses artificial intelligence and machine learning agents across its platform. For example, an 鈥渙rder generation agent鈥� parses uploaded quotes or purchase orders to create flexible payment links in under 60 seconds 鈥� down from a manual process that typically took eight hours 鈥� according to Fernandez. As another example, an AI email agent automatically handles multiparty coordination between vendors, resellers and buyers, all without human intervention.

鈥淲hat makes us different is that we are both the lender and the technology. And AI is what makes the combination work at the speed enterprise tech sales demands,鈥� Fernandez told SA国际传媒 News in an interview. 鈥淲e built the credit decisioning engines that allow us to look at all the data these other players look at as well, but we were able to do it and infer it in just seconds.鈥�

Moving upmarket and expanding globally

The new capital will primarily support Capchase’s rapid transition into the enterprise space.

鈥淚n the past 24 months, we went from serving vendors in the tens of millions of revenue to in the last 12 months in the hundreds of millions in revenue, and now in the multiple billions of revenue,” Fernandez said.

The startup鈥檚 platform now underwrites more stable, established borrowers. The average buyer utilizing Capchase has roughly $80 million in annual revenue, has been operating for over 20 years, and is profitable, he added. This profile has allowed Capchase to maintain a highly controlled risk environment and what he described as a “spectacular” default rate.

Capchase currently supports hundreds of tech vendors and tens of thousands of buyers. Its customer roster features enterprise tech giants, public cybersecurity firms and massive distributors, including , , , and .

Though Capchase keeps its specific financials, valuation and cumulative funding figures confidential, Fernandez confirmed that the latest capital injection represents a valuation step up from its 2021 $80 million Series B round. At the time of that raise, the company had raised more than $400 million in equity and debt.

Looking ahead, Capchase will use its fresh capital to scale beyond its core markets in North America 鈥� the U.S. and Canada 鈥� and Europe, including the U.K., Ireland, Belgium, Netherlands, the Nordics and Spain. Driven by direct demand from its enterprise partners, the company is officially entering the Australian market this year.

Reducing friction with flexible terms

, co-founder and managing partner of 01 Advisors, said he was drawn to Capchase primarily because of how AI has helped it disrupt traditional vendor financing.

Incumbents possessed plenty of capital but 鈥渉ave never been forced to build real technology because their customers had nowhere else to go,鈥� he wrote via email.

AI fundamentally shifts this dynamic, allowing Capchase to “underwrite a buyer and create accurate docs in 30 seconds,鈥� he said.

This solution hits close to home for Bain, who previously ran the sales team at and says he intimately understands the friction Capchase aims to eliminate. In traditional enterprise sales, momentum frequently stalls when a ready-to-buy customer hits a roadblock over payment terms, forcing sales leaders to either “discount to close, wait for the next budget cycle, or spend weeks negotiating.”

Those outcomes drain margin or time. Capchase completely removes that friction, Bain said, by offering instant approvals and flexible terms.

Fintech startups, particularly those that apply AI to traditionally manual or burdensome processes, have benefited from increased investment in recent quarters. Global funding to VC-backed financial technology startups totaled $53.8 billion in 2025, per SA国际传媒 . That鈥檚 a more than 29% increase from 2024鈥檚 total of $41.6 billion raised.

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• Exclusive: Capchase Raises $80M Series B To Give Startups Alternatives To Venture

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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.

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

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

2. , $700M, artificial intelligence: AI startup Hark landed a huge $700 million Series A led by, with participation from a of investors including chip giants , , and , as well as ,, , 1听补苍诲 . The San Jose, California-based company it鈥檚 building 鈥渁dvanced personalized intelligence and next-generation hardware鈥� and plans to release some kind of product later this summer.

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

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

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

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

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

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

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

10. , $150M, wealth management: Farther raised a $150 million Series D led by as investors continue backing platforms modernizing financial advisory services. The San Francisco-based company provides technology-enabled wealth management tools and has raised approximately $268 million to date. Farther didn鈥檛 reveal its valuation with the latest raise, only that it is 鈥渘ow a unicorn.鈥�

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 May 18-22. Although most announced rounds are represented in the database, there could be a small time lag as some rounds are reported late in the week.

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That鈥檚 up 49% from the $3.5 billion valuation it achieved when announcing its $300 million Series C 鈥� which included primary and secondary funding 鈥� in March of 2025. The latest capital infusion brings San Francisco-based Mercury鈥檚 total primary and secondary funding to approximately $700 million since its 2017 inception.

led the latest financing, which included participation from returning backers , , , , and .

Mercury counts more than 300,000 companies as customers, including startups and larger entities such as , , , , and .

Interestingly, Mercury recently received from the banking regulator, the OCC, to establish its own bank. This is in contrast to many fintechs, which typically work with a sponsor bank but are not banks themselves.

The company hit $650 million in annualized revenue as of the 2025 third quarter, and claims to have achieved four consecutive years of profitability on both a GAAP net income and EBITDA basis.

AI鈥檚 effects

鈥淎I is collapsing the friction between an idea and a company faster than anything I have seen in my career,鈥� , co-founder and CEO of Mercury, said in a press release. 鈥淲e are going to see more founders in the next five years than in the last twenty. But legacy banking in 2026 still works the way it did when I started my first company in 2006. I started Mercury because banking should do more than be a vault, it should help customers run the best business possible.鈥�

Fintech startups, particularly those that apply AI to traditionally manual or burdensome processes, have benefited from increased investment in recent quarters. Global funding to VC-backed financial technology startups totaled $53.8 billion in 2025, per SA国际传媒 . That鈥檚 a more than 29% increase from 2024鈥檚 total of $41.6 billion raised.

Disclosure: The author of this article is a freelance writer who also writes for Mercury鈥檚 independent magazine, Meridian.

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

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

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

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

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

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

鈥淲e tell you where to go, we protect your path, we finance your treatment, we support you,鈥� AlSalim said in an interview with SA国际传媒 News. 鈥淣o one else today bundles care, capital and financial protection into a single product.”

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

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

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

Treatment with 鈥榦utcome protections built in鈥�

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

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

鈥淲e are not just a financing company,鈥� AlSalim told SA国际传媒 News. 鈥淲e use data in order to create unique plans that are individualized with outcome protections built in.鈥�

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

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

Closed-loop model

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

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

The founder declined to provide hard revenue figures when asked about growth, saying that the company is 鈥渘ow developing a baby every 18 hours鈥� while maintaining a of 85, which is considered 鈥渆xceptional鈥� in the healthcare industry by , creator of the customer loyalty benchmark.

Building a village

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

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

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

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

Chen believes that Gaia stands out also because it is not 鈥渟imply a financing product.鈥�

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

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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.

Another week, another infusion of big AI rounds. For this past week, the largest fundraiser by a long shot was , a developer of AI customer experience tools that picked up $950 million. Other big rounds went to companies in sectors including satellite development, biotech, and, yes, more vertical AI and AI infrastructure.

1. , $950M, customer experience AI: Sierra, a provider of AI-driven tools for customer experience management, raised $950 million in fresh funding at a $15 billion valuation. and led the financing for the three-year-old, San Francisco-based company.

2.听, $455M, space tech: Astranis, a developer of advanced satellites for high orbits, secured $450 million in equity and debt investment. The financing included a $300 million Series E equity round led by and and up to $155 million in credit through .听

3.听, $250M, biotech: Natick, Massachusetts-based Anagram Therapeutics, a developer of a pill for people living with exocrine pancreatic insufficiency due to cystic fibrosis, pancreatic cancer and related disorders, closed on $250 million in new funding from .听

4.听, $200M, AI software development: Blitzy, developer of an autonomous software development platform, picked up $200 million in fresh funding at a $1.4 billion valuation. Northzone led the financing for the Cambridge, Massachusetts-based company.听听

5. , $160M, insurance: Corgi Insurance, provider of an AI-native insurance platform for startups, secured $160 million in Series B funding. led the financing, which set a $1.3 billion valuation for the San Francisco-based company.听

6. , $140M, renewable energy: Portland, Oregon-based Panthalassa, which aims to perform AI inference computing at sea using power generated from ocean waves, raised $140 million in a Series B financing led by .

7. , $125M, insurance: Reserv, a provider of third-party administrator services to the insurance industry, closed on $125 million in a Series C funding round led by . Launched in 2022, New York-based Reserv has raised over $200 million in known funding to date, per SA国际传媒 data.

8.听, $107M, AI infrastructure: DeepInfra, a cloud platform for high-throughput AI inference, landed $107 million in Series B funding. and led the financing for the four-year-old, Palo Alto, California-based company.

9. , $60M, vertical AI: San Jose, California-based Tessera Labs, developer of an AI platform for enterprise ERP systems and data, secured $60 million in a funding round led by .听

10. , $56M, gaming: Astrocade, developer of an AI platform for creating, building and playing games, announced $56 million in new funding. The funding for the Los Altos, California-based company includes a Series B led by and a Series A led by , Astrocade said.听

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led the financing, which included participation from (Google鈥檚 early-stage AI fund), , , , and several angel investors. The raise brings Fazeshift鈥檚 total raised to $22 million since its 2023 inception.听

The San Francisco company was founded by a team with an unconventional pedigree: (CEO), a former consultant and mechanical engineer and (CTO), an -trained nuclear submarine officer.听

The two met at , but their lightbulb moment came while running a previous startup, , where they found themselves color-coding spreadsheets to track payments for just 10 customers and realized that the tools they were using failed to solve the basic problem of ensuring money actually hits the bank.

They realized that while there are more than a million accounts receivable (AR) clerks in the U.S. alone, many of them spend their time bouncing between systems such as , CRMs like , bank portals, and email threads because these systems do not natively talk to each other.听

Unlike accounts payable, which a company can standardize internally, Leksana contends, accounts receivable is a “snowflake” problem that remains one of the least automated functions in finance. Every customer has a unique set of requirements; for instance, a large retailer might demand that an invoice be submitted through a specific proprietary portal with Part A and Part B attached as PDFs.听

Fazeshift claims that it can automate more than 90% of manual AR tasks 鈥� from invoicing and collections to payment matching and reconciliation 鈥� by operating on top of existing systems and executing workflows across them. It essentially sits on top of a company鈥檚 current stack as a 鈥渂rain.鈥�

Competitors, according to Leksana, are generally focused on automating tasks, while Fazeshift is working on building what she described as an 鈥渋ntelligent control layer鈥� that helps companies 鈥渃ollect faster, more predictably and with less effort, and that is continuously improving through proprietary payer behavior data.鈥�

鈥淲hat sets us apart is our ability to handle complex workflows that other tools fail to solve 鈥� especially in industries like wholesale, construction, staffing, and HVAC, where AR processes are highly fragmented and manual,鈥� Leksana told SA国际传媒 News in an interview.

An OS for the finance organization

After launching at the start of the Summer 2024 Y Combinator cohort, Fazeshift has seen its revenue grow 12x in a single year, attracting dozens of enterprise customers, including eight unicorns and its first public company, according to Leksana.

Customers include , , , and , as well as one of the largest independent wholesale distributors in the Southeast, the world鈥檚 top e-commerce aggregator, and a leader in music publishing, per Leksana.听

Looking ahead, Leksana believes that Fazeshift has the potential to expand beyond accounts receivables. The goal is for Fazeshift to become the primary operating system for the entire finance organization.

鈥淥ur long-term vision is to expand into a broader CFO suite,鈥� she said, 鈥渂uilding toward a future of autonomous finance where core operational work is executed by AI and human teams can focus on agent management, strategic work, and governance.鈥�

Broken workflows for 鈥榗ritical functions鈥�

, partner at F-Prime Capital, said her firm was impressed by Fazeshift鈥檚 efforts to meet the needs of companies still running AR mostly on spreadsheets and email.

鈥淵ou鈥檇 be surprised how many Fortune 500 companies only started adopting software a few years ago and still have dozens, if not hundreds, of AR clerks on staff,鈥� she wrote via email. 鈥淭hat gap between how critical the function is and how broken the workflows remain is exactly the kind of opportunity we look for.鈥�

Wu also believes the market is at an inflection point where AI is moving from co-pilot to co-worker, and human teams are shifting from doing the work to reviewing and managing AI agents.

鈥淔azeshift is bringing us closer to an autonomous future for finance,鈥� she said. The founders had 鈥渓ived the pain of broken AR workflows firsthand at their last company and set out to build the platform they wished they鈥檇 had. When you meet founders like that, you move fast.鈥�

Fintech startups, particularly those that apply AI to traditionally manual or burdensome processes, have benefited from increased investment in recent quarters. Global funding to VC-backed financial technology startups totaled $53.8 billion in 2025, per SA国际传媒 . That鈥檚 a more than 29% increase from 2024鈥檚 total of $41.6 billion raised.

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• Fintech Startups Globally Raise More Money In Far Fewer Deals In Q1 2026

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• 听

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With that in mind, its venture arm, , is backing startups that build the financial and technical infrastructure for a more autonomous economy.听

SA国际传媒 News recently conducted an email interview with , managing director of , about the firm鈥檚 investment thesis, the kinds of startups it aims to back, and how it works with founders to build and scale projects in the American Express ecosystem.听

Amex Ventures鈥� recent investments reflect its focus on an autonomous future. In April, it led a round into business identity infrastructure platform and also wrote a check into , an agentic marketing platform that raised a $43 million Series B. It also backed Candex, a startup that uses AI and aims to help large companies pay small, one-time, or irregular vendors without the administrative headache or risk that comes with onboarding them.听

Since joining Amex 15 years ago, Tsang has been responsible for identifying and executing strategic investments in early- to growth-stage startups that fit the American Express thesis. He also leads the firm鈥檚 consumer services investment vertical, focusing on the future of membership, and oversees the firm鈥檚 global portfolio management operations.

Before joining American Express, he was part of the diversified industrials investment banking group at , where he focused on M&A and corporate finance transactions.

The interview has been edited for brevity and clarity.

SA国际传媒 News: In the 鈥�2025 GenAI era,鈥� we focused on tools that inform decisions. Now that we鈥檙e in the ‘2026 Agentic era,’ where agents execute transactions, how has the bar shifted for founders pitching Amex Ventures? Are you prioritizing the AI model or the trust/identity layer that will allow an agent to use a Platinum card autonomously?

Tsang: The bar for Amex Ventures investment has shifted toward agentic commerce systems that can navigate complexity and help facilitate end-to-end workflows for customers, with appropriate user authorization and controls. The most compelling founders operate companies that can handle much more of the full commerce journey, not just surfacing options, but incorporating context, executing user decisions, and ultimately completing tasks, with personalization increasingly becoming a key differentiator in how those experiences are delivered and retained.

Agentic commerce systems are sometimes framed too narrowly as just the final execution step, but the real opportunity 鈥� and where we are seeing the most innovation 鈥� is in systems that can understand preferences, constraints, and intent, and then orchestrate a complete experience that properly reflects them.听

Over time, this could evolve to support more comprehensive experiences, such as planning entire trips rather than just recommending a flight, or managing a series of related actions instead of a single step. AI also has the potential to help scale the kind of high-touch, tailored experiences that were once reserved for a small set of customers to a much broader base.

From our perspective, we are less focused on any single layer, whether that is the underlying model or the trust and identity infrastructure, and more focused on how these components come together to deliver a seamless and high-quality customer experience.听

Trust and security are foundational, especially in financial services. Ultimately, we are looking for founders who are building with the ambition and technical depth to address real-world complexity, while delivering meaningful outcomes for customers with a focus on security and compliance.听

Many founders struggle with the 鈥淐VC paradox鈥� 鈥� getting a pilot with Amex is a huge win, but scaling it globally can take years. What is the most effective way a founder can leverage your firm to move from a localized experiment to a core membership benefit?

We see the most successful commercial partnerships follow a crawl, walk, run model 鈥� starting with a focused pilot, learning quickly, and then building toward broader integration and scale.

Our investment model creates shared incentives to build commercial partnerships that benefit both American Express and our portfolio companies, and we help advance these relationships over time. We look for founders who continue to iterate and innovate so that the scope of these partnerships can expand in a meaningful and sustainable way.

For example, we recently invested in the startup , an agentic marketing platform that helps enterprises understand, influence, and measure how brands are represented across AI-powered channels. At American Express, we are utilizing Bluefish鈥檚 technology to support our agentic search efforts, including our Answer Engine Optimization (AEO) strategy.

For travel and dining startups, customer acquisition cost (CAC) is skyrocketing due to influencer-driven marketing. How much does a startup鈥檚 ability to plug into the Amex 鈥榗losed-loop鈥� ecosystem factor into your valuation, versus their organic growth?

When we evaluate companies, we start with the fundamentals. We are looking for businesses that can stand on their own, with strong products, clear value propositions, and sustainable growth models. That is core to any investment decision we make.

At the same time, one of the advantages of an investment from Amex Ventures is the potential to partner with American Express and engage with our ecosystem, which we see as a meaningful opportunity for many companies. When there is a clear path to creating mutual value through a commercial partnership, it can strengthen our conviction to invest.

That said, we do not invest simply because a company is likely to have a commercial relationship with American Express. To invest, we must believe in the underlying business on its own merits.听 The potential for an American Express partnership represents additional upside and an opportunity to accelerate the company’s growth together.

With tech M&A volumes up significantly this year, are you managing the current portfolio with an eye toward strategic buyouts by Amex鈥檚 parent company, or are you pushing for independent IPO-ready unit economics given the partially reopened window?

We are not managing the portfolio with a specific exit outcome in mind. Our focus is on investing in companies that can build strong, durable businesses and on creating strategic relationships with our portfolio companies that drive value on both sides.

In many cases, that means working closely with our portfolio companies to explore potential commercial relationships with American Express, which is core to our role as a corporate venture investor. In fact, nearly two-thirds of our portfolio companies have had a commercial relationship with American Express.

From there, a company鈥檚 path, whether toward an IPO or M&A, is ultimately driven by the founder and the broader investor group. Our role is not to steer that outcome, but to support the company in building long-term value and maintaining the flexibility to pursue the right exit opportunity.

When you look at the current 鈥渟ervice-as-software鈥� startups, do you see them as long-term standalone companies, or are we looking at a massive consolidation cycle where travel/dining tech eventually gets absorbed back into the major financial rails?

There are a number of ways this could play out, and it will likely vary by industry. In some sectors, particularly those with high levels of specialization or unique requirements such as regulation, there is a clearer path for companies to build durable, standalone businesses that deliver meaningful value over the long term.

At the same time, we are starting to see early signals that consolidation could emerge in certain areas, particularly at more horizontal layers of the AI stack, where capabilities can extend naturally across multiple use cases. It is still early, though, and the boundaries of how far that consolidation will go are being defined.

In lifestyle categories like travel and dining, I believe the outcome will be a mix. For example, in travel, there is already a range of booking options available to consumers. While there has been some consolidation amongst these companies, many have continued to find ways to differentiate and add value.听

We expect a similar dynamic to continue, with some companies scaling independently while others partner more deeply or join broader platforms over time.

Related SA国际传媒 query:

• 听

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Two newly founded AI labs, both based in London and both with researchers from , raised large rounds out of the gate and made their Unicorn Board debuts. The two companies, and , both raised large initial fundings out of the gate, though take very different approaches to training AI.听 They were joined by another new unicorn in the foundation AI sector: , an open-source model company from China with on-device smaller models.听

Six companies working on humanoid robotics 鈥斕齠ive from China and one from Japan 鈥� also received billion-dollar-plus valuations last month. Quite a few of these companies are building models for robotic intelligence using simulated data.听

The financial services, defense, developer tools, energy and healthcare sectors each added two or three new unicorns in April.听

Of the 28 companies, 12 are U.S.-based and eight are from China. The UK counted two new unicorns last month, while Germany, Spain, Switzerland, India and Japan each added one.听

April鈥檚 new unicorns

Here are April鈥檚 new unicorn companies. Of the 28 companies, 26 are AI-related.听

Foundational AI听

• , a London-based AI lab using reinforcement learning rather than human-generated data, raised a $1.1 billion seed round led by and . The less than 1-year-old company was founded by of AlphaGo and . It was valued at $5.1 billion in its first funding.听
• London-based , a new AI intelligence lab with the goal of continuous learning improvement, raised a $500 million Series A led by and . Founded by DeepMind researchers and 鈥檚 1 previous AI lead, the less than 1-year-old company was valued at $4.5 billion.听
• Beijing-based , an on-device foundation model developer, raised funding led by and . Its open source MiniCPM is deployed in automotives, smartphones, PCs and home devices. The 3-year-old company was valued at $1 billion.听

Robotics听

• Shanghai-based is a robotics AI company building a foundational model as well as hardware. It uses simulated training to create a model for grasping and spatial awareness. The 1-year-old company raised a Series A round and was valued at $2 billion.
• Shanghai-based humanoid robotics company raised a $513 million seed round led by and HSG. The 1-year-old company was valued at $1.9 billion.听
• Beijing-based , a hardware and software developer of models for robotics using simulated data, raised a $220 million Series B. The 3-year-old company was valued at $1.5 billion.听
• Shenzhen-based , a builder of humanoid and quadruped robots, raised a $200 million Series B led by and . The 2-year-old company robots will be deployed for traffic, security and retail. It was valued at $1.5 billion.听
• Shenzhen-based , a commercial robotics company for delivery and commercial cleaning, raised a $146 million funding led by and . The 10-year-old company was valued at $1.5 billion.听
• Tokyo-based , a humanoid robotics company to address public safety and urban maintenance, raised a Series A led round. The 1-year-old company co-founded by was valued at $1 billion.

Financial services听

• , which automates research for investment banks, raised a $160 million Series D led by . The 4-year-old New York-based company was valued at $2 billion.
• Bangalore-based , a consumer and small business lending service, raised a $220 million Series E led by , , and . The 8-year-old company was valued at $1.5 billion.听
• , a banking and expense management service targeting small businesses and solopreneurs, raised a $100 million Series C led by , and . The 5-year-old San Francisco-based company, founded by college dropouts at the time, was valued at $1.4 billion.听

Defense听

• Space defense company raised a $600 million Series D led by and . The company has built software for space operations and an autonomous orbital vehicle called Jackal. The 4-year-old, Colorado-based company was valued at $2.2 billion.听
• Defense aviation company raised a $200 million Series C led by Khosla Ventures. The 7-year-old El Segundo, California-based builder of autonomous aircraft was valued at $1 billion.听

Developer tools听

• , a web search provider for AI agents used by and , raised a $100 million Series B led by Sequoia Capital. The 2-year-old Palo Alto, California-based company was valued at $2 billion.听
• , an agentic software coding tool for enterprises, raised a $150 million Series C led by . The 3-year-old San Francisco-based company was valued at $1.5 billion.听

Energy听

• , developer of small nuclear reactors to provide direct power for AI data centers, raised a $340 million Series B funding. The 2-year-old El Segundo, California-based company was valued at $2 billion.听
• , a long duration energy storage battery provider, raised a $58 million Series C led by . The 12-year-old Bayern, Germany-based company that supports energy needs for grids, data centers and industry, was valued at $1.2 billion.听

Health care听

• Shanghai-based , a developer of a model for healthcare that includes computer vision and large language models, raised a $73 million Series A round. The 12-year-old company has built an assistant for doctors for screening, diagnosis and patient care, and was valued at $1 billion.听
• Switzerland-based , a developer of a peptide product to address enamel repair without needing surgery, raised a private equity funding led by . The 6-year-old company was valued at $1 billion.听

Data platform

• has built a semantic layer between data and agents necessary to interpret data and provide guardrails for AI. The 4-year-old San Francisco-based company raised a $120 million Series C led by and was valued at $1.5 billion.听

Manufacturing

• Shanghai-based , a collaboration tool to make factories more efficient, raised a $146 million Series D funding. The 10-year-old Shanghai-based company was valued at $1.3 billion.

Agentic AI

• , which builds agents trained on company data, raised a $80 million funding led by . The 1-year-old San Francisco-based company was valued at $1.3 billion.听

Aerospace听

• Madrid-based , which is building data from satellites tracking changes in the earth for various commercial needs, raised a $130 million Series B led by . The 6-year-old company was valued at $1 billion.听

Marketing & sales听

• , a provider of booking and customer service for the services industry using AI, has raised a Series B funding led by and . The 4-year-old New York-based company was valued at $1 billion. The company has raised $125 million in funding from seed through its Series B.听

Biotechnology听

• , an AI biotechnology infrastructure platform speeding up drug discovery, raised a $40 million Series E. The 8-year-old Waltham, Massachusetts-based company was valued at $1 billion.听

Waste management听

• converts unused food products into energy. It raised a Series C funding led by strategic partner . The 19-year-old Concord, Massachusetts-based company was valued at $1 billion.听

Related SA国际传媒 unicorn lists:听

• (1,756)
• (611)
• (128)
• (187)
• (118)
• (102)
• (896)
• (516)
• (239)
• (38)
• (477)

Related reading:

• March Mints 11 New Unicorns, As $200B Is Added Through Up Rounds And Board Posts Strong Exits听
• Billion-Dollar AI Rounds Push April To Third-Highest Startup Funding Month In A Year
• This Is A Momentous Year For Early-Stage Unicorns听
• The Rising Investors Behind The New Unicorn Class听
• While OpenAI Shattered Records, Robotics and Semiconductor Startups Quietly Added The Most New Unicorns In February听

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.

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This increase was driven by large rounds to AI lab and Jeff Bezos鈥檚 , which is focused on AI manufacturing. The two companies raised $15 billion and $10 billion, respectively, together accounting for 45% of venture capital in April.听

Large rounds across multiple sectors

Billion-dollar rounds were also raised by Swedish green steel production plant , New York-based AI data operations provider , and London-based AI lab , which was founded by former employees.

Rounds $500 million and above were raised by Michigan-based modular electric pickup truck manufacturer , Colorado-based space defense company , Shanghai-based humanoid robotics startup , another London-based frontier lab, , and London-based , a global payments platform majority-owned by .

AI led

Artificial intelligence funding in April reached $37 billion, accounting for 66% of global venture investment last month.听

AI model companies raised the lion’s share of capital at $26.7 billion. Physical AI in robotics, aerospace, drones and autonomous vehicles represented around $5.3 billion. And AI infrastructure in semiconductor and data centers raised $1.8 billion.听

The U.S. once again dominated startup funding, with American companies raising $39 billion, or around 70% of global venture capital.

Public markets and GDP growth

The first quarter of this year showed the dominance of AI in both the public and private markets, and that continued into April.

As the hyperscalers , and topped analyst revenue expectations and continued heavy AI expenditures, around half of the 2% U.S. GDP growth in Q1 was due to AI buildout, per an estimate from Oliver Allen, an economist with .

That was mirrored on the private-market side. Global venture investment is up 139% year over year through April, per SA国际传媒 data, with nearly 60% of that capital going to just five companies backed by deep-pocketed public technology companies, private equity and venture investors.

Related SA国际传媒 query:听

Related reading:

• Q1 2026 Shatters Venture Funding Records As AI Boom Pushes Startup Investment To $300B听

Methodology

The data contained in this report comes directly from SA国际传媒, and is based on reported data. Data reported is as of May 4, 2026.听

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. 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.

Glossary of funding terms

Seed and angel consists of seed, pre-seed and angel rounds. SA国际传媒 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. SA国际传媒 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.听

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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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.

Large U.S. venture deals this week were led by a massive defense tech raise for space security startup . That theme continued with another two aerospace- and defense-related companies also getting major investor backing. We also saw sizable deals for startups applying AI to fintech, marketing, customer service, healthcare and developer tools. Let鈥檚 take a closer look.

1. , $600M, aerospace and defense: Centennial, Colorado-based True Anomaly raised a massive $600 million Series D led by and , with participation from a long list of other backers including , , , , and . True Anomaly develops space security and in-orbit defense systems, an area drawing increasing venture investor attention amid rising geopolitical tensions. The new round brings its total funding up to $1.1 billion, .

2. , $160M, AI and fintech: New York-based Rogo secured $160 million in Series D funding led by and joined by other investors including , , , , and . Rogo builds AI-powered tools to automate financial research and workflows. The latest financing brings its total funding raised to date to $314 million, . The deal is also the latest example of investor enthusiasm for startups targeting high-value knowledge work such as law and accounting.

3. , $150M, AI and marketing: San Francisco-based Hightouch raised $150 million in a Series D co-led by and . , , , and other investors joined. The company focuses on agentic AI-driven marketing and customer data activation. The round brings Hightouch鈥檚 total funding to date to and comes amid rising demand for AI tools embedded directly into enterprise marketing stacks.

4. , $125M, AI and customer service: New York-based Avoca brought in $125 million in a Series B led by and, with participation from other investors including , , and . Avoca develops AI agents for customer communication workflows. The new raise brings its total funding to $125.5 million, .

5. , $110M, AI and customer service: San Mateo, California-based Netomi raised $110 million in a Series C led by , with participation from and others, including individual investors , , and . The company offers AI-powered customer experience automation across channels. The new funding brings its total raised to date to $217 million, .

6. (tied) , $100M, developer tools: Palo Alto, California-based Parallel secured $100 million in a Series B led by , with additional backing from other big-name investors , and . The startup is building a suite of AI agents and developer tools to automate workflows. It has raised $260 million to date, .

6. (tied) , $100M, aerospace and defense: Sunnyvale, California-based Scout AI raised a sizable $100 million Series A led by and . A long list of other investors joined, including , and . The startup develops AI systems for aerospace and defense applications. Its large early-stage round underscores continued investor appetite for dual-use and defense-focused startups, which globally raised a record $7.7 billion in 2025, per SA国际传媒 data.

8. , $82M, aerospace and defense: San Diego-based Firestorm closed an $82 million Series B led by . also participated in this round, as did , , , and others. Firestone builds modular, mission-adaptable drone systems. It has raised nearly $150 million total, .

9. , $77M, health diagnostics: Cambridge, Massachusetts-based Iterative Health raised $77 million in a Series C led by and, with additional backing from , and . The company develops AI-powered diagnostic and clinical workflow tools, particularly in gastroenterology. It has raised more than $268 million since inception, according to .

10. , $75M, foundational AI: Investors continue to back next-generation foundation model startups. One of the latest is San Francisco-based AI research startup Standard Intelligence, which raised a $75 million Series A led by and . The raise comes at a $425 million pre-money valuation. Other investors in the deal include , and AI researcher . Standard AI is developing 鈥渃omputer-use鈥� models designed to interact directly with software. Its approach 鈥� training on large-scale video data rather than manually annotated screenshots 鈥� aims to significantly reduce costs and improve performance.

Large non-US deals

We also saw several sizable deals for startups based outside the U.S.:

, $1.1B, foundational AI: London-based frontier lab Ineffable Intelligence raised a $1.1 billion seed round, the largest for a European startup on record. (The previous record was set just a couple of months ago, when Paris-based frontier lab raised a $1.03 billion seed round.) and led Ineffable鈥檚 seed funding.

, $300M, aerospace: China-based Volant Aerotech raised a $300 million Series C led by . The company is developing electric vertical takeoff and landing aircraft, or eVTOLs, designed to be used as taxis.

, $200M, robotics: China-based humanoid robot developer Robot Era raised a $200 million round led by , with participation from a long list of investors including and . The company is developing robots designed for industrial and service work, and follows a string of other large fundings for China-based robotics startups.

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 April 25-May 1. 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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