led the San Francisco-based company’s Series A, with participation from , , and of . The financing brings Baselayer’s total funding to about $40 million since its 2023 inception, according to co-founder and CEO . The company declined to disclose its valuation.

Baselayer combines business identity, credit and fraud data to help banks, fintech companies and other financial-services providers evaluate prospective customers. It sells its products directly and through software companies that resell or put their own branding on Baselayer’s technology. Its automated platform initially focused on Know Your Business, or KYB, identity verification, fraud detection and risk management.

More than 2,000 financial institutions — representing over 20% of such institutions in the U.S. — use its technology to onboard, underwrite and open accounts for merchants, according to Awad. Baselayer also works with Fortune 500 companies and has about 50 employees across offices in San Francisco and New York. Since its founding, the startup claims it has helped customers prevent more than $1 billion in fraud losses.

Awad declined to reveal hard revenue figures, saying only that Baselayer reached eight figures in revenue in less than two years.

Now, Baselayer is using its new capital to address a newer — and growing — identity problem: determining whether an AI agent is actually authorized to act on behalf of a particular person or business.

With people using AI agents left and right these days to book a restaurant reservation, for example, it’s becoming increasingly challenging to determine whether an AI agent’s automated activity is legitimate or if it’s a bot attempting to scrape data or commit fraud.

Alongside its raise, Baselayer today is also announcing the launch of its Agentic Identity Suite, extending its identity network from businesses to the AI agents transacting on their behalf.

From businesses to the agents acting for them

Awad and co-founder started Baselayer in February 2023, initially focusing on the lengthy and fragmented process financial institutions use to verify businesses and assess risk.

“What we set out to do was essentially bring risk assessment to the 21st century,” Awad recalls.

Awad describes Baselayer as both an identity network and a fraud consortium. Because its technology is used across thousands of financial institutions, Baselayer says it can recognize when the same person or business applies at multiple institutions and incorporate that activity into its risk scoring.

The company processes tens of millions of applications and says it sees many of the same businesses multiple times a year. That data becomes more useful as additional institutions and reseller partners join its network, according to Awad.

“We’ve essentially streamlined 10 years’ worth of selling into two years,” he said.

An AI agent presents a different problem, however. It may be created for a single task and disappear immediately afterward, leaving little or no history for a bank or risk provider to evaluate.

“Agents spin up and they spin down,” Awad said. “How can you trust this random one-task agent?”

To address this dilemma, Baselayer is developing what it describes as “Know Your Agent,” or KYA. The system is being designed to do things such as determine not only who deployed an agent, but also who that agent represents and whether it actually has permission to carry out a particular task.

It wants to do this by providing an authorized agent with a credential it can present when attempting to make a purchase or interact with another business. Then, when presented with a credential, a merchant, financial institution or online platform could use that information to decide whether to allow the transaction to proceed, Awad explained.

The startup is working with agent developers, payment processors, merchants and fraud-detection providers to issue and recognize its credential. They include , and Socure, among others. Unless agents can establish that they are acting on behalf of legitimate people or businesses, “agents will just get blocked everywhere,” Awad said.

AI can also make fraud easier to scale

Ironically, the same technology that allows legitimate agents to do more tasks can also help fraudsters operate faster.

In the past, identity fraud involved someone getting their hands on stolen personal and business information, creating a credible-looking identity, and then repeatedly applying for bank or credit card accounts until an institution approved one. At one point, the process took significant time and manual work. But today, AI agents can automate parts of it and run continuously.

“It’s fraud on steroids right now,” Awad said. “It’s so easy, it’s so cheap, it’s so fast, and it’s 24/7.”

Reports of AI agents bypassing restrictions have also raised questions about how to identify and control autonomous software. , for example, recently reported incidents in which its models took unauthorized or deceptive actions, including activity involving the e platform.

Baselayer’s technology would not keep a model from disregarding instructions or exploiting a vulnerability, Awad acknowledged. But its goal is to verify an agent’s credentials when it attempts to interact or transact with an outside party.

Without a way to identify themselves, he said, legitimate agents may resort to trying to get around websites’ restrictions just to be able to complete their assigned tasks. Or, they could simply become less useful because they are repeatedly blocked as suspected bots.

Competing to establish a standard

M13 managing partner told șÚÁÏłÔčÏ News in an interview that he met Awad about a year before his firm invested in Baselayer. At the time, he saw the startup primarily as a provider of Know Your Business technology.

“The business did not feel like a business of the future,” he admits. “It just felt like he was solving a KYB banking verification problem.”

The investor’s view changed as more companies began exploring payments made by AI agents and Baselayer began applying its business-identity data to the field.

“Every agent ultimately is going to have to be tied to something real, and they understand the real world,” Alomar said.

He believes Baselayer’s existing data, identity network and relationships with financial institutions give it an advantage over a startup entering the market from scratch.

“AI agents are rapidly becoming economic actors, but the identity infrastructure underneath commerce was never designed for software that can open accounts, make purchases, move money or enter into transactions on someone else’s behalf,” Alomar added. “That creates an enormous new trust problem, and we believe identity will become one of the foundational infrastructure layers of the agentic economy.”

So far, no dominant standard exists. But Baselayer still must work to persuade agent developers, merchants, financial institutions and payment companies to recognize its credential.

That could take time. Awad said relationships with financial institutions typically take 12 to 18 months to establish, while large merchant partnerships can take up to 24 months. Baselayer may be able to reach some institutions more quickly, however, through its existing reseller relationships.

The company also sees potential use cases beyond payments. For example, Alomar said the technology could eventually authorize agents involved in cryptocurrency transactions or smart contracts, among other things.

“This is not just a fintech business — it’s a security business,” he said. “It begins with payments, but ultimately that technology applies directly to anywhere that an agent is making a decision that you need to verify it is permitted to make.”

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A decade ago, Espahbodi co-founded aerospace and defense startup accelerator and moved back to the U.S. to expand it. On the advice of friends at , he opened an office in El Segundo, California, near , just as more alumni of that company were leaving to launch hard-tech startups of their own and next-generation defense startups including were emerging.

Espahbodi eventually sold his stake in Starburst and launched , which invests in companies spanning industrial infrastructure, manufacturing, energy and water desalination. The firm has backed 14 companies since making its first investment in January 2023.

He also advises federal agencies on working with nontraditional, venture-backed companies. In an interview with șÚÁÏłÔčÏ News, he discusses how AI is changing hardware economics, why software investors are rushing into industrial technology, and what he believes many of them misunderstand about the sector.

This interview has been edited for length and clarity.

șÚÁÏłÔčÏ News: What led you to leave Starburst and launch Generational Partners?

Espahbodi: About four years ago, I noticed that my friends from SpaceX were leaving the space vertical and moving horizontally across physical industries. I reached an inflection point: I didn’t want to remain locked into the space sector. I wanted to follow my friends.

I sold my equity in the accelerator, and part of the investment team left with me to start Generational Partners. For the past four years, we’ve invested in what you might call the SpaceX-mafia and hard-tech sectors — anything involving industrial infrastructure, manufacturing, energy or water desalination.

We made our first investment in January 2023, in a North Dakota-based drone company. It was a trial by fire and an opportunity to prove the thesis. We’ve invested in 14 companies since then.

You were already investing in physical, safety-critical industries before the generative AI boom. Has AI materially changed where you invest, or has it mainly reinforced your existing thesis?

Espahbodi: I tend to arrive earlier than others. I embraced the idea that hardware does not have to be capital-intensive. People often confuse hard tech with deep tech, but nomenclature aside, you don’t need to invest in science to win in these categories.

AI has dramatically changed that narrative and encouraged more people to get on board. I’m not looking to invest in science. I don’t necessarily see opportunities in quantum computing, nuclear fusion or other technologies being spun out of laboratories.

People who worked at companies such as SpaceX, and laid their companies’ foundations digitally. AI has significantly improved that augmentation and performance, enabling these companies to tackle legacy industries more aggressively and, more importantly, with new business models.

Another major component of the AI question is that frontier labs have become more expensive and capital-intensive than traditional hardware companies. The success of frontier AI labs, combined with the SpaceX IPO becoming an enormous wealth-creation event, creates a new environment. It raises questions about what is truly capital-intensive, what makes a product or its intellectual property defensible, and where companies are reengineering products around different business models.

Hardware has historically been capital-intensive, slower to commercialize and difficult to scale. Under what conditions does its technical defensibility compensate for those challenges?

Espahbodi: Fundamentally, it comes down to the business model. I look for creative software talent combined with commoditized hardware, significant customer demand and a new business model.

One of our portfolio companies was founded by the team that built the factory for user terminals. When you buy a retail Starlink antenna, these people built and scaled the assembly line that produced it at high volume.

While deploying those terminals globally to provide internet access, they observed that poverty often stemmed from a lack of access to clean water. They asked whether they could replicate the proliferated satellite-and-user-terminal architecture for edge water desalination.

Rather than investing in multibillion-dollar, nation-state infrastructure like that used by Gulf countries, they wanted to mass-produce every component in a vertically integrated stack. Their goal was to produce a cooler-sized device that could clean water at the point of need.

used a digital, software-based approach to build the bill of materials needed for mass manufacturing. AI is part of its business and operations, but the company’s real innovation was inverting the infrastructure model and scaling it.

I helped Vital Lyfe win its first customers within the and . Those organizations can use its devices in the field rather than shipping pallets of bottled water by air freight. That created a signal for overseas partnerships and nonprofit humanitarian-aid applications. It showed that there could be a different way to provide clean water.

Those are the kinds of unique business models that excite me.

What other companies founded by SpaceX alumni demonstrate how hardware businesses can overcome the traditional challenges of the sector? What can these founders build today that would have been difficult five years ago?

Espahbodi: Another example is the team SpaceX recruited to build the autonomous drone ships that catch boosters in the middle of the ocean. The team included former Coast Guard personnel and oil-and-gas technicians.

At SpaceX, they had the freedom to use software and AI tools to automate station-keeping — the ability of those drone ships to position and navigate themselves and reach the right location.

That team spun out and brought in many former colleagues to change commercial maritime shipping. They retrofit legacy boats operating in harbors and waterways and move supply-chain goods.

They brought a digital-first foundation to automating the controls on tugboats and barges. That had never existed before because the communications link to those ships didn’t exist. Starlink changed the concept of operations. The company can use its software expertise to change how physical devices operate aboard these boats and allow their sensors to send signals anywhere in the world.

That makes it possible to retrofit and overhaul how legacy shipping vessels navigate harbors and waterways in the U.S. It’s another example of SpaceX alumni applying the playbook and technologies they learned at SpaceX to a much broader commercial industry.

You’ve said AI is eroding traditional software moats. What evidence are you seeing that investors are responding by moving into hardware and industrial technology?

Espahbodi: I meet many software investors who feel they’re missing out on hardware but don’t necessarily understand it. I’ve met beauty investors who now say they’re defense-tech investors.

Los Angeles is a hotbed of firms that historically invested in software, media or consumer packaged goods. But people forget that Southern California, particularly El Segundo, is the aerospace capital of the world and has the largest concentration of mechanical-engineering talent.

Across the region — from China Lake to San Diego — technicians, builders and vocational talent are intersecting with the democratization of software and access to AI tools. Many local VCs have never taken advantage of the hardware talent located around them, so they’re being thrown for a loop.

Ironically, Bay Area VCs have been among those leaning most heavily into this. But it’s happening everywhere. I’m in Washington, D.C., now, and one of the first investors in , the hypersonic missile company, was in Virginia — before and others became involved.

Los Angeles VCs in particular know there is a talent war underway and that many people are leaving established companies to launch new businesses in these categories. But they struggle to underwrite those deals. They don’t know how to distinguish a strong opportunity from fear of missing out or something merely cosmetic.

So investors’ lack of experience in the space isn’t deterring them from writing checks or competing for deals?

Espahbodi: You have to ask why. The answer is their limited partners.

Sophisticated allocators, such as endowments, foundations and pension funds, along with more FOMO-driven family offices and high-net-worth investors, are watching this wave of SpaceX, and Anduril alumni create new companies and raise extraordinary rounds.

Many of those companies are no longer raising solely to pursue intellectual property. They’re building war chests to acquire other companies. The lines between private equity and venture capital are blurring. VC-backed companies are doing private equity-style buyouts, while venture deals are bringing in private equity checks.

That leaves LPs pushing for more. The success of the frontier AI labs has also perpetuated a fear of a “SaaS apocalypse,” which I don’t think is real — although I sometimes question ’s 1 stock price for fun.

It creates what venture does best: tourists and FOMO. LPs ask why their managers aren’t investing in the same companies and how they can participate, raise more money and show that they aren’t missing out. That’s how I’ve seen investors unfamiliar with these sectors enter the market.

Some of the largest Silicon Valley firms … missed this dynamism wave. Now they’re leaning in hard, sometimes at ridiculous valuations for companies that have yet to produce anything.

If more venture funding continues to flow into defense, aerospace and industrial technology, what prevents hardware from developing the same problems software experienced, including too many competing companies?

Espahbodi: Bring it on — hard and fast, and as much as possible.

Venture as a category exists because it was always about hardware. I would argue that the SaaS era, from the dot-com boom until now, was a blip compared with what venture was originally intended to underwrite.

I would move away from the hardware-vs.-software distinction and ask who is reframing the business model. Is there a way to reengineer a combination of software and hardware to unlock customer value? That’s the more important question.

How important is geography for these startups? Does locating near a major government customer help a company win contracts, and how do startups navigate procurement if they aren’t based near Washington, D.C.?

Espahbodi: It’s a common misconception that Washington is where the money is. The Los Angeles Air Force Base houses , which is another way of saying it holds ’s wallet. El Segundo makes the purchasing decisions for the fastest-growing portion of the military budget.

Washington is a place of considerable activity that needs to be influenced. Venture has never had this degree of influence on an administration and its executive orders. We’re also seeing portfolio companies backed by influential investors win government contracts worth as much as $1 billion at a time. That’s extraordinary.

Geographically, companies need to be where the talent is as much as where the customers are. Government customers should signal what matters, but companies shouldn’t organize themselves entirely around the government.

My catchphrase is that I want everyone to be commercially focused but mission-aware. I don’t want them to be mission-focused on the government. I want government to signal what it cares about while companies remain commercially focused.

The talent war for this convergence of hardware and digital technology is centered in Southern California. If you aren’t building and recruiting there, you’re falling behind. I like that the Bay Area is trying to attract more hardware talent and capitalize on the automotive and humanoid-robotics markets.

But I think the talent base for the factory of the future starts in Southern California and can then be used as a model for expansion into other places, as companies such as Anduril have done in Ohio and Louisiana.

We invested in a company founded by people from SpaceX and . They immediately moved to Austin to build a smart factory for raw-material processing. They wanted to automate the process at its source.

The largest concentration of cotton farming is around Lubbock in the Texas Panhandle. The company is building automated factories from the ground up to mill cotton into yarn and then complete the digital, vertically integrated stack by producing textiles at prices that beat outsourcing to China, Vietnam and other countries.

It sounds crazy, but the founder is determined to do it. If you can prove the model in textiles, you can apply it to copper. If you can do it with copper, you can do it in pharmaceuticals. From there, it could go in any direction.

Do startups located near Space Systems Command have an advantage?

Espahbodi: Not for that reason alone. The advantage is that they’re part of the ecosystem and geography. They’re spending time in the same bars and restaurants, and their children attend the same schools. They’re witnessing the same velocity.

Space Force itself is facing greater demand than ever to protect assets in space. Whatever happens with funding for individual programs, it remains the fastest-growing portion of the Pentagon budget.

I don’t think startups should locate there solely to be close to the customer. They should be there for the talent they need to build.

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The New York-based company publicly launched Thursday with an undisclosed seed round led by São Paulo-based venture firm and a debt financing partnership with ’s Customer Value Fund. Since its January inception, Skalar has committed to finance more than $125 million in sales and marketing spending across seven technology companies over the next 12 months.

Financing tied to customer revenue

Skalar’s model is fairly straightforward, though somewhat unusual. The company provides startups with capital to fund sales and marketing initiatives. The startups then pay it back out of the revenue generated by the customers acquired with that capital.

If those customers generate less revenue than expected, Skalar says it absorbs the shortfall rather than requiring the company to repay the full original amount.

Skalar’s current deals generally call for it to collect about 1.1x the amount provided.

For example, if a company spends $10 to acquire a customer and expects that customer to pay $1 per month for 30 months, Skalar provides the initial $10 and collects the first $11 that customer generates. Once Skalar reaches that repayment limit, the company can keep the remaining revenue.

But if the customer cancels after eight months, Skalar collects only $8 and writes off the balance, according to co-founder and CEO .

“We only get repaid as they get repaid,” CĂĄrdenas told șÚÁÏłÔčÏ News.

Notably, the startup doesn’t have to pay the capital back by a certain date. Instead, repayment is tied to revenue from the customers acquired with the financing, rather than a fixed schedule. For example, a company that recoups its acquisition costs in one month repays the loan in one month, while one that takes 12 months repays it over one year. So while the obligation remains contractual, Skalar operates under the premise that a flexible timeline reduces the risk of a cash crunch.

How it differs from other financing

Skalar’s structure differs from both venture debt and existing forms of revenue-based financing, according to Cárdenas.

offers startups flexible funding without equity dilution, but with higher interest and risk. Skalar’s founders contend that paying back that debt can force startups to cut sales and marketing spending or hold onto cash when new growth opportunities emerge.

The model also differs from revenue-based financing, which typically advances money to companies based on signed contracts or revenue they are already generating, the founders said. Instead, Skalar finances a potential new revenue source before it exists and accepts some of the risk that it may never fully materialize.

Taking on that risk means that Skalar has to closely examine a company’s operations. It analyzes detailed transaction data to determine how much the company spends to acquire customers, how long those customers stay, and how much revenue they generate over time. It also means the company is very selective about who it chooses to finance. Skalar’s system continually updates company assessments as new information comes in, according to co-founder and COO Daniel Castrillón.

“We have become experts in understanding these types of risks and when they are sufficiently predictable and sufficiently profitable to be underwritable,” he said.

The risks for founders

The arrangement is not without risk for startups, concedes CĂĄrdenas. Skalar sets minimum revenue targets for the companies it finances. If results fall below those targets, it can require faster repayment. It can also stop providing additional capital under certain circumstances, which could leave a company without funding it had expected to receive.

Its terms are based on estimates involving customer revenue, profit margins, currency fluctuations and which sales can be attributed to a particular marketing investment. If those estimates prove wrong, or if the cost of acquiring customers rises, the startup may receive less benefit from the arrangement than expected, CĂĄrdenas said.

Importantly, Skalar’s agreements do not give it the right to seize a company’s assets in the event of a default, Cárdenas said, and they do not require borrowers to maintain specific financial benchmarks or cash balances.

Still, founders must weigh the possibility of accelerated repayment or interrupted funding when deciding whether the financing fits their plans.

“Our structure is fundamentally different because it absorbs most of the downside risk 
 and we are unlikely to walk away unscathed if something bad happens. This incentivizes us to always be mindful of not encumbering the companies we work with with credit risk, as this ultimately increases risk for us,” CĂĄrdenas told șÚÁÏłÔčÏ News.

A narrow initial customer base

Skalar is targeting technology companies that spend between $100,000 and $3 million per month acquiring customers and have a consistent record of earning more from those customers than they spend to acquire them. It also considers whether a company has enough cash to remain in business long enough for that customer revenue to arrive.

Its first seven customers include four or five Latin American companies, CĂĄrdenas said, as well as businesses in the United States. Skalar initially plans to work with no more than 15 companies per year.

The company declined to disclose the size of its seed round, which closed during the first quarter. Cárdenas described it as a large seed round by Latin America’s standards. and several angel investors with relevant industry experience also participated.

is providing the debt capital Skalar will use to finance its customers’ sales and marketing spending. The size of that partnership was also not disclosed.

The General Catalyst connection

Skalar grew out of Cárdenas’ work as an entrepreneur-in-residence at Monashees, where he helped introduce several of the firm’s portfolio companies to General Catalyst’s Customer Value Fund model.

General Catalyst pioneered a similar approach but increasingly focused on larger financing deals, CĂĄrdenas said. That created an opportunity to serve smaller companies, including startups in Latin America.

“The best companies are thoughtful about matching their sources and uses of capital: equity for transformative but unstructured product and R&D bets, low-cost, duration-matched capital for predictable investments like customer acquisition,” , partner at the Customer Value Fund, said in a statement. “Most technology companies in Latin America have never had the choice, and Sebastián came to us with that gap in mind. As an investor in the region, he saw the CVF model transform a handful of companies in his own portfolio, and he pitched us on closing the capital gap together.”

Still, Skalar is not restricted to financing businesses with no connection to either General Catalyst or Monashees. Monashees general partner said his firm does not have access to the confidential operating data that startups provide to Skalar as it evaluates their businesses.

For Monashees, the model addresses the long-standing shortage of growth financing in Latin America. Bolognesi told șÚÁÏłÔčÏ News that his firm, the largest venture firm in Brazil, has watched companies with strong customer performance struggle to secure enough money to pursue their growth opportunities, particularly as equity investment in the region rose and fell.

“We’ve seen capital flow into and out of the growth stage, leaving some excellent companies struggling to raise the equity they need to keep growing,” he said. “Skalar fills that gap by giving promising companies access to capital while they build the track record investors want to see.”

A market beyond venture-backed startups

Skalar is initially focused strictly on financing customer acquisition. Its founders eventually envision offering similar products for other business expenses that produce sufficiently predictable returns.

CĂĄrdenas also sees a longer-term opportunity beyond the relatively small group of companies able to attract institutional venture capital. Businesses that have trouble raising venture capital because of their location, industry or growth rate may still qualify for Skalar financing based on their financial performance.

“Venture capital solved the problem of funding the top 1% of tech businesses,” he said. “But 99% of tech businesses — out of which I’d say probably more than half could be underwritten by our product — just don’t have access to capital today, and ours is a product that fundamentally changes that.”

In the long run, Skalar is betting that its approach can bring growth financing to a much larger group of companies. For startups that can raise venture capital, it also offers a way to fund predictable growth without giving up more ownership.

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Startups across sales, marketing and customer management have raised $7.5 billion so far this year, according to șÚÁÏłÔčÏ data. The largest rounds span everything from advertising and customer data to sales software, e-commerce and customer support — reflecting just how many companies are still trying to build a better way to market and sell.

The broad trend: Investors are making far fewer bets on sales and marketing startups than immediately before and after the COVID-19 pandemic, but they’re still writing checks into the space.

Unsurprisingly, AI-focused companies are capturing a much larger share of funding than during the prior peak, with most sales, marketing and CRM investment going to companies in șÚÁÏłÔčÏ AI-related categories.

The numbers: So far in 2026, startups in sales, marketing and CRM have raised $7.5 billion globally across 830 funding rounds, șÚÁÏłÔčÏ data shows. At the current pace, funding could finish near the $9.3 billion raised in both 2023 and 2024, although potentially below last year’s $11.1 billion. Deal volume, meanwhile, is on track to fall for a fourth consecutive year — pointing to a market where investors are putting more money into fewer companies.

Funding in recent years remains far below past levels. In 2022, for example, funding in the sector topped $27 billion, and in 2021, it totaled nearly $41 billion.

Notable deals

The year’s largest funding recipient so far was, which raised more than $1 billion in a June Series E from , , and . The San Francisco-based marketing measurement company, whose products now include AI agents that analyze marketing data and automate tasks, was valued at $2.7 billion.

Restaurant financing and rewards platform announced $450 million in new capital in February. The Austin-based company did not identify a lead investor or disclose a valuation.

In January, AI-native customer service company raised a $350 million Series D led by . The Berlin-based company develops AI agents that handle customer conversations by phone and other channels. The financing tripled its valuation to $3 billion.

Meanwhile, , an online marketplace for digital products, communities and courses, received a $200 million strategic investment from in February. The deal valued the New York-based company at $1.6 billion.

Another larger deal went to Dubai-based property listings platform , which announced a $170 million equity investment in January. The company uses AI in products including home valuations and tools that help real estate agents improve and prioritize listings. led the deal, with participation from another UAE sovereign wealth fund and existing investor . The company did not disclose a valuation.

On Sept. 9,  AI-powered sales automation startup announced it had raised a $115 million Series D at a $7.1 billion valuation. This was more than double the $3.1 billion valuation it achieved when it raised a $100 million Series C in August 2025. Wellington led the latest round, with participation from , , ’s a16z Perennial wealth management arm, , and others. The company says the raise followed 4x revenue growth in 2025. It also told șÚÁÏłÔčÏ News that it’s on track to hit $200 million in ARR this quarter, and $240 million by the end of the fiscal year.

Exits

The sector has produced one notable public offering, but most exits are coming through acquisitions as larger companies buy specialized sales and marketing products to add to their existing platforms, șÚÁÏłÔčÏ data shows.

, a Redwood City, California-based mobile advertising and app-marketing company, began trading on the in June. It initially sold 19 million shares at $23 each, raising $437 million. The IPO valued Liftoff at $3.83 billion, based on the outstanding shares disclosed in its IPO prospectus.

There have been a number of M&A deals this year in the sector, too, though in most cases, the acquisition price was not disclosed.

The largest known deal was Dutch payments giant acquisition of , a Berlin-based loyalty and promotions platform, in July for about $880 million. Talon had previously raised over $120 million in venture funding.

Other startup M&A deals in the marketing and sales arena in 2026 include:

• In July, acquired Seattle-based sales intelligence startup to add information about prospective buyers to its sales products.
• In June, agreed to acquire , whose software helps companies identify and contact people visiting their websites.
• Sales platform acquired , which helps sales teams identify prospective customers based on product use and other signals, in March.
• acquired the Estonian startup , whose software connects sales and marketing data, in August.
• acquired India-based marketing intelligence startup in September through a team and technology deal.

Funding is down from peak years, but it’s clear investors haven’t lost interest in sales and marketing startups. However, they are putting more money into fewer of them. Companies that help businesses find customers, increase sales, or retain existing business are still landing big checks and attracting buyers. But with acquisitions far more common than IPOs, a public-market exit remains much harder to come by.

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After completing medical school in London, decided not to pursue a residency. Her father was disappointed.

But she didn’t change her mind because she lost interest in healthcare. Instead, Abuzeid realized she wanted to work on problems affecting more people than she could treat individually.

“Working as a doctor is great, but you’re only working with one patient at a time,” she said in an interview with șÚÁÏłÔčÏ News. With software, “you have millions of users using your products.”

Abuzeid went on to co-found , a San Francisco-based healthcare hiring platform that has raised about $97.5 million from investors such as , , , and . It says its products are used by 1.5 million healthcare professionals — including 1 in 2 U.S. nurses — and 1,500 healthcare employers.

Before launching Incredible Health in 2017, Abuzeid trained as a doctor, advised healthcare companies at and , and worked as a product manager at a health tech startup, but didn’t know how to code software.

An M.D. who chose not to practice

Originally from Sudan, Abuzeid was born and raised in Saudi Arabia and also lived in the United Arab Emirates. She moved to London at 18, where she completed her undergraduate education and medical school.

Her interest in business predated her medical career. Both of her grandfathers were entrepreneurs in Sudan, and she grew up hearing about the companies they built. By medical school, she was increasingly drawn to the reach that entrepreneurship and technology could offer.

After earning her medical degree, Abuzeid immigrated to New York at age 24. Her time in healthcare consulting at Booz Allen and McKinsey exposed her to the strategy, operations and economics behind the healthcare system, she said.

She later earned an MBA from the specializing in healthcare and entrepreneurship, and moved to San Francisco in 2013.

There, she joined an early-stage healthcare technology company as a product manager. The role taught her how to work with engineers, data scientists and designers, as well as how software products are built and grown.

It was also where she met , the software engineer who would become her co-founder at Incredible Health.

Abuzeid still does not code, although she has experimented with newer AI-assisted coding tools. Portlock, an -trained engineer who she calls “the best engineer I’ve ever worked with,” has led Incredible Health’s engineering and data teams from the beginning.

But Abuzeid, the startup’s CEO, argues that a software founder’s central job isn’t writing code.

“At the end of the day, when it comes to creating software companies, it’s about solving problems,” she said. “It’s about identifying the markets, understanding the problems customers are facing and figuring out ways to solve them.”

A mismatch in healthcare hiring

The problem behind Incredible Health surfaced through conversations the founders were having with people they knew.

Doctors in Abuzeid’s family and circle of friends frequently complained about understaffing. At the same time, nurses in Portlock’s family described applying to numerous jobs and often receiving no response.

The two accounts did not line up. Healthcare is the largest U.S. labor sector by number of workers, Abuzeid said, and it faces severe staffing shortages. Yet experienced nurses were struggling to get the attention of employers that urgently needed them.

“We started to dig into it more, and we were like, ‘This doesn’t make any sense,’” she recalls.

The founders discovered that hospital recruiting teams were often small, overwhelmed by applicant volume, and reliant on manual processes.

Incredible Health’s marketplace reverses the usual hiring process so that employers are actually the ones applying to healthcare workers. The software automates screening and matching for permanent jobs at hospitals, surgery centers, home health organizations and other healthcare facilities.

The service is free for healthcare professionals. Employers pay an annual subscription to use the marketplace and the company’s other hiring software. Customers include , , and .

A selective approach to fundraising

Incredible Health has raised approximately $97 million across seed, Series A and Series B rounds.

It was a process, she admits. She spoke with about 70 investors while raising the company’s seed round. Eight invested, including and .

At that stage, Abuzeid said, she had to educate investors about the healthcare labor market and persuade them that she and Portlock were the right founders to address it.

“I think it was the vision and the mission and the team,” she said. “At that point, you’re really investing in the founders.”

Each of Incredible Health’s funding rounds was oversubscribed, Abuzeid said. She attributes that partly to raising from a position of financial strength. The company generally operates close to cash-flow break-even and at times has been cash-flow positive.

Overall, Abuzeid said she is selective about which investors she approaches. Specifically, she prefers firms with marketplace experience and partners who have previously operated companies. She also prioritizes investors who have already backed women or founders of color.

“I don’t want to be the first,” she said. “I’m not here to overcome someone’s bias. That’s not a good use of my time.”

While she acknowledges structural disparities in venture funding, Abuzeid said she didn’t choose to work with Portlock because she believed she needed a male co-founder. Rather, she recognized that a strong technical partner would balance her own skills and abilities.

Overall, Abuzeid believes female founders generally need to emphasize ambition. In her view, investors are used to hearing expansive visions from male founders, and women should be equally vocal about the size of the companies they intend to build.

“It’s really important to be ambitious and to be very clear about your vision and what you’re trying to achieve,” she said.

Automating the first interview

In 2025, like many other startups, Incredible Health incorporated AI into its product lineup.

The company developed the agents with healthcare systems including , , Johns Hopkins and . Working with customers during the development process made it easier for Incredible Health to incorporate the technology into established enterprise workflows, Abuzeid noted.

One agent, Lyn, conducts the initial recruiter interview, asks clinical and behavioral questions, explains an employer’s value proposition, and discusses available roles. It then hands the candidate off for a possible interview with a hiring manager.

A second agent, Gail, helps healthcare professionals create résumés and practice for interviews.

Abuzeid said Lyn has reduced hiring time by 30%. Three-quarters of interviews now occur within 24 hours of a candidate applying, compared with up to two weeks previously. About 40% take place at night or on weekends, when recruiters are less likely to be available.

The AI products clearly extend Incredible Health’s initial mission of removing hiring delays in the healthcare industry. They also reflect the founders’ complementary roles. Portlock continues to oversee engineering, data and technical architecture, while Abuzeid’s work draws on her experience across medicine, healthcare consulting and product management.

For Abuzeid, that distinction shows why she does not consider technical chops a prerequisite for founding a software company.

“At the end of the day, when it comes to creating software companies,” she said, “it’s about solving problems.”

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As a partner at Menlo Park, California-based venture firm Norwest, Jacobsohn focuses on enterprise software, drawing on his background in finance, sales and business development. His 15 active portfolio companies range from pre-revenue startups to businesses generating more than $300 million in revenue. Much of his portfolio falls within finance and HR software, although he also invests in supply chain and construction technology — often in companies building finance applications for those industries.

The common thread, he explained, is a focus on next-generation business applications taking on entrenched providers that have struggled to keep up. Jacobsohn has found particularly fertile ground in finance, where companies already have software budgets and many categories remain dominated by aging systems.

Norwest, founded in 1961, manages $15.5 billion and is investing out of its 17th fund, a $3 billion vehicle raised in 2024. Over time, the global venture and growth equity firm has backed more than 700 companies in sectors spanning enterprise, consumer and healthcare.

In an interview with șÚÁÏłÔčÏ News, Jacobsohn discusses where he still sees openings in the crowded market for finance software, how far companies should trust AI with accounting work, why HR startups may be better off attacking the secondary products of large platforms, and why he tests a CEO’s sales ability before investing.

The interview has been edited for clarity and brevity.

șÚÁÏłÔčÏ News: The office of the CFO is an area where you’ve invested fairly extensively. Why is there still so much room for startups when finance software is already such a crowded market? Where is the opportunity right now?

Jacobsohn: I’m focused a lot on companies that are disrupting legacy players, and there are a lot of legacy players in the office of the CFO. We had more than 500 companies on our Office of the CFO market map, and probably three-quarters of those are legacy players.

What’s interesting about finance is that the CFO approves all software purchases across the organization, but CFOs also buy software for themselves. There’s actually one less layer of approval when they’re buying their own software, so it is a little easier to replace it when they’re the direct buyer.

I’ve found a lot of opportunities in both finance software that sells to every industry and software focused on specific industries. I’ve invested in a lot of horizontal applications, and so far the vertical solutions have been in construction and manufacturing. We’ve also invested in the healthcare space, but that’s not my area of focus. I’m also looking at companies in transportation and logistics.

Are there specific finance workflows that still strike you as surprisingly manual and therefore more ripe for disruption?

Jacobsohn: I actually think most workflows have been automated, but some are being automated by legacy solutions. Some could still be on-premise. Some could be companies making the transition from on-premise to the cloud that are still very legacy. You might even call them SaaS 1.0, because a company can be considered legacy and be only five to 10 years old now that a lot of the new generation is AI-native.

Every company wants to buy AI-native products these days. Some legacy companies have done a better job of reinventing themselves, and others are having more difficulty. Since most everything has been automated by someone, I’m focused on new-generation disruptors of legacy solutions.

What are some of the areas you think are ripe for disruption?

Jacobsohn: I have a portfolio company in some of these categories, and not in others.

One area where I do not have a company is ERP. I think there’s a potential opportunity to disrupt and Those companies have been around for a very long time. I’m seeing more disruption downmarket, and some of these companies will eventually move upmarket.

I think sales tax is another category with some ancient legacy players where there’s an opportunity to disrupt them. Treasury management also has some very old legacy players. Another area I’ve invested in is procurement.

Finance is particularly sensitive when it comes to accuracy and audits. Is that affecting how much work companies will actually hand over to AI agents, especially in accounting?

Jacobsohn: We think about this a lot. Finance people are risk-averse, and they need consistent answers. There’s some concern that there could be errors with AI, and there are.

It’s important to infuse AI into your finance products, but you have to be careful about what you’re giving AI to do. You don’t want AI doing calculations because it is not good at math. There are certain workflows it can handle where it doesn’t produce precise numbers. But when you need precision, accuracy and calculations, you can’t rely on AI for that.

In Norwest’s recent , you mentioned that categories including payroll, benefits and workforce management can be difficult to disrupt because of the time and expense associated with switching. If a startup wants to take business from Workday or ADP, how can it make switching more enticing?

Jacobsohn: I think it would be very hard to disrupt the core products of Workday, , SAP, and Dayforce. But it’s easier to disrupt some of their secondary products, where the category isn’t their core business. Those companies have really good distribution. Often, the best distribution wins, not necessarily the best product.

Workforce management is a category I’ve invested in through . UKG has a product in the space, but it started as an on-premise company and moved to the cloud. We’ve been a cloud-native AI player, and we’ve done well against it in the market.

Another company I invested in that complements these players is , which is in the benefits space. What’s interesting to me is that I worked at WageWorks, a legacy player in the space. Elevate is disrupting my old employer. Benefits isn’t the core business of the suite players I mentioned, but it’s a big enough market where a specialist can do well.

That’s how I look at it: What are some big markets where suite players aren’t putting much effort behind the product because they can only focus on so many things at once?

Is AI making it easier or harder to build a durable software company? Features and products can be built faster, but they can also be copied faster.

Jacobsohn: I do think it’s making it easier to build companies. We’re going from products that store data and automate some workflows to really smart solutions that understand, predict and execute work for you. It’s changing employees’ jobs. Employees can focus on higher-value work and automate some of their tasks with agents that can work really quickly.

As for whether anyone can vibe-code something, I think if you’re building a simple horizontal workflow for small businesses that isn’t very complex, it could be easy to build the product yourself, or it could lead to a lot of competition.

If you’re building something complex for the midmarket or enterprise, something that needs deep domain expertise or something vertical in nature, any of those areas would be really hard for a lot of people to build internally or for too many startups to compete in. Those solutions would also be really hard to maintain. I’m not seeing much competition from people wanting to build internally at my portfolio companies that are focused upmarket, where you need deep domain expertise.

The IPO market has improved, but it certainly isn’t where it was. How does the current exit environment affect what you’re willing to fund today, if at all?

Jacobsohn: It doesn’t impact our interest in funding. Our primary entry point is seed and Series A. I’ve done some Series B and C deals, so we can be opportunistic at the later stage.

We’re focused on backing entrepreneurs with deep domain expertise who are going after big markets with legacy players ripe for disruption, and we don’t worry about the exit environment. At some point, the IPO market will open up more, and maybe that will help us in the future. But more companies get acquired than go public.

I do want to invest in a company that, if it executes well, someday has the option to go public. But I’m realistic that most companies get acquired before that can happen.

How do you feel about an acquisition as an outcome?

Jacobsohn: You have to support your entrepreneurs and what’s in their company’s best interest. M&A can be a very good outcome, especially since we come in so early. If a company is acquired for less than $1 billion, it still could be a great outcome for us and the company.

The challenge is entering late, at a valuation above $1 billion. Not many companies will acquire another company for billions of dollars. We like to come in early so that if a company sells for less than $1 billion, which is where most buyers have budgets, it can be a really good outcome.

Is there a fundamental belief you have about funding or building startups that you think other investors might disagree with?

Jacobsohn: Something that’s different about me from most VCs is that I come from a sales background, and I think the CEOs I back need to be good at sales.

Just about every CEO I back comes from a product and engineering background, but that’s not enough. You need to be good at selling. You need to sell to customers, partners, investors and employees. Before I invest, I’ll go on a lot of sales calls I set up with the CEO to see how good they are at selling.

To me, that’s a big way of assessing the potential of a company.

Have you ever passed on a CEO or startup because you felt the founder didn’t have strong sales skills?

Jacobsohn: Yes. When I go on sales calls and people aren’t interested in a second meeting, and that’s a consistent theme, it often leads me to walk away.

Tell me about your Failure Museum. What are some of the biggest findings you’ve learned in building out the Failure Museum?

Jacobsohn: I have built a that includes more than 1,500 items from failed companies and products. I have them all on my website, where I study why they failed.

People are eager to share their successes and their failures. The museum evokes more optimism than one might think. People shouldn’t be afraid to take risks. Failure can be a springboard to success.

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led the round, with participation from co-leads Scaleup Europe Fund, managed by , and existing investor .

The financing comes nearly one year to the day after Mistral’s $2 billion Series C, which valued the company at $13.7 billion. Mistral has now raised $7.5 billion since its 2023 inception.

Mistral’s new raise means it retains its spot as the most highly valued foundation model company out of Europe. There are currently seven private frontier labs valued above $20 billion on The șÚÁÏłÔčÏ Unicorn board — eight including China’s , which is also building its own model — though the rest are all based in the U.S. and China.

In a statement, the company says the new capital will “significantly expand Mistral’s frontier research” and help it “expand infrastructure and accelerate” its commercial growth and international footprint. Mistral currently operates across 20 countries and counts more than 125 global enterprises as customers, including , , and .

Mistral builds AI models for tasks such as generating text, writing code and analyzing documents, putting it in competition with U.S. companies including , and .

However, unlike many of its U.S. rivals, Mistral touts greater control for businesses by offering models they can customize and run on their own systems rather than relying entirely on a third-party cloud provider.

Europe’s VC momentum

This year has marked a turning point for European venture funding. In Q2, Europe posted its strongest quarter in four years for venture funding, șÚÁÏłÔčÏ data shows. All told, Europe-based startups raised $24 billion in the quarter, up around a third quarter over quarter and two-thirds higher than the $14.4 billion raised in Q2 2025.

At the time of Mistral’s $2 billion Series C, that raise represented the largest venture round ever raised by a European AI company.

This latest round has now eclipsed that, and several other large AI-related deals in Europe have also closed this year. They include London-based Google spinoff , which raised a $2.1 billion Series B in May led by and AI data center provider , which raised a $2 billion Series C at a $14.6 billion valuation in March co-led by and . (It has also since raised several billion in debt financing, per șÚÁÏłÔčÏ.)

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When an executive at suggested that seemed distracted by artificial intelligence, she was not an engineer working on the coding startup’s AI products. She was its general counsel.

The executive told her ‘You’re a great GC and good at business development 
 but it seems like maybe your head’s not in it because you’re so into this AI thing,’” Ziniti recalled in an interview with șÚÁÏłÔčÏ News.

“And it was true,” she said.

By then, Ziniti had spent roughly two decades working as a lawyer at companies such as , and . She had never learned to code. She had not ever founded a company. And she had not worked in the same sort of technical or product roles that many venture-backed software founders have.

But her time at Replit gave her an early look at generative AI. That was enough to inspire her to leave the legal profession and build , a startup bringing AI technology to legal work.

An early look at GPT

In late 2021 and early 2022, Replit was working with on AI-powered coding products, giving Ziniti access to an early version of GPT before ChatGPT was released publicly. She began considering what the technology could mean for lawyers.

Ziniti later taught classes on using ChatGPT for legal work. During these sessions, she began to see the disconnect between applying a general-purpose chatbot to a profession that requires precision, sourcing and tone.

For instance, in one class, she used ChatGPT to research the legal considerations involved in entering the Brazilian market. The response covered the relevant issues, but it started out with language about going to Rio and grabbing surfboards, Ziniti recalled.

At that point, Ziniti recognized there was a distinct gap between an AI-generated answer and something a lawyer could actually use in a professional setting. She realized that what broad models weren’t quite getting right could — and should — become product requirements.

As she began developing the idea, Ziniti teamed up with , an engineer she had worked with at Replit who had experience with earlier generations of GPT. Pourvakil had once been admitted to , she said, but chose engineering instead, partly because he expected AI to automate some legal work.

“I would teach these classes in the morning and tell my co-founder in the afternoon, ‘Our software needs to provide accurate citations. Our software needs to tell you where in the document it’s getting the backup for this. Our software needs to speak in this way,’ ” she said.

A founder who was also the customer

Their backgrounds complemented each other. Pourvakil knew how to build the technology, while Ziniti intimately knew the work it was meant to support.

“I am a better founder for GC AI than I think anyone could be because I was the ICP,” Ziniti said, referring to the startup term “ideal customer profile.” “I was able to step up and meet the moment, even though I don’t code.”

Her understanding of that customer came from a legal career that began well before the current AI boom. Ziniti started as a paralegal at , later worked at and went on to hold senior legal positions at Amazon, Cruise, robotics startup Anki, and Replit.

Although it was when Ziniti realized the enormous potential of AI when it came to the legal industry, Replit wasn’t her first experience with the technology. In 2013, she became the first full-time lawyer assigned to Amazon’s Alexa. She later encountered other forms of AI through autonomous vehicles at Cruise and robotics at Anki.

Notably, she had done much of her work inside companies rather than at law firms. With that experience in mind, Ziniti decided to focus GC AI on those in-house legal departments.

From idea to company

Ziniti left Replit on Nov. 1, 2023, and incorporated San Mateo, California-based GC AI about a week later.

The company initially built an AI assistant for corporate legal departments, then added products for contract analysis and for handling requests submitted to legal teams.

GC AI has seen impressive growth, growing 400% year over year, according to Ziniti. The company now serves roughly 2,100 companies, up from about 900 a year earlier, she said. Its customers range from large enterprises to startups with a single in-house lawyer, and include companies such as , , , and .

The company makes money through a mix of per-seat subscriptions and additional products, including a contract-analysis tool priced by document volume. It also sells a platform for handling and responding to requests submitted to legal departments.

While GC AI competes with legal AI startups and , Ziniti said the startups mostly serve different customers. Harvey and Legora initially focused on law firms, while GC AI has concentrated from the beginning on corporations and their in-house teams.

Its contract intelligence offering, for example, is designed to analyze a company’s own documents, while law firms’ tools may need to work across materials belonging to thousands of clients. Nearly 30% of GC AI’s seats are also used by employees outside legal departments, including HR and finance executives, according to Ziniti.

She believes her extensive legal background helped GC AI address one of the biggest barriers to selling AI software to corporate legal departments: trust.

“It is the number one most important thing,” she said.

About one-third of GC AI’s 125 employees are lawyers, according to Ziniti. The company pursued SOC 2 compliance early, built data-isolation protections, and says it does not train its models on customers’ confidential information.

One longtime customer, Ziniti recalled, described their perception of the difference between GC AI and general-purpose AI tools this way: “Trust, trust, trust. Oh, and trust.”

A different route into venture capital

Ziniti was new to founding a company, but not entirely new to the world of venture capital. She had invested as an angel and served as general counsel at several venture-backed startups, which helped build investor relationships before she began raising money herself.

One of GC AI’s first commitments came from , founder of , a venture firm that invests in experienced operators becoming first-time founders. Ziniti had previously worked with Illig at Cruise.

“Once you get one commit, then it’s relatively easy,” Ziniti said of the company’s seed round.

GC AI has since raised nearly $72 million across three rounds. Its most recent financing was a $60 million Series B co-led by and , which valued the company at $555 million. , , , and The Council also participated.

Ziniti said about 45 general counsels have also invested in GC AI through a special-purpose vehicle.

Her experience illustrates one way generative AI is producing a different type of software founder. One who is an experienced industry practitioner who has identified a use for a certain technology but needs a technical partner to build it.

In Ziniti’s case, the idea for GC AI emerged from the overlap between two parts of her career. Replit exposed her to generative AI early, while her years as an in-house lawyer gave her firsthand knowledge of what a legal AI product should do.

“You have a unique insight on the world in some way from your life experience,” she said. “I did, and I built around that.”

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

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

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

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

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

‘A new kind of perception’

“Physical AI will create entirely new categories of robots, and every one of them will need to understand the world around it,” CEO Shpunt told șÚÁÏłÔčÏ News via email. “That requires a new kind of perception: precise, real-time understanding of geometry and motion that machines can trust enough to act on. We built Lyte to become the perception foundation for that future.”

Funding in the physical AI space has exploded in recent years. In the first half of 2026, global venture funding in the space totaled $47.4 billion across 521 deals, per șÚÁÏłÔčÏ data. That’s up dramatically — almost 4x — compared to the second half of 2025 when physical AI startups raised $12 billion across 470 deals. It’s also up significantly — by nearly 80% — from the $26.4 billion raised across 436 deals in the first half of 2025.

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

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

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A16z led an $87 million equity investment, with participation from , , , and . And General Catalyst’s Customer Value Fund committed $113 million in debt to fund čóĂ©±ôŸ±łæ’s growth.

Founded in 2020 by and , Miami-based čóĂ©±ôŸ±łæ has now raised a total of nearly $300 million. The company did not reveal its valuation after its Series C round, saying only it had “increased threefold” since its Series B, a $75 million round led by QED Investors in 2025.

čóĂ©±ôŸ±łæ says it has processed more than $8 billion in transactions to date and grew revenue more than 2.5x in the past year. It connects people in the U.S. with families across 11 Latin American markets including Mexico, Brazil, Costa Rica, Honduras and Peru.

“I experienced this problem personally,” Godoy said in a statement. “When I came to the U.S., even getting a small loan was harder than it should have been. Traditional financial institutions often start with the product they want you to use. We want to start with the person. You tell čóĂ©±ôŸ±łæ what you need, in your own words, and we help you figure out the rest.”

, general partner of , said in a statement that he believes čóĂ©±ôŸ±łæ represents “what the future of financial services can look like for millions of Latinos in the United States.”

“čóĂ©±ôŸ±łæ has packaged two frontier technologies, AI and blockchain networks, into something simple and consumer-friendly: a better way to send and receive money,” he added.

The company plans to use its new capital to expand its offerings and enter new markets across Latin America.

Overall, fintech startups raised $28.6 billion globally in the first half of 2026, a 22.7% increase from the first half of 2025, but down 17.3% compared to the $34.6 billion raised in the second half of last year, per șÚÁÏłÔčÏ data.

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This story was updated to clarify the company’s valuation.