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.

Defense tech unicorn led the fundraising lineup in a week heavy with rounds for companies focused on applications in the physical world. Anduril’s $5 billion financing was by far the biggest. Other large rounds went to companies focused on supplying data power, robotics, space tech, biotech, and even strawberries.

1.��, $5B, defense tech: Defense tech unicorn Anduril Industries raised another $5 billion in funding at a $61 billion valuation — double the valuation of $30.5 billion it received less than a year ago. The Series H round, led by and , brings the Costa Mesa, California-based company’s total raised to date to $11.4 billion, .����

2.��, $775M, energy: Houston-based VoltaGrid, a provider of mobile natural gas generators for data centers, microgrids and industrial applications, secured $1 billion in strategic investment from and . The investment includes $775 million in capital funding and a $225 million secondary purchase from existing investors.

3.��, $400M, robotics: Palo Alto, California-based Mind Robotics, developer of an AI-enabled industrial robotics platform, picked up $400 million in new financing led by . The round brings total funding to date to more than $1 billion for the startup, which launched in 2025 as a spinout of .

4.��, $275M, space tech: Cowboy Space, a developer of rockets and satellite infrastructure to power and run AI compute in space, closed on $275 million in Series B funding at a $2 billion valuation. led the financing for the San Carlos, California-based startup, which was founded by co-founder .��

5.��, $150M, indoor farming: Oishii, operator of highly automated indoor farms for growing strawberries, raised $150 million in Series C funding led by . Founded in 2016, the Jersey City, New Jersey-headquartered startup has raised $370 million in total funding to date.

6.��, $125M, cybersecurity: San Jose-based Exaforce, developer of an AI-native security operations platform, secured $125 million in Series B funding from backers including , , , �����Ի��� .

7.��, $122M, biotech: Create Medicines, a Cambridge, Massachusetts-based startup focused on in vivo immunotherapies for autoimmune diseases and cancer, closed on $122 million in Series B funding. , , and led the financing.

8.��, $100M, autonomy: Providence, Rhode Island-based HavocAI, a provider of tools for developing military and commercial-grade autonomous systems across sea, air and land, secured $100 million in Series A funding. The round brings total funding to date for the 2-year-old company to $200 million.

9.��, $65M, space tech: Star Catcher, a startup that says it is building the first power grid in space by beaming concentrated solar energy on demand to satellites, picked up $65 million in Series A funding. , and led the financing for the Jacksonville, Florida-based company, which was founded less than two years ago.

10.��, $64M, data center power: GridCare, developer of technology to more efficiently provide power to AI data centers, raised $64 million in Series A funding. led the financing for the Redwood City, California-based startup.��

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• Anduril Raises Another $5B As Defense Tech Startups Shatter Funding Records��

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The energy sector necessary for AI compute also garnered significant funding this year.��

All told, roughly half of European venture funding in 2026 to date has been in AI-related companies, �������� data shows.

The uptick in artificial intelligence investment has coincided with an overall gain in startup funding in the region the last past quarters. Funding was up a third year over year in Q4 and Q1, reaching more than $17 billion each quarter.��

AI talent hubs

One area where Europe is seeing momentum is with frontier labs.

Employees from — the original AI lab established in London in 2010 and acquired by Google in 2014 —��have spawned two new labs in London: and . And , previously Meta AI’s lead, formed in Paris. Just this year, the three companies have altogether raised $2.6 billion.��

Last year, German-based AI lab raised hundreds of million in funding. One of the earlier model companies from Europe, , founded in 2023, has raised $4 billion in total.��

Europe is also home to one of the early diffusion model companies, . from Heidelberg, Germany, recently merged with Canada-based in April for sovereign and commercial AI deployments, valuing the merged entity at $20 billion, creating a transatlantic competitor to U.S. model companies.��

The recent spate of new AI lab formation and renewed momentum on the funding front could be a driver for talent hubs to concentrate in Europe. Still, although foundation labs in Europe have raised more than , that represents a tiny percentage of the amount raised by frontier model companies in the U.S.

AI-native

In the European report, found 81% early-stage companies, largely pre Series A, are AI-native — up from 50% a year ago. Leading by company count this year were 12 companies in dev tools and infrastructure and 11 companies in industrials and robotics.��

The advantages of building in Europe are “access to strong engineers in the very beginning — having people that want to build and be part of a founding business, and access to good quality talent that you can retain,” said , a principal at Notion Capital who co-wrote the report.��

He also noted that in earlier vintages, the trend was to “build a company, expand to the U.S. at some point around the Series B. Now, from the start, founders tend to think globally from day one.”

The single most dramatic change, however, is how much leaner teams are ahead of the Series A, he said.

US bound

Despite the more recent pickup, European funding growth has lagged behind the U.S. since 2024.��

The leading San Francisco-based model companies — and — have raised $254 billion since 2023 and recentered the Bay Area post-pandemic as the place to be for ambitious founders.��

“The companies that start in the UK, France, Germany, and the Nordics, then come to Silicon Valley to grow,” said , managing partner at , speaking on current market trends.��

“You can build an amazing business anywhere in the world now. The barrier to building greatness has shrunk,” said McLoughlin, who himself relocated to�� San Francisco from the UK in 2010. “But, the chances of building a generational company are so much higher, if you come to the Bay Area.”

UK-founded incubator (EF) relocated to the U.S. in 2024. EF sources founders�� from leading universities around the globe to start companies but incorporates each business it funded in the U.S.��

“The Bay Area program is not just about proximity to capital,” said , CEO and co-founder on announcing EF’s recent fund raise. “It changes the ambition gradient. Founders move faster, think bigger and compete on a global stage from day one.”

“I’m seeing more than ever, companies that started in these emerging markets, and then going to the U.S. very early in their journey — not to sell themselves, but to sell to customers,” said , general partner at global investment firm . The firm invests on a global basis day zero at pre-seed, with its Elevate fund investing at later stages.��

“The time to copy a business is a month or two months, as opposed to years,” said Abdel-Nour,�� “You have an incentive to go and capture these big markets before your U.S. competition has really reached escape velocity,” he said.��

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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.

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

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

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

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

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

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

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

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

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

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

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

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

�������� News recently conducted an email interview with , managing director of , about the firm’s investment thesis, the kinds of startups it aims to back, and how it works with founders to build and scale projects in the American Express ecosystem.��

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

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

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

The interview has been edited for brevity and clarity.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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Starting a company has never cost less. A founder with the right AI tools can ship a working product in a weekend, stand up a website in an afternoon, and fill out an accelerator application before lunch. But that speed hasn’t made it easier to get funded.��

Fewer seed-funded startups are graduating to Series A than just a few years ago, and startup funding has been in a downturn so far in 2026. Investors are concentrating capital in fewer, stronger bets. The question is what “stronger” means now.

Every generation of technology resets what investors should expect from founders. Twenty years ago, a founder who wasn’t internet-native was at a structural disadvantage. Forty years ago, it was computer literacy. Today, AI-native fluency is the baseline — the ability to build, test, and iterate using AI copilots, APIs, and low-code tools at a speed that would have required a full engineering team just a few years ago.��

Founders who haven’t embraced these tools in their daily operations aren’t even at the table. They’re new-aged dinosaurs. Technical expertise still matters, but when everyone can build, thanks to AI, it no longer differentiates. And that forces a harder question for investors: If the product isn’t the moat, what is?

Finding the fit

The answer is founder-market fit. Investors are shifting their attention from what a team can build to whether the founder has domain expertise that predates the startup, has done real customer discovery, and can articulate a path to market that competitors can’t easily replicate.

AI can help a founder build anything, but it’s what customers have a need for that tells them what’s worth building. That judgment is steeped in industry knowledge, customer relationships, and a clear-eyed view of what people will actually pay for. That is the scarce resource these days.

That’s not to say AI can’t help build a company the right way. It has implications for how early teams should be composed., the average seed-stage company last year had just over six employees, down from more than 10 in 2021.��

With teams that lean, every hire has to pull disproportionate weight. The highest-leverage early additions are a product-minded builder who can ship fast with AI tools, someone who owns the customer relationship and drives early revenue, and someone who can position the product and generate demand. A bench of engineers no longer tops the list.

The investor’s harder job

Knowing what to look for is one thing. Finding it is another, because AI has made it easier to fake the signals investors rely on.��

There’s an entrepreneurial equivalent to the that so many people are talking about. Instead of a tidal wave of empty marketing copy about “ever-evolving landscapes,” there’s startup slop that creates a serious evaluation problem for investors. Dealflow volume has become a vanity metric. There’s a surge of submissions that are pure noise, especially from software startups that can fabricate credibility in a single afternoon.

Deep tech is harder to fake. Building a therapeutics company still requires real science, real key opinion leaders, and real partnerships. The same is true for hardware and advanced manufacturing. There’s an actual moat in those sectors, which may help explain why investor interest in deep tech has been growing steadily.��

Investors can weed out the startup slop by asking more specific questions. For instance, our accelerator, AlphaLab, is based in Pittsburgh, and we always ask founders why this city is the right place for them to grow their businesses. You can sense how genuine someone is based on their answer. Same goes for asking about the customer discovery process. Even more telling is why someone started their company in the first place, whether the answer reflects real conviction or a market opportunity they read about.��

AI can’t manufacture what investors are really looking for. The signals that matter most at the early stage are coachability, hustle, and genuine conviction. There are details in an application that suggest someone has actually lived the problem they’re solving. Investors don’t want to write a check to someone who has vibe-coded a company they aren’t passionate about, and the tells are easier to spot than founders think.��

However, AI has reallocated where founders should spend their energy. Because it can help with some of the technical aspects of creating a company, founders should devote more effort to refining their strategy through higher-order skills like judgment, creativity, storytelling, and relationship-building. Speed of communication has become a revealing signal. There is no longer any excuse for taking four days to respond to an email, skipping a weekly investor update, or failing to follow up after a meeting. AI has eliminated the friction in all of those tasks. A founder who is still slow is telling investors something about how they’ll run a company, and investors are paying attention to those soft interactions more than ever.

While the cost of building companies has dropped, the burden of earning investment has risen. And for investors, the evaluation itself has gotten harder, with more noise, more polish, and fewer of the old signals to rely on. The founders worth funding will stand out the same way they always have: by knowing something the rest of the market doesn’t.

��brings 20 years of experience in venture capital, accelerator leadership and strategic operations to his role as director of accelerator programs at����in Pittsburgh. He oversees��, AlphaLab Gear, AlphaLab Health and Robotics Factory Accelerate, programs that support early-stage startups with mentorship, resources and capital. His leadership has helped create a connected AlphaLab ecosystem that empowers founders across industries and stages of growth. Earlier in his career, Tainter held roles at�������Ի�����where he led cross-functional initiatives and evaluated early-stage investments. He also teaches at��, where his work focuses on funding entrepreneurial ventures.

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Cambridge, Massachusetts-based Blitzy has now raised more than $204.4 million. led its latest financing. New investors including , and also participated, as did existing backers such as and . The company said it also received strategic investments from , and .��

Blitzy claims that its platform autonomously completes months of software development, including automated testing and quality validation. It further claims to increase engineering velocity by 5x “for some of the world’s largest enterprises.”��

While Blitzy did not reveal hard revenue figures, it said that its technology has been adopted by “dozens” of Global 2000 enterprises across 10 industries, including State Street and QAD. The company says it was built on the premise that frontier models alone would not solve enterprise software development.

“We believed that delivering production-ready code for the enterprise would come from fusing hyperscaled agent orchestration and a system that deeply understands the legacy codebases it is working within,” , co-founder and CEO of Blitzy, said in a press release.

Elliott, who also previously founded and is a former Army Ranger, started Blitzy with alum in 2023. Pardeshi holds more than 27 patents related to neural networks, image generation and AI-driven interface translation.

Big money for AI software development

Several other companies in the AI software development space have raised large rounds over the past year. They include:

• , which sells the popular AI coding assistant Cursor. The company has raised $3.4 billion and was most recently valued at over $29 billion. The company has since with that gives the -led space exploration company the right to buy Anysphere for $60 billion later this year.
• , a cloud-based development platform, has raised more than $870 million, including a March that valued the company at $9 billion.��
• , a Swedish AI vibe coding startup, has raised more than $550 million, including a December $330 million Series B financing at a $6.6 billion valuation.

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American companies raised just around $13 billion in seed- through later- and growth-stage funding so far this month, per �������� . Unless momentum suddenly picks up, that puts March on track to deliver just a fraction of investment tallies from either of the prior two months, as charted below.

Slowdown more pronounced at late stage

The slowdown is almost entirely due to fewer giant AI megarounds closing this month.��

Given that, there’s a case to be made against reading too much into the topline numbers. After all, most of February’s huge tally came from a single round — ’s record-setting $110 billion fundraise — that happened to be announced on the second-to-last day of the month.��

A couple weeks before that, secured a $30 billion financing. Also in early February, robotaxi pioneer picked up $16 billion in fresh late-stage funding.

Early- and seed-stage dealmaking in March, by comparison, is on track to come in close to the prior two months’ levels, as charted below.

Iran War and US investor jitters��

The March startup funding slowdown also coincides with the Iran War, which commenced on Feb. 28. Broad stock indexes have fallen in tandem in subsequent weeks, although Monday did bring a much-awaited partial rebound.

Notably, this month’s funding deceleration is mostly a U.S. phenomenon. European startup funding, by contrast, actually hit its highest point of the year in March, boosted by megarounds for AI infrastructure unicorn and artificial intelligence startup .

February may be one for the record books

While there are plenty of potential catalysts that could drive funding higher in coming weeks, both economic and geopolitical, it’s likely February’s U.S. funding tally will remain one for the record books.��

Clearly, a $110 billion funding round — something without close precedent in startup history — will be�� tough to top. If it does happen, it’ll likely take years, not weeks or months.

For now, we’ll be keeping a close eye on the health of later-stage funding by more typical comps. By those measures, the March slowdown looks considerably less dire.

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led the financing, which included participation from ��and angel investors from , ��and , among others. Founded in 2022 by former institutional commercial real estate operators and , Cambio has now raised a total of $22 million. It participated in Y Combinator’s summer 2022 cohort and then went into “R&D mode.”

The San Francisco-based company launched its offering at the end of 2023, and de Guzman claims it has since seen “rapid adoption” across enterprise customers and geographies — scaling to 35 countries and to more than 2 billion square feet in assets. It recently opened a London office to support EU and APAC growth.��

From ‘messy’ to investment-grade data

Put simply, Cambio uses large language models and agentic artificial intelligence workflows to turn “messy building data into investor-grade decisions and reporting.” And it claims to do so within minutes.

“Commercial real estate owners sit on thousands of pages of unstructured documents — spreadsheets, PDFs, invoices, energy audits, regulatory filings — that historically required months of manual analysis,” de Guzman told �������� News. “Cambio applies large language models and agentic AI to ingest, reason over, and synthesize that data automatically, delivering investment-grade capital and compliance decisions in minutes.”

Cambio, she said, is architected around agentic AI software that can reason across unstructured data, run multi-step analyses, and “continuously adapt as regulations, assets, and market conditions change.”

In a nutshell, it aims to help institutional investors figure out where to deploy capital, which assets to prioritize, and how to maximize returns. Customers include , , , ��and , among others.

The market opportunity, according to de Guzman, is enormous: commercial real estate is estimated to be in the U.S. alone.

In 2025, global real estate-related startups pulled in about $10.5 billion in seed- through growth-stage financing, per �������� . That’s up about 17% from $9 billion in 2024.

An industry track record

Part of Cambio’s strategy is to have built a (largely female) leadership team that has directly worked in the space it is trying to serve. De Guzman and Grayson began their careers at large institutional firms such as and Oxford Properties.��

The startup also recently hired alumna to serve as head of product innovation. , formerly of Oxford Properties and , has been tapped to serve as lead of Cambio’s European and APAC business.

The moves from institutions to a startup serving them reflect a broader shift happening in commercial real estate, noted Grayson — the choice “to step inside AI transformation, and not just observe it from the sidelines.”

Cambio operates an enterprise SaaS revenue model. It plans to use its new capital primarily to scale product and engineering.

, managing director at Maverick Ventures, told �������� News via email that his firm was impressed with the fact that Cambio’s founders had spent more than two decades running commercial real estate portfolios.

“That lived experience matters,” he said. “It gave them an intuitive understanding that this wasn’t a tooling problem – it was a workflow problem.”

Maverick was also impressed by the fact that Cambio wasn’t trying “to bolt AI onto existing processes.”

‘Re-architecting the workflow’

“Cambio isn’t automating around the edges, it’s re-architecting the workflow end to end in an AI-native way, with a deeply product-minded approach,” Isono said. “Knowing what to build, which workflow to wedge into, and how to sequence products requires having lived these workflows, which Leia and Steph have.”

The investor also praised the startup’s technical team, noting that CTO was one of the earliest backend engineers at , a marketplace and wholesale platform that was valued at nearly $13 billion in 2022. That technical team, he said, also includes Ph.D.s with “deep expertise” in building science.��

“That matters because commercial real estate is fundamentally tied to the physical world. Much of the data isn’t clean or fully digitized, and automating it is meaningfully harder than in purely digital domains,” Isono said. “Solving that unlocks a uniquely valuable dataset that compounds over time.”

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It’s no simple goal to achieve, of course. But these days there are almost infinite ways to spend money trying, including classes, gear, biometric trackers, supplements, and so on.��

Just don’t expect newly funded startups to get you to the finish line. Venture investment in the fitness and wellness space peaked about four years ago. It hit a cyclical low last year, with just over $5 billion in reported global funding.

Where the money is going

That said, it’s not as if investors have abandoned the space, and there are still companies securing big rounds.

In recent months, the standout was , maker of a smart ring that collects data on dozens of personal health and wellness metrics. In October, the 12-year-old Finnish company that it closed on more than $900 million at an impressive $11 billion valuation.

Another longtime player in the space, fitness app , reportedly reached a $2.2 billion valuation earlier this year after raising an undisclosed amount of new funding led by . And on the wellness front, , an at-home testing platform, picked up $165 million in a Series F early last year.

Getting a good night’s rest is also fundamental for healthy living, and in this arena smart sleep system developer was a standout. The 12-year-old company raised $100 million for its Series D last summer.

Below, we put together a list of some of the larger funding recipients this past year.

Outside the venture sphere, private equity and growth investors are also eyeing the intersection of fitness and AI. Last week, fitness and wellness brands , , ��and announced they are merging under a parent company, . The transaction includes $785 million in new equity investment, led by , and values the combined company at $7.5 billion.

Where the money isn’t going

Yet while investors are keen on some fitness startups strategies, others have fallen out of favor.

So where is the money not going? Connected fitness equipment startups are one of the areas that have lost financial support in a big way.

Shares of what used to be the sector’s most famous success story — —�� are down over 95% from the pandemic-era highs. Others that raised considerable capital have been mostly running on existing reserves.

This includes rowing machine startup , which raised more than $360 million between 2018 and 2022, but hasn’t had a reported financing since, per �������� data. Another, smart home gym maker , secured $580 million but has not landed a fresh round in nearly three years.

Prediction: More AI

As we look ahead to contemplate what fitness and fitness-adjacent areas might be best primed to attract investment, it’s not quite obvious. For now, IPO activity in the space looks muted, though last week’s Playlist rollup offers a sign that acquirers see some value.

Perhaps for now, the only thing one can be comfortable prognosticating is the same thing that applies to every sector on earth: that AI-enabled offerings will be more widespread and more heavily funded.��

Now, if only the AI could lift weights and go on runs for us too.

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While a relatively small acquisition, the deal is significant in that it’s representative of the role that artificial intelligence is playing in many of the fastest-growing venture-backed startups — even those that aren’t necessarily strictly AI companies.��

New York-based fintech Ramp is definitely among that rapidly growing bunch, having achieved a valuation of $22.5 billion, as well as annualized revenue of $1 billion, in 2025. That’s up from just a few months earlier in March, as well as an increase from as of January.��

The company says it began “generating cash flow” earlier this year.

has raised just under $2.5 million in funding since its 2022 inception from investors such as , and . The startup initially was a load-testing platform before pivoting in 2024 to launch an AI coding assistant for large production-scale code, according to CEO and founder .

More startups buying startups

Besides being strategic for Ramp, the acquisition is also representative of an uptick in the number of startups buying other startups. In the first three quarters of 2025, there were 647 reported M&A deals globally in which startups bought other startups, according to �������� . That compares to 539 in the same period last year, a 20% increase.

For comparison’s sake, in the full years 2021 and 2022, there were nearly 1,000 deals in which startups bought other startups, per �������� data.

‘Making engineers radically more productive’

“The need for both of those is even more important now with AI and agentic work taking hold in finance,” he said.��

He claims that thanks in part to AI, Ramp customers can get 3x more done in Ramp today than they could just two years ago.��

“And in the next two years we want that to be 30x,” Atiyeh said. “We think the way to get there is by focusing on AI and agentic workflows, making Ramp’s platform dramatically more powerful. We’re focused on hiring the best engineering talent there is to make this happen and then, importantly, making our engineers as productive as possible.”

That’s what got him so excited about the Jolt team. Their entire focus, Atiyeh said, “is on making engineers radically more productive — helping them ship faster.”

Jolt AI’s 2024 pivot proved to be the right move. So much so in fact that the CEO of one of its early customers introduced the small startup to Atiyeh and Ramp earlier this year.

And the rest, as they say, is history. Ramp’s purchase, notably, involved only the company’s three-person team, and not its product.

“Jolt is a team of world-class engineers who have spent years solving some of the hardest problems in developer productivity,” Atiyeh said. “They’re now bringing that expertise to Ramp’s developer tools and beyond. I’m most excited to see what their team can do within Ramp, so that’s what this deal was focused on.”

Financial terms of the transaction were not disclosed.

Ramping up

Today, Ramp has more than 45,000 customers, in early March. Those customers include , , , , , , , , , ��and , among others.

Presently, Ramp has 1,200 employees. The Jolt team — made up of Spektor, (CTO) and (principal engineer) — will integrate into Ramp’s engineering platform team with a “core focus on helping engineers build faster.”

“They’re going to do this by strengthening our core AI platform and infrastructure, supercharging our dev experience, and transforming product and tooling with applied AI,” Atiyeh said.��

The trio is also going to be working on Ramp’s AI and agentic products for its customers, he added.

It’s not the first time that Ramp has acquired AI-related companies. In 2023, it in an effort to accelerate AI-powered customer support. And in 2024, it to automate procurement workflows.

“From a talent perspective, Ramp’s engineering team is made up of founders, math olympiads, and AI researchers,” Atiyeh told �������� News. “… My goal is to hire elite technical talent, and then get out of their way.”

For his part, Jolt’s Spektor admitted in an interview that he didn’t expect to get acquired by a company like Ramp, but that he’s “extremely happy” it is where his team landed.

The trio will be working on a number of things including Ramp’s internal engineering platform.

“Some of that does involve AI tooling. Our whole goal is to make sure engineers are as fast and effective as possible,” Spektor said. “And on the customer-facing side of things, there’s a lot of development around bringing AI agents and features to financial workflows. So we’ll be helping out in that department as well.”

Bottom line, according to Atiyeh, AI is changing the way Ramp uses and builds software.��

“With the Jolt team on board, we’re doubling down on both fronts,” Atiyeh wrote in a blog post, “building the internal AI devtools that help our engineers ship at high velocity, and creating products that save finance teams time and money at scale.”

Over the years, Ramp has built a name for itself in the corporate card and expense management space. It’s branched out into travel, bill pay, and, in January, released that had it encroaching into digital bank territory.��

Its latest acquisition is in line with what experts are seeing in 2025. Earlier this year, , co-founder of , noted an interesting trend she’s seeing: more asset acquisitions plus acqui-hires.��

She said one reason for that increase is a rush to market, most particularly in the extremely competitive AI field and with companies who have incorporated AI in their offerings..

Indeed, Ramp operates in an extremely competitive space against the likes of – which recently filed an S-1 to go public despite being far from profitable – ��and . In an Oct. 2 , Brex CEO and co-founder wrote that his company “was operating cash flow positive for the first time in history.”��

Since its 2019 inception, New York-based Ramp says it has raised a total of $1.9 billion in equity funding. Investors include , , , ,, , and , , (formerly Google Ventures), and .

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Related reading:��

• Why More Startups Are Buying Other Startups In 2025
• Fueled By AI, Fintech Ramp Raises $500M at a $22.5B Valuation Just Weeks After Last Raise

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