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 — 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.

“We started to see that there was a very big pull in the market,” , co-founder and CEO of Capchase, said in an interview. “We 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.”

He added: “We 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.”

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 “order generation agent” parses uploaded quotes or purchase orders to create flexible payment links in under 60 seconds — down from a manual process that typically took eight hours — according to Fernandez. As another example, an AI email agent automatically handles multiparty coordination between vendors, resellers and buyers, all without human intervention.

“What 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,” Fernandez told Crunchbase News in an interview. “We 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.”

Moving upmarket and expanding globally

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

“In 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’s 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 — the U.S. and Canada — 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 “have never been forced to build real technology because their customers had nowhere else to go,” he wrote via email.

AI fundamentally shifts this dynamic, allowing Capchase to “underwrite a buyer and create accurate docs in 30 seconds,” 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 Crunchbase . That’s a more than 29% increase from 2024’s total of $41.6 billion raised.

Related Crunchbase query:

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• Fintech Startups Globally Raise More Money In Far Fewer Deals In Q1 2026
• 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’s top 10 announced funding rounds in the U.S. Check out last week’s biggest funding deal roundup here.

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

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

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

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

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

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

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

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

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

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

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

Methodology

We tracked the largest announced rounds in the Crunchbase database that were raised by U.S.-based companies for the period of May 18-22. Although most announced rounds are represented in the database, there could be a small time lag as some rounds are reported late in the week.

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That’s up 49% from the $3.5 billion valuation it achieved when announcing its $300 million Series C — which included primary and secondary funding — in March of 2025. The latest capital infusion brings San Francisco-based Mercury’s 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’s effects

“AI is collapsing the friction between an idea and a company faster than anything I have seen in my career,” , co-founder and CEO of Mercury, said in a press release. “We 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.”

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 Crunchbase . That’s a more than 29% increase from 2024’s total of $41.6 billion raised.

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

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

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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 — trained on millions of anonymized historical data points and fertility outcomes — to better understand risk and probability for fertility treatment.

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

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

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

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

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

Treatment with ‘outcome protections built in’

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

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

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

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

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

Closed-loop model

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

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

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

Building a village

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

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

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

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

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

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

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• VC Investment Soars For Fertility Services Even As Birthrate Dips

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Goldman Sachs Alternatives has committed up to $50 million to the round, including an initial $25 million investment and an additional $25 million to be funded in the coming months, subject to undisclosed conditions.

Existing backers and also participated in the financing, which brings New York-based Kashable’s total equity and debt raised to more than $450 million since its 2013 inception. The company declined to reveal its valuation saying only it had tripled since its January 2024 Series B raise.

The premise behind Kashable is that, since its loans are facilitated through an employer, the service can often offer better rates than a traditional bank might — making it a more appealing alternative to high-interest credit cards or payday loans.

In addition to low-cost loans, Kashable partners with employers to provide employees with a suite of financial wellness services, including credit monitoring, financial coaching and affordable credit. Employers offer the services as employee benefits integrated with their HR and payroll systems.

Big growth

Kashable has grown more than 40% year over year so far in 2026, according to co-CEO and co-founder , an computer scientist and former derivatives trader. Its revenue model is driven by interest and fees paid on loans and administrative fees from employers for customized programs.

To date, the company has funded nearly $2 billion in loans and expects to surpass $500 million in volume in 2026 alone. Co-founder and co-CEO told Crunchbase News that Kashable is profitable, and has been “for several years.”

“Timely repayments [of loans] through payroll reduce default rates, giving Kashable better unit economics that it can then pass on to its customers as lower-cost loans,” Kumar told Crunchbase News.

Kashable’s platform is available to over 4 million employees across more than 600 employers. Its customers include governments, large nonprofits such as universities and hospitals, school districts, and large companies. They include , , , , , , , the , and San Mateo County in California.

This isn’t the first company that Kumar and Steklov have started together. The pair also founded , a commercial finance company, in 2008.

Investor POV: ‘Essential liquidity’ on fair terms

, partner and head of inclusive growth at Goldman Sachs Alternatives, told Crunchbase News via email that his firm’s investment in Kashable was driven by its mission “to support innovative solutions that help working Americans lead more secure financial lives.”

“The American workforce is facing a significant squeeze as job security and wage growth has struggled to keep pace with inflation, eroding personal savings and the ability to absorb unexpected financial pressures,” he said. “We recognized Kashable’s model and mission as differentiated, providing essential liquidity on fair, transparent terms, in a way that is substantial enough to offer true long-term relief rather than a short-term, expensive Band-Aid. Kashable’s platform offers a necessary financial bridge that helps users navigate personal liquidity needs without falling into predatory debt cycles.”

Shell also believes that Kashable stands out due to its “unique” structural advantage. Its integration with employer’s payroll systems gives it the ability to get a more accurate picture of creditworthiness, he said.

“Consequently, Kashable sustains meaningfully lower loss rates than its competitors,” Shell added, “and can pass the resulting savings directly to its borrowers in the form of lower interest rates”

Fintech startups have benefited from increased investment in recent quarters. Total global funding to VC-backed financial technology startups totaled $53.8 billion in 2025, per Crunchbase . That’s a more than 29% increase from 2024’s total of $41.6 billion raised.

Related Crunchbase query:

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

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was founded in 2023 on the idea that winding down a startup shouldn’t be chaotic, opaque or a total loss for founders and investors. Since then, it raised just over $20 million from investors including,,, and

Founder and CEO came up with the concept while building his previous company, after a board member asked him to produce a “shutdown analysis.” The process proved so complex and time-consuming that it sparked the idea for a software platform to automate and streamline company closures.

Three years later, Los Angeles-based SimpleClosure is expanding that vision with the launch of Asset Hub, a marketplace designed to help founders recover value from what they’ve built — from source code and operational data to domain names and equipment — rather than letting those assets disappear in the shutdown process.

Crunchbase News spoke with Yona via email about the new product, the rise in startup shutdowns, and how attitudes around failure are beginning to shift.

This interview has been edited for brevity and clarity.

Crunchbase News: Are we seeing more shutdowns than in the past?

Yona: We’ve seen strong year-over-year growth in startup shutdown activity over the past few years, and that trend has continued into 2026 so far. Based on our data, in Q1 2026 we saw 2.6x more companies close compared to Q1 2025.

Tell us more about the Asset Hub and why you launched it.

This offering was part of our original vision for SimpleClosure and has continued to be reinforced by feedback from the thousands of founders we have worked with over the past three years.

In our early days, we kept hearing the same thing: Selling off assets was one of the most frustrating and opaque parts of winding down. Companies had spent years building real things: source code, internal tools, operational data, but when it came time to shut down, there was no straightforward way to find buyers or capture any of that value. It just evaporated.

We’re launching the Asset Hub with two initial offerings: Source Code and Workplace Data (beta), but it doesn’t stop there. We’re talking about physical equipment like laptops, domain names, IP — all the things a company accumulates over its lifetime that still hold value but often get written off or forgotten during the chaos of a shutdown.

SimpleClosure has always been about making the shutdown process more efficient, more compliant and less painful. Asset Hub is the natural next step, moving beyond the paperwork and filings to actually help founders walk away with something tangible from the work they put in.

With the industry now actively seeking real-world codebase and workplace data to train the next generation of models and agents, the timing couldn’t be better. What used to be abandoned assets now have a real market, and we’re in a unique position to facilitate that connection on behalf of our customers.

We’re seeing more capital-intensive sectors like biotech and climate tech beginning to use SimpleClosure. How does the dissolution process change when you’re dealing with physical assets and complex IP rather than just code and a cap table?

The underlying dissolution framework is the same. You still need to wind up the company by settling liabilities, handling assets, and distributing any remaining proceeds in the correct priority order.

What changes with capital-intensive industries like biotech or climate tech is the nature of the assets and obligations, which introduces more complexity in a few key areas: Physical assets require real-world disposition. Instead of just transferring code or shutting down software, you’re dealing with lab equipment, inventory or hardware. These need to be inventoried, stored, sold, or disposed of, often with logistics, costs, and timelines involved. We have some liquidation partners who assist in this area.

IP is more complex and often more valuable. Rather than a codebase, you may have patents, filings or licensed technology. That means more formal valuation considerations, potential buyers or licensing opportunities and additional documentation to properly transfer or assign rights.

The process isn’t fundamentally different, but it’s more hands-on, more document-heavy, and requires tighter coordination across legal, financial, and operational workstreams to ensure everything is properly closed out.

As we move into 2026, “simple” rule-based automation is being replaced by adaptive AI. How is SimpleClosure moving toward “Cognitive Partnering” to help founders make nuanced decisions about creditor negotiations rather than just filing paperwork?

At a baseline, dissolution still requires structured, rule-based steps (filings, notices, sequencing). But where founders really need help is in the gray areas, especially around creditor strategy, tradeoffs, and timing.

That’s where cognitive partnering would come in.

Founders often ask questions such as: Am I allowed to settle this vendor at 50%? Can I pay this vendor first? What happens if I don’t respond?

Rather than giving a single answer, we help frame what’s required in terms of creditor priority, where there’s flexibility, and what risks are introduced by each path.

We’re also able to see pattern recognition across hundreds of shutdowns, and are starting to leverage what we’ve seen across many wind-ups, such as where delays create real risk versus just noise and what “good” vs. “problematic” outcomes look like.

We also keep humans in the loop for judgment calls. We’re not trying to fully automate these decisions — they’re too nuanced. The goal is that AI surfaces context, options, and risks while humans make the final call.

We’re moving from: “Here’s what to file next” to “Here’s how to think about this decision, what your options are, and what the consequences look like.”

Is there a future where your platform provides “health monitoring” tools to help founders recognize months in advance when a pivot or a clean shutdown is their best fiduciary path?

Potentially. It is definitely something that comes up with founders from time to time.

Making the decision to shut down however, is typically based on more than just company health. It is often an emotional decision for the founder that marks the end of a multi-year journey.

We will never push the founder into a dissolution. The decision has to come from them.

Is it accurate that your company has helped return more than $150 million to investors that might have otherwise been trapped in “zombie” companies? Do you see a shift in VC sentiment where a “clean failure” is now viewed as a more positive signal for a founder’s next raise than a slow, three-year bleed-out?

Yes! That’s accurate, and as of this week we’ve actually helped return over $200 million to stakeholders.

What we’re seeing from both founders and investors is a real shift in mindset. A few years ago, there was more tolerance for companies lingering, trying to figure it out over long periods. Now, there’s a growing recognition that a clean, well-executed shutdown is often the more responsible outcome.

From a founder perspective, running a thoughtful wind-down (prioritizing creditors appropriately, returning remaining capital and closing things out cleanly) demonstrates strong judgment and integrity. That absolutely carries weight in future fundraising conversations.

From the investor side, capital efficiency matters more than ever. Getting capital back, even partially, and seeing that a founder handled a difficult situation responsibly is often viewed more positively than a prolonged burn with no clear path forward.

“Clean failure” is about communication and trust. Investors keep telling us what stresses them out isn’t a company that’s struggling, it’s a founder who goes dark when things get hard. Investors want the hard truth.

They don’t just want to hear from the founder when things are good. They want to hear when they’re stuck, because that’s when they can actually do something like brainstorm a pivot, restructure, raise a bridge round, or explore an exit or soft landing. Shutting down is almost never the first option they reach for. But they can’t help if they don’t know.

I recently chatted with a founder whose investor wants to back them a third time. Their first company exited. The second was a shutdown. By the third, the investor was writing a blank check because they’d seen this founder handle both the highs and the lows out in the open. The founders who handle the downside cleanly are the ones who get the next yes.

So yes, I would say that we’re increasingly seeing that a clean failure is not only more accepted, but in many cases preferred, because it preserves both capital and credibility.

After exited the shutdown space to back you, how has that partnership changed the way cap table data integrates into the dissolution process? Is the goal a “one-click” shutdown?

Carta has been very helpful. We’ve been working closely with them, and it’s been valuable not just for improving the product (cap table side of things) and user experience, but also for strengthening the brand and reputation venture-backed founders expect.

That said, the reality is that cap table data, even when coming from a system like Carta, still requires validation and context. Companies evolve over time, and by the time they’re shutting down, there are often nuances that need to be reconciled. So while integration helps streamline things, it doesn’t eliminate the need for thoughtful review.

On the idea of a one-click shutdown: We think about that a bit differently. There are definitely parts of the process that should feel close to one-click, such as pulling in cap-table data, generating documents and calculating distributions

But a shutdown is the unwinding of everything that went into building a company — contracts, obligations, stakeholders, and decisions made over years. There are some decisions that can and should be made by the founder themselves such as how to communicate with employees, investors and vendors. That’s not something that can, or should, be reduced to a single action.

You’ve often said that automating shutdowns helps break the taboo of failure. In 2026, are you seeing founders talk about their SimpleClosure experience as openly as they talk about their seed rounds?

We’re definitely seeing a shift. More founders are talking about their SimpleClosure experience in the same breath as their fundraising story, because for many of them, shutting down is part of the story. I can point to any of our customer testimonials to demonstrate that founders are increasingly willing to share their experience.

But I don’t want to overstate it. The stigma hasn’t disappeared. There’s still a version of founder culture where talking about closing your company feels like admitting defeat. What we are seeing is that SimpleClosure gives founders a way to close with their heads held high — the process is clean, documented and professional, and that changes both how they talk about it afterward and their relationships with investors, employees, vendors and other stakeholders moving forward.

A significant portion of your users are already working on their next company. What is the most common lesson learned you hear from founders who used your platform to close their first venture?

1. A lot of founders say some version of “I knew earlier than I acted.” They reflect that they held on just a bit too long, hoping for a turnaround, a fundraise, or a breakthrough. In doing so, they burned additional time, money, and energy that could have been preserved, as well as saving themselves some extra heartbreak. They could have started their next company already.
2. It’s not just your company or your money. You have obligations to vendors, employees, investors. And those obligations don’t go away just because things didn’t work out. The founders who go through a structured wind-down come out with a much clearer understanding of responsibility, and that shows up very differently in how they operate the next time.
3. How much unnecessary complexity founders take on without a downside plan. Debt, grants, multistate operations, vendor contracts … all of it feels manageable when things are going well. But during a shutdown, that complexity becomes friction and liability quickly. We’ve seen second-time founders are much more intentional in all fronts, from limiting vendors to debating whether to bootstrap for as long as possible. Indeed, these are many of the same lessons I have learned myself over my career as a founder.

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led the financing, which included participation from , , and . It brings Boulder, Colorado-based Schematic’s total funding since its 2023 inception to $12 million.

Schematic builds entitlements and enforcement infrastructure for SaaS and AI companies. Put more simply, it serves as a digital gatekeeper for software and AI companies. For example, if a company’s sales team wants to give a major client a special discount or extra storage, they have to ask an engineer to go in and “move the walls.” The process can be slow, expensive and tedious.

That’s where Schematic comes in. It essentially acts like a universal remote control for a company’s features.

Instead of burying those rules in the code, a company can plug Schematic into its product. Then, if it, for example, wants to launch a new “AI Tier” or change how many users a client can have, a person in marketing or sales can flip a switch in a simple dashboard.

“When a software company sells you a plan, something inside their product has to enforce what you can do and access based on what you paid for,” said CEO and co-founder . “Most companies build that enforcement infra themselves, often badly, and it becomes the thing that slows down every future monetization change. Schematic is the infrastructure that handles it, so engineering doesn’t have to.”

In addition to the fundraise, Schematic is also announcing that payment giant has tapped it “to solve entitlements as a first-class primitive: decoupled from code, enforced at runtime, on top of Stripe Billing.”

Schematic will be launching its new Stripe app publicly on stage next week at Stripe Sessions.

Systems like Stripe currently handle the money, sending invoices and charging credit cards. But Stripe doesn’t actually sit inside the app to block or allow a user from clicking a button. Schematic claims it will now serve as the “muscle” that actually enforces the rules that a platform like Stripe sets.

‘An emergent crisis’

By using Schematic, Glover said that companies like went from taking weeks to change their pricing to just 10 minutes. The startup’s other customers include , and .

AI has made entitlements an emergent crisis, in Glover’s view.

“Neither underlying costs nor customer value are predictable, and both accrue at runtime,” he told Crunchbase News. “This is why we describe what we’re building as runtime monetization infrastructure: Value is now accruing nondeterministically at runtime, and as a result, pricing and packaging have to be enforced at runtime. A shadow enforcement system catching webhooks from a billing platform cannot support this inflection.”

, general partner at S3 Ventures, said his firm was drawn to invest in Schematic for a few reasons.

“As operators and through our portfolio companies, we’ve seen firsthand how often pricing changes get delayed or deprioritized because entitlement logic is buried in application code. On top of that, AI is accelerating a structural shift away from seat-based pricing; hybrid and consumption-based models now represent 38% of SaaS companies and that number is rising as companies hone their AI pricing strategies, putting real pressure on legacy monetization architectures,” he wrote via email. “Finally, Fynn, Ben, and Gio have worked together for nearly a decade, and each of them encountered this specific problem while running pricing and packaging at growth-stage SaaS companies.”

Fintech startups have benefited from increased investment in recent quarters. Total global funding to VC-backed financial technology startups totaled $53.8 billion in 2025, per Crunchbase . That’s a more than 29% increase from 2024’s total of $41.6 billion raised.

Related Crunchbase query:

Related reading:

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

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His company raised a few million in seed, and lifted the curtain, and … crickets. Nothing happened. Businesses didn’t sign up. My friend was confused while prospective clients hesitated. This simply didn’t sit well with them.

Then the founder decided to do something odd. He charged money on top of the original monetization plan. Same product, same value proposition, but now there is a monthly subscription. Almost overnight, new businesses began signing up.

Today, that startup is worth billions.

This highlights a counterintuitive truth in strategy: In real-world markets, free or lower prices don’t always drive demand. Frequently, they achieve the opposite.

Higher prices amplify perceived value

The price-quality heuristic is a cornerstone of behavioral economics. When buyers lack complete transparency, they use price as a shortcut for quality. This is why identical items, from fine wines to electronics, are rated higher when they cost more. In B2B, this effect is amplified: A cybersecurity solution priced far below the market doesn’t look like a bargain; it looks like a risk.

Pricing dictates customer behavior and expectations

Low entry points tend to attract price-sensitive users who optimize for cost over outcomes. These cohorts are often more prone to churn and demand excessive support. Conversely, premium pricing attracts partners who value reliability and performance. Opting for higher pricing means going after clients with a different mindset. Even in strategic advisory, I see premium pricing as a filter for commitment.

Your price defines your competitive landscape

Pricing at the bottom floor frames the company within a commoditized segment where differentiation is minimal. Pricing at a premium forces a higher standard of depth, service and trust. Price defines who you are competing against and how you will be compared to them.

is a strategic adviser to tech companies and investors, specializing in strategy, growth and M&A, a guest contributor to Crunchbase News, and a seasoned lecturer. Learn more about his advisory services, lectures and courses at . for further insights and discussions.

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AI infrastructure also added four new unicorn companies focused on data center technology and provisioning. Fintech, including startups in wealth management, payment and digital assets, added four companies, while developer tools and defense each added three.

Twenty of March’s new unicorns are U.S.-based, including 11 from the San Francisco Bay Area. China added six companies in sectors ranging from robotics to AI and quantum computing.

From Europe, four new March unicorns are U.K.-based, while France, the Netherlands and Belgium each minted one. The UAE, Seychelles, India and Australia also each added one new unicorn to the board.

The most valuable unicorn newcomer last month was Seychelles-based crypto exchange , valued at $25 billion. The largest funding was a $1 billion round raised by AI pioneer ’s new frontier lab startup, Paris-based .

The board also saw a sizable cohort of very young companies earning their unicorn horns: 18 of the companies that joined the board last month were less than 3 years old. Five were not even a year old.

March’s new unicorns

AI-centric sectors by far led unicorn creation in March, with 14 of the 36 newcomers hailing from the robotics, foundational AI or AI infrastructure industries:

Robotics

• , a robotics for manufacturing company spun out by , raised a $500 million Series A led by and . The 1-year-old Palo Alto, California-based company was valued at $2 billion.
• Shenzhen-based , an intelligent sensor technology for robotics, raised a $145 million Series B led by , and . The 4-year-old company was valued at $1.5 billion.
• Beijing-based , a humanoid robotics company, raised $145 million in funding. The 2-year-old company was valued at $1.5 billion.
• , a humanoid robotics company for household tasks, raised a $165 million Series B led by . The 2-year-old Mountain View, California-based company was valued at $1.2 billion. The company plans to deploy robots to homes this year.
• Pudong, China-based , an intelligent layer for robotics in manufacturing, raised an $87 million Series D round. The 9-year-old company was valued at $1.2 billion.
• , a provider of simulated data for robotic intelligence, raised a $146 million Series A. The 3-year-old Santa Clara, California-based company was valued at $1 billion.

Foundational AI

• Paris-based raised a $1 billion seed round led by , ,, and . The less than 1-year-old company was founded by LeCun, ’s former AI lead, and is working to develop models for physical AI. It was valued at $4.5 billion in the round, which is Europe’s largest seed round on record.
• , a robot foundation model developer trained on internet scale video, raised a $450 million Series A led by . The 2-year-old Palo Alto, California-based company was valued at $1.7 billion.
• , a math foundation model developer for verified AI useful for coding and other applications, raised a $200 million Series A led by . The 1-year-old Palo Alto, California-based company was valued at $1.6 billion.
• Beijing-based , a text-to-video startup with its own AI model, raised a $300 million Series C led by . The 2-year-old company was valued at $1 billion.

AI infrastructure

• , a provider of networking hardware and software for data centers, raised a $500 million Series B led by and . The 2-year-old Santa Clara, California-based company was valued at $4.2 billion.
• , a chip cooling technology, raised a $143 million Series D led by . The 8-year-old San Jose, California-based company was valued at $1.6 billion.
• , which offers GPU rentals for startups, raised a Series A funding led by . The 2-year-old San Francisco-based company was valued at $1.5 billion.
• Redmond, Washington-based , a company building data centers in space, raised a $170 million Series A led by and . The 2-year-old company  was valued at $1.1 billion.  It launched its first satellite with a H100 in November 2025.

Financial services

• London-based , an AI-native platform for debt providers including banks, asset managers and advisory firms, raised a $170 million Series C led by . The 9-year-old company was valued at $1.3 billion.
• Mumbai-based , a wealth asset advisory firm for high-net-worth individuals and family offices, raised a $53 million private equity funding led by . The 4-year old, venture-backed asset manager was valued at $1.1 billion.
• Brussels-based , an investment group for digital assets, raised a Series C led by . The 8-year-old company was valued at $1.1 billion.
• Abu Dhabi-based , a payments infrastructure provider for regulated gaming markets, raised a $250 million funding led by . The less than 1-year-old company was valued at $1 billion.

Developer tools

• , which promises to make your app enterprise ready with authentication and other features, raised a $100 million Series C led by and. The 8-year-old San Francisco-based company was valued at $2 billion.
• , an observability platform for agentic AI, raised a $110 million Series B led by . The 3-year-old New York-based company was valued at $1 billion.
• , a software developer for hardware testing and development, raised an $80 million Series B led by . The 3-year-old Austin-based company was valued at $1 billion.

Defense

• , a drone technology company built for defense, raised a $110 million Series B led by . The 7-year-old Huntsville, Alabama-based company was valued at $1.2 billion.
• Sydney-based , provider of advanced navigation beyond GPS for military and industrial capabilities, raised a $112 million Series C led by . The 13-year-old company was valued at $1 billion.
• London-based , a builder of unmanned systems used in the Ukrainian war, raised a $50 million seed  funding led by and . The 1-year-old company was valued at $1 billion.

Biotechnology

• Austin-based , a biological AI research company spun out of  , raised a $10 million seed extension. The less than 1-year-old company was valued at $2 billion.
• , a neurotech company focused on brain computer interfaces, raised a $230 million Series C led by and  Lightspeed Venture Partners. The 5-year-old Alameda, California-based company, whose primary product, an implant to restore vision for those who suffer retinal disease, was valued at $1.5 billion.

Sales and marketing

• Amsterdam-based , a builder of agents for companies to deploy in customer service and business operations, raised a $150 million Series B led by . The 1-year-old company was valued at $2 billion.
• , an agentic layer that monitors customers and researches prospects, raised a Series B led by . The 2-year-old San Francisco-based company was valued at $1.2 billion.

Security

• , native AI security with its own human triage for customers, raised a $250 million Series B led by . The 1-year-old Sarasota, Florida-based company was valued at $1 billion.
• , which uses AI for offensive security, raised a $120 million Series C led by and . The 2-year-old Seattle-based company was valued at $1 billion.

Cryptocurrency

• Seychelles-based , a global cryptocurrency exchange platform, raised a $200 million corporate round led by , the parent company of the . The 12-year-old company was valued at $25 billion.

Telehealth

• Miami-based , ‘s telehealth provider for GLP-1 medications through employers, raised a $200 million Series A led by . The 5-year-old company was valued at $2 billion.

Professional services

• London-based , an AI notetaking startup, raised a $125 million Series C led by . The 3-year-old company was valued at $1.5 billion.

Consumer goods

• , a company with a mattress, thermal blanket and pillow designed to monitor and improve sleep, raised a $50 million Series D led by . The 11-year-old New York-based company was valued at $1.5 billion.

Accelerator

• London-based , an accelerator that sources founders from top schools, raised a $200 million Series D. The 11-year-old company, which hosts its latest cohorts in Silicon Valley, was valued at $1.3 billion.

Quantum computing

• Sichuan, China-based , a quantum computer and chip-production company, raised a $145 million Series B. The 5-year-old company was valued at $1 billion.

Autonomous driving

• Hangzhou-based , an intelligent driving platform, raised a Series A led by , and . The less than 1-year-old company was valued at $1 billion.

Related Crunchbase unicorn lists:

• (1,739)
• (609)
• (101)
• (188)
• (117)
• (102)
• (896)
• (510)
• (236)
• (38)
• (472)

Related reading:

• This Is A Momentous Year For Early-Stage Unicorns
• The Rising Investors Behind The New Unicorn Class
• While OpenAI Shattered Records, Robotics and Semiconductor Startups Quietly Added The Most New Unicorns In February

Methodology

The Crunchbase Unicorn Board is a curated list that includes private unicorn companies with post-money valuations of $1 billion or more and is based on Crunchbase data. New companies are as they reach the $1 billion valuation mark as part of a funding round.

The unicorn board does not reflect internal company valuations — such as those set via a 409a process for employee stock options — as these differ from, and are more likely to be lower than, a priced funding round. We also do not adjust valuations based on investor writedowns, which change quarterly, as different investors will not value the same company consistently within the same quarter.

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

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

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

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

Transportation and biotech were leading themes among this week’s largest U.S. funding recipients. This includes the week’s largest round, a $650 million financing for electric pickup truck maker . Other sizable investments went to spaces including drug development, autonomous public transit and software engineering.

1. , $650M, electric vehicles: Troy, Michigan-based Slate Auto, a developer of lower-cost electric pickup trucks that can be customized as SUVs, raised $650 million in Series C funding led by . The -backed company said it plans to deliver its first vehicles to customers later this year.

2. , $300M, biotech: Beeline Medicines, a Boston-based developer of precision therapies for autoimmune and inflammatory diseases, emerged from stealth with $300 million in Series A funding led by . The company’s initial portfolio includes five programs licensed from .

3. , $170M, autonomous transportation: Glydways, a developer of personal autonomous pods designed to operate on dedicated lanes, closed on $170 million in Series C funding. , ACS Group�����Ի� led the financing for the San Francisco-based company, which is launching operational pilots in three cities this year.

4. , $150M, AI software development: Factory, a startup focused on bringing autonomy to software engineering, secured $150 million in a Series C round led by . The financing set a $1.5 billion valuation for the 3-year-old, San Francisco-based company.

5. , $108M, biotech: South San Francisco, California-based Terremoto Biosciences, a developer of small molecule medicines for cancer and rare diseases, raised $108 million in Series C funding from backers including , , and .

6. (tied) , $100M, student transportation: Zum, a provider of a platform for optimizing K-12 student transportation, secured $100 million in new funding from . Founded in 2015, Redwood City, California-based Zum has raised about $500 million in known funding to date, per .

6. (tied) , $100M, biotech: Neomorph, a developer of cancer therapeutics, closed on $100 million in Series B funding to support clinical trials. led the financing for the San Diego-based company.

6. (tied) , $100M, fintech: San Francisco-based Slash, a business banking platform, picked up $100 million in a Series C round led by , and . The financing set a $1.4 billion valuation for the company, which said it surpassed $250 million in annualized revenue in 2025.

9. , $80M, semiconductors: nEye, a developer of integrated optical interconnects for data center connectivity, raised $80 million in Series C financing led by . Founded in 2020, Silicon Valley-based nEye has raised $152 million in funding to date.

10. , $75M, space tech: Irvine, California-based Turion Space, a provider of an orbital intelligence and operations platform, over $75 million in a Series B round led by .

Methodology

We tracked the largest announced rounds in the Crunchbase database that were raised by U.S.-based companies for the period of April 11-17. Although most announced rounds are represented in the database, there could be a small time lag as some rounds are reported late in the week.

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