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.

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’s 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’s 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 �������� 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 “computer-use” models designed to interact directly with software. Its approach — training on large-scale video data rather than manually annotated screenshots — 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’s 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 �������� 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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The raise brings the Swedish company’s recent Series D funding round total to $600 million. At the time of the first close in March, Legora was valued at $5.5 billion.

, and also participated in the extension, according to CNBC.

The valuation was a big jump from the $1.8 billion Legora achieved just last October, when it raised The company has now raised a total of $866 million since being founded in 2023 by , and .

Nvidia has been an active startup investor, backing over three dozen companies so far in 2026, according to �������� data. The chip giant has a stake in several of the most valuable AI companies, including , , and . It also has a number of power-generation-related investments sprinkled in, indicating ongoing concern and interest in how we are going to feed all those power-hungry AI bots.

Record legal tech funding

Meanwhile, venture funding for legal tech startups reached a record high in 2025, driven by investor enthusiasm for AI’s potential to automate the legal profession. Per �������� , companies in the legal and legal technology sectors raised $4.08 billion in seed- through growth-stage funding in 2025. That’s an impressive 77.4% increase from the $2.3 billion raised by legal tech startups in 2024.

So far this year, legal tech startups have already raised more than $1.3 billion, .

Other startups in the industry that have closed on sizable fundings over the past year include:

• : A provider of legal practice management software, Filevine announced in September that it had closed on two previously undisclosed rounds totaling $400 million. led the first round and, interestingly, joined and to co-lead the second.
• : San Francisco-based Harvey, a provider of AI tools for legal professionals, closed on four separate funding rounds in 2025, including two rounds of $300 million each. To date, the 3-year-old company has raised more than $1 billion.
• : Toronto-based Blue J, developer of a GenAI tax research platform that counts legal professionals among its core users, raised $122 million in an August Series D financing led by and .
• : Palo Alto, California-based Eudia, which develops an intelligence platform for Fortune 500 legal teams, landed up to $105 million in a Series A financing led by .

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• Swedish Legal Tech Startup Legora Triples Valuation To $5.55B With $550M Series D Led By Accel
• Legal Tech Investment Hits All-Time High With Filevine Funding

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This phenomenon has been on the rise over the past couple years, driven by voracious investor appetite for AI early movers. Since 2024, an estimated 207 AI-focused companies have joined The �������� Unicorn Board. That’s roughly half of all companies that first hit valuations of $1 billion or more during this period.

Of those, more than a third first secured 10-figure valuations at seed or early stage. That includes some of the most well-known newish unicorns in sectors like foundational AI, robotics and vertical AI.

Many newish unicorns are worth a lot more than $1 billion

While a $1 billion valuation is the threshold for claiming unicorn status, many newer entrants to the group are now worth much more than that.

Per �������� data, at least 45 companies that became unicorns in the past 28 months are now valued at $5 billion or more. That’s just over 10% of the total cohort.

So who’s at the top? To answer that question, we put together a sample list of 18 high-profile, newish unicorns with a most recent post-money valuation of $5 billion or more.

Notably, many of these are very young companies. U.K.-based AI infrastructure startup , for instance, launched from stealth just a year ago as a spin-out of crypto mining firm . It recently secured a $14.6 billion post-money valuation.

, a developer of AI-enabled software to control robots, has also scaled up quickly since its inception in 2024. This year, the San Francisco company is reportedly to raise fresh funding at a valuation exceeding $11 billion.

Foundational AI startup , meanwhile, has raised around $3 billion in less than two years since its founding. A round last spring set a $32 billion valuation for the Palo Alto, California-based company.

Newer unicorns are also fundraising at a fast clip

In addition to their youth and ultra-high valuations, many newer unicorns also stand out for the speed and magnitude of their fundraising.

San Francisco-based AI legal tech platform , for instance, has gone from Series A to Series G in about three years and raised close to $1.2 billion along the way.

Predictions marketplaces and are remarkably fast fundraisers as well. New York’s Kalshi has gone from Series C to Series E in the past year, pulling in over $2.4 billion. And Polymarket, another New York-based company  has scooped up close to $2.9 billion in the past two years.

Foundational AI is also scaling superfast. Medical AI company went from Series A to Series D in less than a year, with the Cambridge, Massachusetts-based company picking up over $700 million from early 2025 to early 2026. , the developer of AI coding tool Cursor, went from Series A to Series D in under a year, securing over $3.2 billion in that time frame. The San Francisco-based company most recently entered an agreement with , giving the latter Cursor for $60 billion.

Move fast and build things

These are of course remarkable times for mega fundraising rounds, particularly around AI. Cynics might question valuations and check sizes, while optimists might quickly point out that we are in the early days of building foundational technologies of the modern era.

I suppose both have a point. For now, we’re less inclined to pick winners and more engaged in simply keeping score. One thing is clear: It’s a very well-capitalized playing field.

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Austin-based Dreambase has developed AI-native data agents to do the analytical work that data teams have historically done, according to CEO and co-founder .

After a decade in the Austin tech scene as a “first product hire” working alongside early-stage founders, Keil spent three years as head of product at . By August 2024, he had teamed up with to launch Dreambase. After months of prototyping and proving concepts, the company started offering early access in April 2025.

The startup describes itself as -native and not just Supabase-compatible. Supabase is the developer of an open-source relational database for AI app development that competes with ’s database.

Dreambase users can connect their Supabase database and get a dashboard “in seconds,” according to Keil.

“Our AI data agents handle the rest,” he told �������� News. “They build dashboards, run analysis and surface insights 24/7. Whether you’re a solo founder shipping your first product or an enterprise AI innovation team running mission-critical analytics, you get a full virtual data team without the headcount.”

Interestingly, Supabase’s team was so impressed with Dreambase’s products, three of its executives participated in its funding round, including its CFO, CTO and COO. 1 led the raise, which also included participation from , , , , and . Angel investors from companies including , and QuotaPath also participated.

‘The analytics layer’ for every Postgres company

While Dreambase’s technology is “Postgres native” — meaning it functions with any Postgres database — the company saw a massive opportunity within Supabase’s community of 7 million developers.

For the unacquainted, (often just called “Postgres”) is a popular open-source relational database where a company stores all its most important data such as user profiles, transaction histories, app settings and product logs.

Keil is ambitious about Dreambase’s potential to help companies at any stage move faster.

“We plan to be the analytics layer for every company running on Postgres in the world,” he said.

Historically, companies have waited until later stages to hire a data team. But Dreambase says its value proposition is that it goes straight to the database. By providing a “context layer” to LLMs, it allows anyone to ask product questions in natural language.

“Our AI data agents aren’t a chatbot wrapped around a chart. … Your Supabase database is the source of truth, and the experience is fast and intuitive whether you’re a founder, engineer, operator or analyst,” Keil said.

Currently a five-person team, Dreambase aims to double its headcount over the next few months by hiring across engineering and enterprise go-to-market.

A ‘fundamentally different starting point’

Felicis General Partner said her firm was impressed with the fact that Dreambase’s founding team had “lived the problem” the company is trying to solve “from both sides” — Keil as head of product at QuotaPath and Ledbetter leading design at , and .

“They’ve watched the same broken sequence play out for years: someone asks a simple question about the product, and the answer takes weeks. What’s different now is that AI can finally do the work a data team used to do, and the Supabase platform they’re building on is 7 million+ developers and accelerating,” she wrote via email.

Supabase CFO said he invested as an angel into Dreambase because he believes the company “will win the analytics layer for the next generation of Postgres-native companies.”

“Most analytics tools treat Postgres as just another data source to extract from. Dreambase treats it as home,” he wrote via email. “That’s a fundamentally different starting point, and it shows up everywhere in the product, from how fast teams get to their first dashboard to how the AI agents reason about real Supabase schemas. The Postgres ecosystem has been waiting for this analytics layer, and Dreambase is the team building it.

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She began on the consumer side at early-stage companies including and pioneered the early push of CPG e-commerce at long before the acquisition. After a pivot into tech M&A at and a partnership at GGV Capital (now ), she joined NEA roughly three years ago.

Today, Luck’s thesis centers on the AI application layer, betting on vertical AI and the “last mile” of automation to bridge the gap between horizontal model potential and tangible enterprise ROI.

We recently spoke with Luck about the increasing relevance of vertical AI, how startups can carve out durable advantages in a world dominated by platform giants and more.

The interview has been edited for brevity and clarity.

�������� News: You’ve seen the evolution of commerce from the early days of Amazon Fresh to the current AI boom. How does that background influence how you view the “friction” of AI adoption today?

Luck: I see incredible parallels. At Amazon, I spent my days convincing CPG manufacturers that e-commerce was the inevitable future. Back then, there was immense friction — technological, logistical and mental. Today, 500 companies are in a similar spot with AI.

While the potential is obvious, most organizations are still struggling to integrate it into their daily workflows. We are moving from a world where AI is a “shiny object” to one where it must solve a mechanical problem, but getting there requires overcoming that initial resistance.

You’ve talked about the “ question” — the fear that frontier models will eventually swallow the application layer. How can vertical startups build a durable defense?

It’s the primary concern for founders right now. Most horizontal tools, like Claude, currently act as research co-pilots. They are excellent at taking a user from 0% to 80%, but they don’t handle the “last mile.” For 99% of people, AI isn’t yet running in the background while their hands are off the keyboard.

Moats are being built by solving the specific hardships of that last mile. Take financial planning and analysis: You can plug data into a general model and ask questions, but the model won’t automatically re-forecast, flag specific trade-offs between burn rate and growth, or create a unified data layer across disparate sources.

Startups that build these purpose-built product flywheels — and use forward-deployed engineers to sit alongside users and identify workflow holes — build a moat that general models can’t easily replicate through scale alone.

Why is owning the end-to-end workflow becoming more valuable than the underlying model differentiation?

Because it removes the mental friction of “What do I do with this?” If a company can deliver a finished work product — an artifact — the ROI is undeniable.

Our portfolio company does this for legal due diligence. Another, , does this for equity research reports. When the output is a discrete document that looks exactly like (or better than) what a team of analysts would produce, the enterprise doesn’t care which model is under the hood. They care about the hours saved and the accuracy of the result.

You mentioned the idea of the “operating system” changing. How should startups think about partnering versus competing with platforms like Claude or ?

We haven’t truly seen our way of working change yet; we’re still using the same UIs. But I expect a shift in which a model becomes your de facto operating system — a command center from which you “call” other specialized applications.

Think back to five years ago, when startups used as their primary interface. You might see a future where a specialized tool like Samaya is integrated directly into a horizontal model’s UI.

The specialized knowledge graph and proprietary data remain with the startup, but execution occurs within the user’s primary “operating system.” Interoperability will be the next big frontier at the application layer.

In regulated industries, what is the “make or break” factor for an enterprise buyer right now?

It’s a mix of accuracy, auditability and cybersecurity. Enterprises are terrified of “data provenance” issues — they need to be able to audit the trail of every number.

I’m closely following (Artificial Intelligence Underwriting Co.). They are essentially building a “Moody’s for AI agents.” They’ve assembled a group of over 100 CISOs to create a for-profit certification standard. If a company like or can certify its agents against this standard, it gives the enterprise a layer of trust that a standard SOC 2 just doesn’t cover yet.

With AI-fueled hackers creating new attack vectors, this kind of authentication is becoming a necessity.

What does the “next frontier” look like for you as an investor?

We are in the “pre-mobile-native” era. We’ve moved the web to the phone, but we haven’t seen the apps that only AI can enable. I’m waiting for the “ moment” — the transition from a co-pilot, where you’re still “driving,” to a truly autonomous, agentic workflow. Whether it’s through voice-first interfaces or agent-to-agent interaction, the next 12 months will likely reveal the first truly novel ways of working that feel fundamentally different from the laptop-and-keyboard era.

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

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We’re not talking about confidential filings either. Sure, they signal serious intent and contain valuable information for regulators. But for the rest of us, it’s the public S-1 filing that signifies an IPO is actually imminent.

By this latter measure, the past few weeks have been pretty busy for venture-backed startups. , the designer of speedy AI inference chips, filed publicly last week for an offering expected to raise around $2 billion. The Silicon Valley company, which withdrew plans for an IPO last fall, is reportedly seeking a valuation upwards of $35 billion this time around.

That alone would be enough to set IPO market watchers abuzz. Per �������� data, it stands to be the largest initial share offering of a U.S. semiconductor company to date.

However, Cerebras wasn’t the only venture-backed company seeking a multibillion-dollar IPO valuation.

Power players

Another, albeit smaller, contender is nuclear power startup , which is making its debut today. The Rockville, Maryland-based company priced shares at $23 each late Thursday, above the projected range, raising around $1 billion. Shares closed up 27% in first-day trading Friday.

Meanwhile, on the geothermal power front, is also looking to take its clean energy ambitions to the public market. The Houston-based company filed last week for a offering that could bring in around $250 million.

Biotech IPOs heating up

Biotech is also heating up. Last week delivered a big debut from , a Waltham, Massachusetts-based developer of oral and injectable treatments for obesity and metabolic disease that $718 million in its Nasdaq offering. , a Fremont, California-based startup applying proteomics to early disease detection, made its market entry as well, securing a current market cap around $1.6 billion.

More biotech debuts are on deck too. Austin-based , a venture-backed developer of a nerve stimulation device for stroke survivors, filed last week for an offering. The prior week brought S-1 filings from Boston’s , a developer of medicines for depression, anxiety and other neuropsychiatric disorders, and , a Denmark-based biotech which focuses on treatment of blood coagulation disorders.

Space and defense on the rise

Of course, everyone knows the Texas-based company on deck to publicly file for a space tech offering of unprecedented magnitude. for an IPO a few weeks ago, with media reports pegging its target valuation around $1.75 trillion. If the company forges ahead with reported plans for a June market debut, a public filing should follow in the next few weeks.

In the interim, another, much, much smaller offering in the defense tech space is on track to hit the market much sooner. , a Herndon, Virginia-based developer of radio frequency intelligence for military customers, filed earlier this month for a offering. It comes amid a period of heightened investor appetite for defense tech, with an expectation of more debuts in the space likely in coming months.

Now we just need some software

Of course, it’s not an IPO market that is welcoming to all venture-backed startup sectors. One area noticeably absent from the impending offering list is enterprise software. While SaaS has long been a mainstay of the IPO pipeline, the sector has taken a hit of late amid investors’ concerns of AI disruption.

That said, it’s still encouraging to see a swathe of other sectors dipping a toe in IPO waters.

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On the positive side, EVs are gaining ground. In 2025, sales increased by more than 20% year on year, rising to 21 million units, per .

On the other hand, early EV optimists assumed we’d be much further along by now. And while sales are up, the is slowing, driven by affordability constraints, trade friction and shifting government incentives.

The broad trend: Funding to EV-related startups reflects a similar mix of optimism and restraint. Investors are backing big rounds for a handful of upstart brands like customizable pickup truck maker and micromobility spin-out . Yet funding remains far below prior peaks and exit activity appears muted.

The numbers: Companies in ��������’s electric vehicle category are on track to see higher investment this year relative to last. Around $3.6 billion has gone to companies in the space so far in 2026, spread across about 50 rounds.

However, we’re still nowhere near the 2021 cyclical peak, when nearly $19 billion went to global EV startups. For perspective, we charted investment and deal count since 2020 below.

Noteworthy deals

The largest round tied to the EV space this year went to , which isn’t an electric vehicle brand but rather a developer of autonomous driving technology that has been tested on EVs. The London-based company raised $1.2 billion in a February financing at an $8.6 billion valuation.

Another standout fundraiser was Troy, Michigan-based Slate Auto, a developer of lower-cost electric pickup trucks that can be customized as SUVs. The -backed company raised $650 million in Series C funding last week and says it plans to deliver its first vehicles to customers later this year.

The Rivian spin-out Also, focused on electric bikes and skinny four-wheeled models capable of carrying cargo, is also scaling up, securing $200 million in Series C funding in March. The startup also plans to partner with to develop autonomous delivery vehicles.

China-based startups are also scaling up. , a developer of autonomous electric trucks,  secured $310 million early this year, while , the flying car subsidiary of EV brand , picked up $200 million in fresh financing.

Exits

While private funding still flows to EV-related startups, exit activity has been comparatively slow.

On the IPO front, Chinese EV car brand made its Hong Kong debut last month. And India-based electric scooter and charging provider went public last spring.

U.S. startups, however, have been sitting out the IPO market in recent quarters, with the exception of a $9 million micro- early this year from solar electric vehicle brand .

As for M&A, we haven’t seen sizable disclosed-price purchases of private, venture-backed EV companies in recent quarters, per �������� data. Another deal in the wings, meanwhile, is a planned SPAC merger transaction involving Swedish autonomous electric freight shipping startup .

Outlook

The EV funding environment, neither especially weak nor particularly robust, contrasts sharply with the investment climate for autonomous driving startups, which hit a record amount this year. Perhaps, over time, we’ll see some momentum spilling over to EVs, as you can’t have autonomous vehicles technology become widespread without somebody supplying the actual vehicles.

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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.

�������� 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.

�������� 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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Look closer, and the story changes completely. Early-stage funding was up 41% year over year. AI/ML deal count , up from roughly 5,600 the year before. More companies are getting funded at the early stage, not fewer.  The concentration at the top? That’s an infrastructure play. The application layer looks entirely different.

Build vertical, not horizontal

The real signal is in the shift from horizontal to vertical. shows horizontal SaaS down 35% over the past 12 months while vertical SaaS is essentially flat (up 3%). That divergence matters for founders deciding what to build.

Horizontal software (project management, general productivity, collaboration) is commoditizing fast as AI agents handle coordination natively. But vertical software? That’s where proprietary data shines and industry-specific compliance workflows matter. AI makes the first category less valuable and the second category more valuable.

If you’re starting a company right now, the data says: Pick an industry, not a feature. Claims processing in insurance, scheduling in healthcare, compliance in financial services, job costing in construction. These are workflows where software penetration has been shallow for decades because the problems were too specific for horizontal tools. AI changes that math.

Build for the $6T, not the $500B

The addressable market for software is expanding, not contracting. In Redpoint’s CIO survey, 58% cite AI as the top driver of increased software spend. As agents move from copilot features into autonomous workflow execution, the addressable market grows from roughly $0.5 trillion in current U.S. enterprise software spend toward $6 trillion or more, because AI starts capturing portions of the knowledge-worker payroll that software never could.

This is classic : When a resource gets dramatically cheaper to produce, consumption goes up. AI makes software dramatically cheaper to build, deploy and maintain. Suddenly, job costing for midsize contractors pencils out. Inventory optimization for independent pharmacies becomes economically viable. The cottage industries that enterprise software ignored for decades? They’re all in play now.

Build for acquirability, not just IPO optionality

But let’s talk about exits, because that’s where the rubber meets the road. The IPO market remains largely closed. In 2025, roughly 2,300 VC-backed startups were acquired compared to just 65 IPOs, per �������� data.

LPs have seen nearly $200 billion in cumulative negative net cash flows since 2022. The pressure to return capital through M&A is real and growing.

Smart founders are building for this reality from day one. They’re building products that integrate into existing enterprise stacks, accumulating proprietary data that makes them expensive to replicate and cheap to integrate. Strategic acquirers in insurance, healthcare, logistics and financial services are actively buying vertical software companies. Why? Because these buyers can’t build this stuff internally — they lack the talent, the focus, and frankly, the DNA.

Start with the workflow, not the technology

So while everyone’s mesmerized by the infrastructure megarounds, the real opportunity is staring us in the face. Pick a specific industry workflow that’s still manual or stitched together with Excel. Build the AI-native solution that actually works for that vertical. Get to revenue before the market catches up.

The record quarter and the shrinking fund base are telling the same story from different angles. Infrastructure capital is concentrating at the top while the application layer is wide open for those willing to roll up their sleeves and solve real problems for real industries. That’s where I’m putting capital, and that’s where smart founders should focus their energy.

As the co-founder and managing partner of , is committed to establishing MGV as the premier venture firm for world-class tech entrepreneurs to accelerate their visions. Under Schröder’s stewardship, MGV has swiftly ascended to a top-quartile firm, surpassing the performance of 95% of venture funds. The performance of MGV is driven by Schröder’s unique approach to venture investing — that providing intensive sales training, devising robust fundraising strategies and securing follow-on investments is the best way to support founders and drive the deepest return for investors. has recognized him as one of the Top 100 global seed investors, and his perspectives are published regularly in �������� News and other leading publications.

Related reading:

• These 3 Charts Show How Venture Capital Has Concentrated At The Top In 2026
• Q1 2026 Shatters Venture Funding Records As AI Boom Pushes Startup Investment To $300B

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