Notably, the quarter also marked the busiest one for General Catalyst since 2021 in terms of investing in rounds of $5 million or above. The firm鈥檚 next-busiest fintech investing quarter in rounds of that size was the fourth quarter of 2025, when it participated in 10 raises of $5 million or above.

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. (It鈥檚 important to note that H2 2025 marked the strongest six-month funding period for fintech startups since the second half of 2022.)

Over the past year, startup accelerator Y Combinator has routinely ranked as the most active investor in the fintech space. And overall, it was still the most active investor in the second quarter of this year, participating in 41 deals.

But this time, it ranked behind General Catalyst in terms of backing fintech rounds in the $5 million or more category. General Catalyst participated in 12 of those deals, while YC and each invested in 11.

In overall fintech dealmaking, General Catalyst still ranked far behind YC鈥檚 41, with 13 deals. participated in 12, Index Ventures in 11, and in 10.

Top lead investors at $100M or more

For megarounds 鈥� those deals of $100 million or more 鈥� we once again saw private equity firms topping the list of lead or co-lead investors. , , , and topped that list, according to 小蓝视频色情网页版 data.

The largest rounds in Q2 were raised by a geographically diverse bunch of fintech startups. They include:

• Expense management startup was the fintech sector鈥檚 largest recipient of capital in the second quarter, raising a massive $750 million Series F round in June co-led by Ontario Teachers鈥� Pension Plan, Iconiq Capital and GIC that valued the company at over $50 billion post-money.
• , a London-based cross-border payments and foreign-exchange fintech majority-owned by , was a close second 鈥� landing $748 million in a private equity financing led by Centerbridge Partners in April.
• Also in April, Indian consumer lending startup raised $220 million in a Series E round co-led by , and that valued it at more than $1.5 billion.
• Paris-based insurtech landed a $545 million Series G led by Prosus that valued it at $6.2 billion.

Top fintech investors at seed

When it comes to investing in seed rounds, unsurprisingly, Y Combinator again topped the list 鈥� by far, with 33 fintech deals. Next up was with seven investments at the seed stage, and then with six.

The investor base shifted when we looked at who led or co-led post-seed rounds in the second quarter. General Catalyst topped that list, with five deals. , , , Index Ventures, and all tied with three investments each.

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Docter also proved adept at securing funding for research and other projects, a skill that ultimately caught the attention of venture capital firms and led him into the industry 26 years ago.

His technical roots are reflective of Palo Alto, California-based Dell Technologies Capital鈥檚 broader team. Its investors have degrees in fields including electrical engineering, computer engineering, computer science and data science, and many have worked at both large technology companies and startups.

That experience shapes the firm鈥檚 affinity for deeply technical founders and its approach to early-stage investing. When evaluating seed and Series A companies, the team focuses heavily on the potential impact of a technology: what problem it solves, what it could disrupt, and how well it works, often before traditional financial metrics become the central consideration.

Since its 2012 inception, Dell Technologies Capital has invested $1.8 billion across the enterprise stack and saw six high-profile exits at the end of 2025 alone.

In this interview with 小蓝视频色情网页版 News, Docter also discussed how AI is reshaping SaaS and why he doesn鈥檛 believe the business model is headed for extinction. He also shared why he thinks distribution may ultimately separate the winners from the losers among AI startups, and more.

The interview has been edited for clarity and brevity.

小蓝视频色情网页版 News: When you evaluate companies, do they all have to tie into what Dell does?

Docter: Not necessarily. I usually describe it as Dell Technologies Capital having a unique network you don鈥檛 get at any other VC firm. I鈥檓 using my words carefully because I鈥檓 not saying we鈥檙e better. I鈥檓 just saying we鈥檙e unique.

That unique network is that we have access to network and his company network, which has become even more relevant in this AI world but has always been very much in the middle of technology.

We leverage that network in two ways. One is to get another perspective on what鈥檚 going on in the world and understand technology and how it鈥檚 being used. What do Fortune 500 companies want or need? What is asking for? We have that perspective.

If you look at the other side of the coin, those are also the areas where Dell Technologies Capital can best help our portfolio companies. We have this perspective and this network that are really valuable. We can use those to the benefit of our portfolio companies, and that defines our investment philosophy.

classically said, 鈥淚nvest in what you know.鈥� The way I look at it is that we鈥檙e trying to invest in what we know because of who we are, our technical background and our unique network. But if I turn that over, that鈥檚 also where we can help. Invest in what you know, but also in what you can help with.

For founders building deep tech, there鈥檚 a fear of being on the right track, but too early. Some companies have had to wait more than a decade before they really took off. As an investor, how do you evaluate a team that is clearly building technology with incredible potential but is years ahead of the adoption curve? How do you help them survive that stretch of time?

Docter: You asked two questions in one. One is: How do you identify the founders you think can be successful? The second is: How do you keep them alive long enough to get to the finish line?

The answer to the first question hasn鈥檛 changed from how we鈥檝e always thought about it and how venture capital always thinks about it. First and foremost, you鈥檙e really betting on the people. This is a people business. I know you hear that all the time, but you really are betting on the people and the founders.

It鈥檚 not purely about the technical capability of the founders. There鈥檚 definitely an EQ part of the equation, which I think our team is really good at. Our group is good at quickly getting an opinion on a founder and whether he or she is capable. Then we usually spend additional time trying to pressure-test our initial thesis on that founder鈥檚 ability to be agile 鈥� to understand when they鈥檙e wrong and change directions or to be willing to get input from somebody else who might be way less smart than they are but has a different approach or way of thinking about the problem that opens up new avenues.

I think that鈥檚 qualitative. It鈥檚 EQ more than IQ, but a lot of times that determines success. I don鈥檛 think this AI era has changed that. That鈥檚 consistently true.

The answer to the second question is even harder. How do you know if you鈥檙e betting on a deep-tech company and you know going in that this is a five-, seven-, 10-, 15-, or 20-year problem? It鈥檚 really, really hard to sustain that company.

You have to do a bunch of things smartly. You have to make sure you don鈥檛 overspend, because overspending can really kill a startup. You also have to have really good co-investor partners.

We feel like we are part of a venture capital ecosystem, and we always strive to partner and play nicely with others. As Michael says, 鈥淧lay nice but win.鈥� We always try to play nice but win.

It takes a village for these things to work, so it鈥檚 important to have the right constituents and partners around the table who can continue to fund the company for years and years. The timeline is absolutely compressed, so I think it is getting harder for that to happen.

The classic venture playbook often considers first-mover advantage to be everything. But the 鈥渟leeping giants鈥� thesis suggests the second wave 鈥� the companies with the foundational architecture in place when a catalyst like generative AI hits 鈥� may be the ones that win. Is being a first mover still the same advantage it used to be?

Docter: I think it can cut both ways. One of the things we talk about is whether a company is doing category creation 鈥� which means it鈥檚 creating a brand-new category of business or software product that doesn鈥檛 exist today and is going to be huge 鈥� or category disruption, meaning there鈥檚 already a very large category that exists and I鈥檓 going to disrupt it with my technology. I鈥檓 doing something much better, faster, cheaper or stronger.

It鈥檚 important to have a sense of whether a company is doing category disruption or category creation. If you鈥檙e doing category creation, being first means you have to educate everybody. It鈥檚 a heavy lift. It鈥檚 a daunting amount of work, capital and effort that goes into explaining something that doesn鈥檛 currently exist and why it鈥檚 going to be needed in the future.

A lot of times, first-mover advantage isn鈥檛 an advantage there. Category creation is often where the second, third or fourth company hasn鈥檛 had to spend all the effort. They can piggyback off the heavy lifting the first mover had to do.

But in cases of category disruption, I think there鈥檚 value in first-mover advantage. You鈥檙e disrupting a big, existing, multibillion-dollar category and doing something in a new or better way. Being first there is very beneficial.

There鈥檚 a lot of talk about AI agents replacing SaaS models. Do you feel that panic is overhyped? If so, why?

Docter: AI is disruptive to the SaaS world, without a doubt. It鈥檚 disruptive because it will change how software is built and consumed. Maybe even more importantly, it鈥檚 going to change how it鈥檚 priced. The per-seat pricing model is probably outdated and going to die. It鈥檚 going to be priced based on consumption or outcomes.

Everything is disrupted, but I fundamentally don鈥檛 believe all SaaS companies are going to die because of this. I believe the SaaS companies with smart, effective management will look at what AI can do for their businesses, which most already are. They鈥檙e going to adopt it, embrace it, and transform their companies using it. The ones that do will come out the other side as successful companies. They鈥檙e not going to go away.

How they charge and price might be different, but they鈥檙e still going to be the category winner or category leader. Remember that they have some fundamental advantages they can leverage.

One is brand. When I say a big SaaS name, you and I both know it. Pretty much everybody knows 1, and .

They can leverage their brands.

They also have incumbency, meaning they currently have the business. They have customers they鈥檝e sold to for years and years and have long-standing relationships with. If 鈥� and it鈥檚 a big if 鈥� they understand how to embrace the AI transformation that鈥檚 going on and leverage it, there can and will be winners.

There will be winners for sure, or people who come out okay. Without a doubt, there will also be SaaS companies that don鈥檛 make the turn. But is that any different from any other technological or industrial revolution? It鈥檚 always the case that there are a few with good leadership and management who are nimble and agile, even at scale, and they are successful. Others aren鈥檛.

As early-stage founders shift from pay-per-user to pay-per-outcome or other new models, how should they think about their go-to-market strategies and still seem attractive to investors?

Docter: One of the biggest questions we ask early-stage AI founders is: 鈥淲hat is your distribution strategy?鈥� That basically means: How are you going to go to market or get distribution for your product?

Today, that is a harder problem. In terms of differentiating yourself as a startup, I would say its importance has grown.

There will be many people with very good or disruptive technology. The winners are almost certainly going to be the people who figure out distribution first, best or fastest.

If I tie that back to the SaaS question, it鈥檚 clear that some SaaS companies won’t be able to transform themselves organically. They鈥檙e going to need to undergo an inorganic transformation, meaning they鈥檒l have to buy or acquire something that can help their company transform.

If you think about what I just said about early-stage AI startup founders, they need distribution. How do you get distribution? By partnering with an incumbent that has a brand in the space you鈥檙e trying to sell into, sell adjacent to or disrupt.

I think there is a recipe here for SaaS companies to be in acquisition mode for the next six, 12, 18, or 24 months to help transform their companies and make the curve. The incumbent can acquire technology that would take too long to build, and the startup gets distribution that would be much harder for it to build.

Dell Technologies Capital had incredible exit momentum late last year 鈥� including massive liquidity events like , and 鈥� right in the middle of a broader venture liquidity drought. What did you see in those specific businesses or the macro environment that allowed DTC to return capital so effectively when everyone else was stuck?

Docter: I鈥檇 love to say we saw it all coming, but the reality is we can鈥檛 time the market. It just doesn鈥檛 work that way. But we feel lucky that things are lining up the way they have. Netskope, Rivos, SingleStore, and recently, and .

We just try to stay really focused on backing great founders with deeply technical ideas. We鈥檙e investing early and know that sometimes it can take years for the market to fully catch up to what鈥檚 being built. You can see that pretty clearly across the outcomes you asked about. Netskope and SingleStore were at it for more than a decade, building products and businesses until the market met them.

Rivos was a little different. The founders had a strong point of view that a shift in computing was coming fast as AI workloads started to put real pressure on data center infrastructure. They were right and got to a significant exit in just under five years.

We really try not to over-rotate on timing and instead stay consistent in who we back and how we invest.

You鈥檝e talked about looking at startup traction to see whether revenue comes from an “innovation pilot budget” or a “core engineering production budget.” For a startup trying to raise its Series A or B right now, what evidence do they need to show you to prove their AI revenue is sticky and not just experimental hype?

Docter: The biggest question we are asking ourselves today when we talk about making any Series A or B investment is 鈥淚s their revenue durable?鈥� Everyone knows about the complete shift away from the SaaS seat-pricing model.

But what we鈥檙e also seeing is a huge shift away from recurring revenue to something I鈥檓 calling听 鈥渞e-occuring鈥� revenue. I know that鈥檚 not really a word. What I mean by 鈥渞e-occuring鈥� is that, instead of showing multiyear contracts, a lot of revenue is uncontracted, meaning customers are not signing up for annual or multiyear deals. But they are signing up for projects, sometimes very large projects.

My suggestion to startups looking to raise substantial rounds is to show how customers engage and keep coming back for more. The ability to say 鈥渨e got our first deal with in October, and they did a second deal with us in January, and we already did our third deal in March鈥� is very powerful.

Given DTC鈥檚 unique position, how do you advise founders to leverage a corporate venture capital relationship differently than a traditional institutional VC, especially when navigating a rapidly shifting market like this one?

Docter: The answer really is that the investor type is irrelevant. The one thing founders should universally do with every investor on their cap table is ask for more help. 鈥淵ou don鈥檛 get what you don鈥檛 ask for.鈥� I know that鈥檚 an old saying, but it absolutely holds true.

So many founders, especially first-time founders, are reticent about asking for help or advice. Don鈥檛 be. Play to your investors’ strengths and ask them for the help they can deliver. Whether it鈥檚 management advice, introductions to decision makers at Fortune 500 companies, or access to channel sales. Ask!

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Mexico鈥檚 startups led the LatAm pack in Q2 鈥� by a wide margin. The country鈥檚 startups raised $944 million in the second quarter, up 131% compared to $409 million in last year鈥檚 Q2, and up 136% from the $401 million raised in this year鈥檚 first quarter, per 小蓝视频色情网页版 data. For comparison鈥檚 sake, that鈥檚 almost as much as Latin American startups as a whole raised in the second quarter of 2025.

Notably, Mexico-based companies accounted for the region鈥檚 three largest fundraising deals in the quarter ended June 30.

Meanwhile, Brazil-headquartered startups raised $350 million in Q2 2026, down 11% from the $363 million raised in Q2 2025, but up 20% from the $270 million raised in Q1 2026.

In general, a continued boom in late-stage and growth funding helped buoy the region for the period, 小蓝视频色情网页版 data shows. Startups in Latin America raised a combined $1.36 billion across seed- and growth-stage deals in the second quarter, up 47% year over year and 22% from the first quarter.

For perspective, we charted out total investment, color-coded by stage, for the past 10 quarters below.

Of that total, $991 million went into late-stage and growth deals, up 84% year over year and 30% compared to the first quarter of 2026.

Round counts declined sequentially and year-over-year across angel, seed and early stages. (We expect the Q2 deal count to rise somewhat over time, however, as seed rounds in particular are commonly reported weeks or months after they close.)

Table of contents

• Late-stage boom
• Investor POV
• The US-LatAm connection
• Methodology
• Glossary of funding terms

Late-stage boom

There were five nine-figure raises in Latin America in the second quarter, and as mentioned earlier, three of those were by Mexico City-based companies. Interestingly, several of the deals were led by U.S.-based firms.

• In June, payments startup raised $500 million at a valuation exceeding $2.5 billion in a private-equity deal with undisclosed investors.
• In April, digital bank raised $405 million in a Series C round led by Miami-based at a $5 billion valuation.
• And in February, , a startup that operates a pre-owned car marketplace, raised $300 million in a Series F financing co-led by Laguna Beach, California-based and Menlo Park-based . Notably, the round was reported to be a16z鈥檚 largest investment in Latin America and the first in the region for its growth fund.

Other large deals in Latin America in the same period included a $195 million round for Argentinian digital bank in March, led by Germany鈥檚 at a $3.2 billion valuation. And, Sao Paulo-based legaltech startup raised a $100 million Series B led by San Francisco-based

Investor POV

Several investors who spoke with 小蓝视频色情网页版 News described a somewhat slower pace in the region. , co-founder and general partner of New York-based , said the firm remains active, although its investments so far this year have been in U.S. and European companies. It has seen less early-stage fintech activity in Latin America but expects to make new investments in the region, given its current pipeline.

The region鈥檚 underlying fundamentals remain intact and fintech adoption continues to grow, he said.

, principal at Alexandria, Virginia-based , said her firm鈥檚 pace in Latin America has also slowed, largely because it is increasingly investing around global themes rather than individual geographies. As QED focuses more heavily on stablecoins and artificial intelligence, many of the most compelling startups it encounters operate globally, with Latin America representing one of several important markets, she said.

Within Latin America, QED generally invests at the later Series B stage.

, managing partner at Mexico City-based , said the firm鈥檚 investment pace has remained consistent.

Brazil and Mexico continue to attract the bulk of all three firms鈥� activity, but the investors noted that promising companies are also emerging elsewhere in the region.

Armaza cited portfolio successes including Uruguay-based , which was acquired this year by U.S. public company ; Argentina鈥檚 , which raised a $55 million Series C in January; and Venezuela鈥檚 , which serves CFOs and corporate treasury teams.

鈥淚 think this is an underrated LatAm story right now: The periphery is also producing big successes,鈥� he said.

The US-LatAm connection

The investors are also tracking an increasingly fluid relationship between Latin America and U.S. technology hubs.

Hi Ventures, which is now focused almost exclusively on AI applications, has expanded its strategy to include Latin American founders building companies in the San Francisco Bay Area. About half of its portfolio is based in San Francisco, including companies led by founders originally from Mexico, Brazil, Chile and Argentina.

鈥淲e increasingly think of the ecosystem as one connected innovation network rather than separate geographies,鈥� Antoni said.

Armaza has observed a similar trend among both repeat and first-time entrepreneurs who are relocating to San Francisco or New York to build U.S. or global companies from the outset.

鈥淭he talent is still LatAm talent, but the company formation is increasingly happening here,鈥� he said.

The New York-based firm鈥檚 sector focus remains on early-stage companies developing financial and commercial infrastructure.

At QED, meanwhile, stablecoins, tokenization and digital assets have become a substantially larger part of the investment strategy than they were several years ago, particularly at the infrastructure layer. The firm is also interested in the intersection of AI and fintech, including applications that improve financial operations and customer experiences or broaden access to financial services.

Overall investment in Latin America remains far below its 2021 peak and has returned to roughly 2019 levels in both capital deployed and deal volume.

But today鈥檚 market differs from 2019 in one significant respect, Antoni noted: AI allows founders to build companies and reach meaningful milestones with considerably less capital. That shift may particularly benefit Latin American entrepreneurs accustomed to operating with limited resources.

鈥淭he region has always produced resourceful founders, and today鈥檚 environment rewards capital efficiency rather than aggressive spending,鈥� he said.

The threshold for securing funding, particularly at the Series A stage and beyond, has nevertheless risen considerably. Investors are still deploying capital, Antoni said, but more selectively.

Armaza noted that global investors have historically cycled in and out of Latin America, particularly firms without dedicated regional teams or local roots. But the region鈥檚 largest rounds in 2026 have attracted firms including , Andreessen Horowitz, , Allianz X and .

鈥淭his tells you that the best capital in the world finds great companies, regardless of macro sentiment,鈥� Armaza said.

Recent public-market activity by Brazilian fintech companies could further boost the funding prospects for later-stage startups. Gadala-Maria said the fact that two of fintech鈥檚 three IPOs have come from Brazil serves as an important signal that Latin America can produce durable, high-quality fintech companies capable of reaching sufficient scale to enter the public markets.

The newly public companies also provide comparables that investors can use to evaluate the next generation of later-stage Latin American fintech companies, potentially giving them greater confidence in underwriting those businesses. QED has several Latin American portfolio companies that could pursue public listings if market conditions and timing were favorable, Gadala-Maria said.

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• Where Argentina And Spain Are Scoring Startup Goals

Methodology

The data contained in this report comes directly from 小蓝视频色情网页版, and is based on reported data. Data is as of July 9, 2026.

Note that data lags are most pronounced at the earliest stages of venture activity, with seed funding amounts increasing significantly after the end of a quarter/year.

Please note that all funding values are given in U.S. dollars unless otherwise noted.

小蓝视频色情网页版 converts foreign currencies to U.S. dollars at the prevailing spot rate from the date funding rounds, acquisitions, IPOs and other financial events are reported. Even if those events were added to 小蓝视频色情网页版 long after the event was announced, foreign currency transactions are converted at the historic spot price.

Glossary of funding terms

Seed and angel consists of seed, pre-seed and angel rounds. 小蓝视频色情网页版 also includes venture rounds of unknown series, equity crowdfunding and convertible notes at $3 million (USD or as-converted USD equivalent) or less.

Early-stage consists of Series A and Series B rounds, as well as other round types. 小蓝视频色情网页版 includes venture rounds of unknown series, corporate venture and other rounds above $3 million, and those less than or equal to $15 million.

Late-stage consists of Series C, Series D, Series E and later-lettered venture rounds following the 鈥淪eries [Letter]鈥� naming convention. Also included are venture rounds of unknown series, corporate venture and other rounds above $15 million. Corporate rounds are only included if a company has raised an equity funding at seed through a venture series funding round.

Technology growth is a private-equity round raised by a company that has previously raised a 鈥渧enture鈥� round. (So basically, any round from the previously defined stages.)

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The purported deal, which has been rumored for months, is notable not just for its scale 鈥� it would be one of the largest acquisitions of a technology company in recent years 鈥� but also for its highly unusual nature. Privately held startups typically lack the cash, publicly traded shares and debt capacity to acquire their publicly listed brethren.

Of course, Stripe is not just any privately held company. The fintech startup was, until just a few short years ago, the highest valued startup based in the U.S., before being eclipsed on that metric by AI labs and . In February, the company announced it had inked deals with investors to provide liquidity to current and former employees through a tender offer at a $159 billion valuation, which still ranks it as the fourth most valuable startup in the world.

With substantial private capital 鈥� it has raised some $10.4 billion since inception, 鈥斕齋tripe has long been one of the most acquisitive venture-backed startups. It has made since its 2010 inception, according to 小蓝视频色情网页版 data. Only three have disclosed prices: stablecoin platform at $1.1 billion (2025), usage-based billing software startup at $1 billion (2026), and Nigerian payments startup at $200 million (2020).

Stripe鈥檚 M&A pace has also accelerated sharply since 2020, 小蓝视频色情网页版 data shows, with 13 of its 21 acquisitions announced since then.

Its recent strategy appears to be focused on stablecoins and crypto infrastructure 鈥� Bridge, , and 鈥斕齛s well as on billing and money movement through Metronome, payment processing startup and .

If the plan to buy PayPal does go through, it will most certainly make Stripe an even more formidable player in the crowded payments space.

It would also rank as one of the largest acquisitions of a U.S. tech company, public or private, of the past five years, according to 小蓝视频色情网页版 data, trailing only a handful of larger deals including $61 billion purchase of in 2022 and 鈥檚 acquisition of AI coding platform Cursor and its parent, , for $60 billion last month.

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All told, 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. (It鈥檚 important to note that H2 2025 marked the strongest six-month funding period for fintech startups since the second half of 2022.)

Fintech funding in the first half of 2026 also topped the sector鈥檚 investment totals in 2020 and the pre-pandemic year of 2019, though they remain lower than the peak funding year of 2021 as well as 2018.

Historically, the United States has led the globe when it comes to fintech funding, and the first half of this year was no exception. More than 52% 鈥� $15 billion 鈥� of the global fintech funding in H1 flowed into companies based in the U.S. The United Kingdom was the second-largest recipient of capital, with companies there raising a collective $2.7 billion. India came in third, with a total of $1.9 billion raised, 小蓝视频色情网页版 data shows.

Deal count drops

Even as dollar volume climbed, deal flow into venture-backed fintech startups fell fairly significantly in H1 2026, 小蓝视频色情网页版 data shows. The first half of the year saw 1,605 funding deals announced in the sector, a 25.7% decline from the more than 2,161 completed in H1 2025 and down 40% from H1 2024.

Where investors are placing their bets

Active fintech investors who spoke with 小蓝视频色情网页版 News said they see a split market emerging.

In general, the startup investment market has been cleaved into two extremes, with funding either pouring into brand-new companies or concentrating into a tiny handful of larger, established giants, according to , a partner at (Google Ventures).

The fintech sector is following the same pattern, Sakach told 小蓝视频色情网页版 News via email, but its biggest players are using their size in an unusual way. 鈥�2026 marks the definitive ‘lab-i-fication’ of the modern corporation,” she noted, with some fintech platforms using their scale and steady profits to fund experimental new divisions.

Because these companies have significant data and distribution advantages, they are becoming magnets for top-tier workers, according to Sakach. For instance, she said, is now competing directly with top AI research labs for engineering talent, while is using its dominant position to build out new products in enterprise billing and blockchain.

For early-stage startups inside the U.S., the focus is shifting away from copying legacy financial services toward creating entirely new categories.

Wealth management is seeing a massive surge, driven by an influx of assets from a younger generation demanding AI tools, Sakach pointed out.

Fintech startups are also targeting massive, hidden corporate headaches.

鈥淎 50% reduction in global chargebacks is a ~$60 billion opportunity when accounting for both the merchant and banking overhead,鈥� she said.

The biggest shift, however, is happening around artificial intelligence and financial services. 鈥淐oding was AI’s first killer use case; financial markets could be the second, given its extraordinarily broad corpus of data,鈥� said Sakach, pointing to new concepts such as automated hedge funds and prediction markets.

, partner at , said the firm鈥檚 investments into the fintech sector have surged this year, as areas such as money movement infrastructure, stablecoins and tracking of real-world assets on the blockchain draw attention.

鈥淲e’ve never been busier: The quality of founders, the size of the markets they’re going after, and the maturity of the technology being built has never been more impressive,鈥� he said.

Those trends showed up among fintech鈥檚 largest fundraisers last quarter, with companies such as New York-based , which is building an agentic decision platform for banks and insurers, and , an African payments infrastructure startup, clinching some of the period鈥檚 largest funding deals. Both raises took place in June, with Taktile raising a $110 million Series C funding round led by and Flutterwave landing a Series E round of an undisclosed amount that valued the company at $3.2 billion.

Risks and opportunities

Even with a wealth of new opportunities in the sector, investors are also wary of the risks introduced by AI and hype around businesses that don鈥檛 have a clear path toward growth or profitability.

Sakach was particularly skeptical of new stablecoin networks that lack a clear way to get users, personal credit card startups with tough profit margins, and traditional banking software.

The problem with selling software to legacy banks is that their slow buying cycles 鈥渆ffectively break the hypervelocity speed needed for AI-level product evolution,鈥� she said. Instead, Sakach believes that AI tools will likely succeed by embedding highly specialized engineering teams directly into specific business units.

The era of the generic digital bank or basic payment app is largely over, in Overdorff鈥檚 view: 鈥淲ithout a real wedge or distribution advantage, it’s hard to build a durable business there.”

The real value of AI right now is its ability to act as the central engine for financial products rather than just a side feature, Overdorff believes. Startups are using the technology to compress complex underwriting, fraud detection and advisory workflows 鈥渢hat used to take teams of analysts weeks into tasks that happen in minutes.鈥�

As a result, traditional industries such as tax and audit are being completely upended, he said.

Traditional financial institutions, which are usually the slowest to adopt new tech, are finally bringing AI into their core operations, though Overdorff cautioned 鈥渢hat shift is opening up as much risk as opportunity.鈥�

He also flagged the cybersecurity risks associated with the rapid adoption of new technologies and AI into the financial system. 鈥淭he compliance and governance layer becomes just as important as the AI itself,鈥� he wrote.

Mega-valuations keep top fintechs private

While the fintech IPO market was robust in 2025, it has been markedly quieter in the U.S. so far this year. Three fintech companies went public in the first half of 2026, and they were all foreign companies opting to list in New York: Brazil鈥檚 and and Japan鈥檚 . That鈥檚 the same number of finance-related startups that went public in the first half of 2025, when , and made their debuts.

Many of the fintech companies expected to list in 2026 have remained private, often at escalating valuations. That includes fintech giants such as Stripe, , Ramp, , and others that have opted for more private financing, secondary sales or simply waiting out the public markets.

For example, in February, payments infrastructure giant Stripe announced it had inked deals with investors to provide liquidity to current and former employees through a tender offer at a $159 billion valuation. That valuation represented an impressive 49% increase from the $106.7 billion Stripe was valued at in September, when it completed .

In early June, expense management startup Ramp announced a $750 million funding round at a $44 billion valuation, just a few months after raising $300 million at a $32 billion valuation.

The H2 outlook

The trend of capital concentration seen in the first half of the year will continue into H2, Overdorff predicted, with 鈥渕ega-rounds for a small set of category leaders, and a tougher fundraising environment for everyone else.鈥�

And while AI adoption will continue to deepen rather than flatten out, the industry will also be watching the stock market closely. The conversation around IPOs is heating up for mature fintech companies, though Overdorff notes that 鈥渢he timing may hinge on how other high-profile tech IPOs perform this year.鈥�

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To understand how institutional capital is navigating this gap, 小蓝视频色情网页版 News recently interviewed , a partner at . Ranum has spent nearly 15 years at the firm, where he focuses on B2B enterprise software, security and industrial infrastructure. Prior to joining Sapphire, he spent 12 years as a product management and strategy executive at .

His recent investments include core infrastructure plays such as and , as well as the industrial AI platform .

In this e-mail interview, Ranum breaks down how the definition of net revenue retention is shifting, why he believes 2026 will see a historic run of major tech IPOs, and where real enterprise demand is materializing on the factory floor.

This interview has been edited for clarity and brevity.

小蓝视频色情网页版 News: You鈥檝e been at Sapphire for 15 years. Right now, public market software multiples are at decade lows as Wall Street worries about AI disruption, while private AI valuations are hitting record highs. As a growth investor caught in the middle, how are you valuing companies today? Are traditional growth metrics like net revenue retention still the gold standard, or has the math completely changed?听

Ranum: The gap between public and private market signals right now is unlike anything I’ve seen. I think it creates a real opportunity for investors who can make sense of it. Public software multiples have come down hard, while private AI valuations are hitting record highs. Those two things can’t both be right indefinitely, but the fundamentals underneath are holding up. Gross margins, free cash flow, and NDR have actually improved. The market is broadly pricing in disruption risk, but the companies that are genuinely building enterprise value are still being built.

What that means for how I evaluate companies is that I’m spending more time on whether something is genuinely embedded in how enterprises work, not just whether the numbers look good today. NRR still matters. It tells you whether customers are finding real value. But it’s a lagging indicator. What tells me more is whether switching away from a product would meaningfully disrupt operations. If the answer is yes, that’s a more durable signal than any retention metric.

The current regulatory environment has essentially frozen large-scale tech M&A, and the IPO market is sluggish. If the traditional exit pathways are bottlenecked, how does that change the way you underwrite a Series B or C bet? Do companies just have to stay private and build to massive scale longer than they used to?听

Ranum: I鈥檇 push back a bit on the framing that M&A is frozen. Software M&A activity actually picked up meaningfully in 2025, with deal value rising 40% year over year to $334 billion across 678 transactions. We saw that in our own portfolio with over half a dozen acquisitions in the past six months. What鈥檚 changed is the pricing. The valuations are being reset, but the deals are getting done.

On IPOs, I believe 2026 is shaping up to be a historic year, with having gone public, having filed, and reportedly set to file soon. If they follow through, we’re looking at some of the largest IPOs ever over the next several months. That’s a remarkable moment. Below that tier, though, the picture is more nuanced. Companies that meet today’s higher bar will wait for more favorable conditions, likely into 2027 or beyond. That means you have to build accordingly, focusing on margin alongside revenue, so you have real optionality when the time comes. The secondary market also helps, giving companies and their investors more flexibility as they wait.

You used to love investing in what you called 鈥渂oring software,鈥� or tools that quietly automated mundane enterprise tasks. Today, every software company claims to be an AI company. In 2026, does traditional SaaS even exist as a viable investment category anymore, or is a software startup inherently unbackable if it isn鈥檛 AI-native from day one?

Ranum: I don鈥檛 think the narrative is AI vs. SaaS. Instead, it’s AI plus SaaS. The companies that are struggling aren’t struggling because they’re SaaS businesses. They’re struggling because investors are in a 鈥渟how me鈥� era, and they don’t have clear answers yet.

Show me the free cash flow. Show me the path to profitability. Show me how AI is actually helping you win. You can’t get a stock bump anymore just by claiming you’re integrating AI. The market wants evidence of monetization.

The way I think about it is whether a company is building something that fundamentally changes how work gets done, or just layering AI on top of a workflow that a human is still doing. We used to back systems of record and workflow companies where the human was doing all the work. Now we’re in a position where the system itself can come in and actually do some of those tasks. That’s a different category of value entirely, and it changes what we look for. The bar has moved, but the opportunity is very real for the companies that can clear it.

Your core thesis is that the LLM stack is fracturing into distinct, standalone billion-dollar layers, such as orchestration (LangChain) and identity (WorkOS). But we鈥檙e seeing a massive border war. Big model providers like OpenAI are building their own tools, and data giants like are buying up security tools. How do standalone startups protect their turf when giants encroach from both sides?

Ranum: Both fracturing and consolidation are happening simultaneously, and I think that’s actually the right way to think about it. The moat isn’t about being first in a category. It’s about becoming genuinely embedded in how enterprises work. The companies I’m most excited about are the ones capturing orchestrated workflows in which the enterprise’s actual processes run through the product. That makes them very hard to displace, regardless of what the giants are building around them.

Because of your background at SAP, you know how enterprise buyers think. Right now, CFOs are looking at massive AI pilot bills and demanding to see actual ROI. When a startup is pitching an enterprise on a software governance or security tool, how do they defend that line item to a cynical CFO before the enterprise has even fully figured out its core AI strategy?听

Ranum: What we consistently hear from buyers is that trust has become what actually separates the market. Security, governance, compliance, and auditability aren’t nice-to-haves anymore. They’re what make an AI deployment defensible when the CFO or the board asks hard questions.

And cost predictability is right alongside that. We’re in an era of greater focus on ROI, and enterprises want to know what this will cost them at scale before they commit. The vendors that can answer that question clearly are winning deals over the ones that can’t.

It feels like Silicon Valley is obsessed with the glamour of humanoid robots right now. Meanwhile, Sapphire鈥檚 big bets in this space, like Tractian, focus on practical, unglamorous industrial AI and predictive maintenance. Are humanoid robots an expensive venture capital distraction right now? Where is the actual, contract-signing enterprise demand on the factory floor today?听

Ranum: The near-term ROI story is in constrained, high-value industrial settings such as packing, picking, inspection, and maintenance. These environments have clear labor economics, manageable deployment risk, and real buying cycles. That’s where the contracts are getting signed today.

Our portfolio company Tractian is a good example of what that looks like in practice. Unplanned downtime costs the world’s 500 largest companies roughly 11% of their revenue annually, which is a massive, measurable problem.

Tractian addresses it directly by combining sensor hardware with AI that detects early warning signs of equipment failure. The value proposition is concrete before you sign the contract, and the platform gets smarter the longer you use it. That’s the kind of embedded, compounding value we look for.

The humanoid era will come, but the gradient approach beats the all-or-nothing bet for near-term value creation. Start with specific, well-defined tasks where the payoff is obvious and work from there. The market is ready for that today.

Heavy industry and manufacturing are notoriously slow to change. A startup can’t just plug a modern AI API into a 30-year-old machine on a factory floor. For founders trying to build in the industrial tech space, is the winning strategy to build entirely new autonomous hardware, or is the bigger venture opportunity in retrofitting the world’s existing infrastructure with smart software?听

Ranum: I believe the winning strategy is smart software layered on top of existing infrastructure rather than replacing it. Factories aren’t going to rip out 30-year-old machines because a startup has a better alternative. That’s just not how it works. The opportunity is in making those machines intelligent.

That said, the hardware-plus-software combination really does matter. You can’t get the data without the sensors. But the durable value is in the software layer that keeps learning over time. That’s where I鈥檓 focused.

In pure software, a buggy AI agent might mean a broken spreadsheet or a weird email draft 鈥� annoying, but fixable. In robotics and industrial tech, a mistake means a factory line shutting down or a broken multimillion-dollar asset. From a venture perspective, how much harder is it to scale a robotics startup when the cost of product failure is so high in the physical world?听

Ranum: I’d actually reframe the question. The cost of failure in physical environments is what makes the value proposition defensible. When the downside of getting it wrong is measurable, the upside of getting it right is equally concrete. You can walk into a sales conversation and show a customer exactly what prevention is worth before they sign anything. That’s a different conversation than selling software, where ROI takes quarters to show up.

From a scaling perspective, the key is discipline about where you deploy first.

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Smith spent eight years on active duty, serving as a technical product manager building satellites and software for national defense for the and . When he returned home from a seven-month deployment, Smith looked at the data surrounding community college transfers to four-year universities and realized how low the success rates were.

鈥淵ou have a higher chance of success [of attaining a bachelor鈥檚 degree] by pursuing a military academy 鈥� than if you go to any community college 鈥�,鈥� Smith said in an interview with 小蓝视频色情网页版 News. “That didn’t really make sense to me.鈥�

He then entered graduate school and launched in 2019 while working on his MBA听at .

Now, the Los Angeles-based startup tells 小蓝视频色情网页版 News exclusively that it has secured a $13.3 million Series A funding round to scale its AI-native platform, which automates the manual back-office workflows that can slow down university admissions.

led the financing, which included participation from , , , , , , 听and others.

The new capital brings EdVisorly鈥檚 total funding to about $22 million and marks a significant valuation step-up from its previous tranches, according to CEO Smith.

The startup鈥檚 funding comes amid an overall downturn in investment in the sector. Venture funding to education-related companies has in recent years come in at a fraction of the sums such startups raised during the pandemic peak, when investment topped out at nearly $20 billion in 2021. Through the first half of 2026, however, edtech and education-related startups have raised just under $1.8 billion globally, . That鈥檚 below the $2.5 billion raised in the first half of last year, but a notch higher than the $1.4 billion raised in the second half of 2025.

Automating the back office

EdVisorly aims to take the slow, manual paperwork out of the college admissions and transfer process.

The software doesn’t decide which students get accepted and does not serve as a gatekeeper, Smith emphasized. Instead, he said, it is designed to handle the tedious, behind-the-scenes administrative tasks that bog down university staff.

The driver behind EdVisorly鈥檚 recent growth is its proprietary platform, EddyAI. The tool works to automate repetitive back-office workflows in the admissions and enrollment process, including tasks such as reading student transcripts and recalculating GPAs based on a university鈥檚 specific criteria.

“We automate a lot of the backend processes,鈥� Smith said.

For the 10.5 million community college students in the U.S. trying to transfer to a four-year university, the process is usually a total guessing game. EdVisorly aims to bridge that gap.

Applicants are able to upload their transcripts into its platform to run an unofficial credit evaluation. The app automatically reads their classes and matches them against university requirements. Even before they ever speak to an admissions counselor, families can learn exactly how their credits stack up, what a degree will cost, and how many semesters a student would have remaining.

On the university side, registrars use the same technology to process official transfer credits and quickly build new credit-matching rules, bypassing a process that historically required a human to review every course.

“The technology actually reads the transcript, it takes that data from the transcript, and it compares it to the equivalencies that the school has,” Smith noted. “There’s kind of an infinite number of 鈥� transferable credits and courses that could exist across the United States.鈥�

The startup鈥檚 next iteration will focus on organizing all of that data, 鈥渟o that there’s no mystery as to whether a student’s credits will transfer,鈥� Smith said.

Both sides of the market

EdVisorly counts more than 100 colleges, universities and higher education systems as customers. Its roster includes institutions such as the , the , and . It has helped over 250,000 students since its inception, per the company.

The startup sells directly to higher education institutions via a B2B subscription model. Smith uses a management framework from his military days to run deployments: People come first, clear policies come second, and technology sits at the bottom as a tool to support them.

“We believe in not the concept of replacement, but truly repurposed,” Smith said. “Technology can best be implemented when you have people who are willing to adopt, and they’re innovative, and they’re excited.”

Its Series A funding will go toward upgrading the platform’s core engineering infrastructure and adding more UX designers to polish the student-facing app. Currently, the company has nearly 50 employees.

, managing partner and founder at Breachway Capital, said he is most excited about EdVisorly鈥檚 鈥渂readth of impact.鈥�

鈥淭his is not a solution that optimizes for one side of the market at the expense of another,鈥� he wrote via email. 鈥淚t drives real efficiency and tangible value for institutions while delivering a meaningfully better experience for students navigating one of the most important decisions of their lives. That is a truly unique value proposition.鈥�

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• Edtech-Specific Startup Funding Stays Low

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Created in partnership with the European angel fund , the initiative gives Omnea employees who have completed five years of service a chance to pitch for $250,000 in seed funding to launch their own companies.

The initiative doesn’t just aim to discourage employees from hiding their entrepreneurial ambitions from leadership but actively supports them.

“Starting a business, you don鈥檛 want to speak to investors who you don鈥檛 know. You want to speak to people you know and trust, who want you to succeed and know what they鈥檙e talking about,” said , founder and CEO of Omnea, in an exclusive interview with 小蓝视频色情网页版 News explaining why the company decided to start the initiative. “And ideally, you want to get the advice of your colleagues. But it鈥檚 always taboo 鈥� telling your colleagues you want to go start something and quit your job. I don鈥檛 think it needs to be.”

Eligible employees present their concepts in a single 30-minute pitch meeting to Freeman and Firedrop founder , with final investment decisions delivered within 24 hours. Alongside capital, accepted founders receive dedicated office space, operational support and ongoing coaching from Omnea鈥檚 executive team.

How the funding works

To keep the process simple for first-time business owners, the fund avoids strict, rigid formulas. Omnea has set a rough guidance benchmark of $250,000 against a $10 million valuation 鈥� which would convert to a 2.5% equity stake 鈥� giving new founders a sensible baseline so they aren’t left guessing about early-stage pricing.

However, the program is built to be highly flexible. Founders can instead opt for an uncapped, discountless Simple Agreement For Future Equity () note. Under this structure, Omnea provides $250,000 upfront with a valuation to be determined, leaving the final equity percentage open until the startup raises its next major round of capital.

鈥淭he only reason I’ve set guidance is so people know roughly where to start,鈥� Freeman said. “For 2.5%, we’re not causing dilution issues, and then the rest is up to them.”

The initial $250,000 is intended as a 鈥渇irst check鈥� or seed funding. It provides just enough runway for teams to build an initial product and establish a personal salary, removing the financial fear of how to pay bills the day they stop working at Omnea.

“The fund is set up to be able to write lots of checks, and they don鈥檛 all need to land,鈥� Freeman notes. 鈥淚 suspect Omnean founders will raise big seed rounds of a few million dollars. So the initial $250,000 is just to get them on the journey there.鈥�

Eliminating the 鈥榮ide hustle鈥� friction

The structural flexibility mirrors the program’s primary cultural goal: removing the awkwardness of the hidden corporate side hustle. Traditionally, employees with entrepreneurial ambitions secretly grind on side projects, creating an environment that is healthy for neither their current job nor their future business.

The Future Founders Fund replaces that secrecy with transparency, allowing employees to openly discuss their ideas with leadership, set a clean transition timeline, and map out their launch.

鈥淪omebody wants to start a business, but they can’t tell their employer or their team, so they’re awkwardly trying to have side hustles, and it’s not good for their business or their job,鈥� Freeman said. 鈥淭hat’s not a good outcome, and this will solve that, because they can talk about it, they can have a timeline, they can plan.鈥�

Sourcing capital from a network of elite operators

Rather than drawing on traditional institutional capital, the fund is fueled by a specialized pool of more than 150 angel investors, tech founders and executives who have backed the project individually.

The advisory and investor network features prominent global tech executives, including former COO , former COO , CEO , and CTO .

鈥淭hese people aren鈥檛 doing it for money 鈥� they鈥檝e made their money. Many of them are billionaires already,” Freeman told 小蓝视频色情网页版 News. “They do it because they enjoy it and want to give back and help the younger generation.”

Omnea chose to partner with Firedrop to ensure the fund received dedicated, professional management, leveraging Invernizzi鈥檚 existing network and infrastructure designed to support founders at the earliest stages of ideation, before business concepts are even fully formed.

While no employees have formally entered the program yet 鈥� as the 4.5-year-old startup approaches its first cohort of five-year veterans 鈥� four employees have already signaled their intent to leverage the program to launch future ventures. Two of these individuals have run businesses before, while two are first-time founders. According to Freeman, 鈥渂ased on their profiles, they鈥檇 have no difficulty raising money anyway.鈥�

An internal ecosystem of 鈥榝uture founders鈥�

The fund serves as an aggressive recruitment and talent-density strategy, signaling that the company takes its team’s long-term career arcs seriously.

鈥淧ersonally, if I thought that I wanted to be a founder in the future, I would want to join a company that shows it is going to support me as a founder,鈥� Freeman said. “Showing that we will invest time, energy and money is a pretty strong signal that we鈥檙e serious about our people.听 I think it also shows that we take a long-term view on things.”

Currently, roughly 15% of Omnea鈥檚 200-person workforce across London and New York consists of former founders, including executives who previously built venture-backed startups like , and . The company’s rigorous talent screening process historically involved interviewing over 10,000 applicants to secure its first 50 hires. Freeman believes it doesn’t make sense to wait until the company grows to 1,000 employees to launch this initiative, as early-stage environments are precisely where great founders are built.

By openly incentivizing employees to eventually leave and build their own enterprises, Omnea is explicitly optimizing for high-autonomy, founder-type personalities.

鈥淔uture founders work harder, care more and think outside of the box,鈥� Freeman said. 鈥淚 think these founder-type folk have the mindset that they will do whatever is needed to get to a successful outcome. Normal people may quit when things get tough; founder-type people lean in. They are energized by solving hard problems. Many of them actually like chaos.”

This mentality manifests in Omneans catching flights on short notice to assist clients with key meetings and building deep, authentic relationships that cause stakeholders to maintain ties with the team even after leaving their respective companies. Internal operations are structured to mirror this entrepreneurial friction.

The organization maintains a flat meritocracy in which product managers pitch roadmaps to cross-functional internal teams, engineers set their own deadlines based on direct commercial context, and go-to-market teams operate as localized chief executives.

From the Tessian blueprint to the McKinsey Model

The inspiration for the program stems directly from Freeman’s personal experience as part of the founding team at email security company . When he left Tessian to go out alone, he found the transition significantly more complex and isolating than necessary. While Tessian鈥檚 founding team supported him as angel investors, the lack of formal structure meant he had to figure out the mechanics of quitting, fundraising and building pitch decks in an unstructured environment.

鈥淭he same was true for , co-founder of . And (), (), and (). All of these founders came out of Tessian,鈥� Freeman pointed out. 鈥淲e should have made it easier for people to found their own things. That鈥檚 why I鈥檓 doing it at Omnea.鈥�

Freeman is entirely unconcerned about losing top talent to this pipeline, noting that if an individual is committed to entrepreneurship, they will inevitably leave anyway. The fund simply captures and backs that drive rather than fight it.

鈥淚f people are going to build a business, they鈥檙e going to build a business. My setting up this fund isn鈥檛 pushing them out by any stretch,鈥� he said. 鈥淚n fact, if you鈥檝e done five years at Omnea, the reality is that you鈥檙e highly paid and have lots of equity.”

Ultimately, Freeman emphasizes that this initiative is absolutely not philanthropy, but rather a strategy designed to deliver exceptional financial returns by backing elite operators. He points to as an architectural parallel, noting how it invests heavily in its thriving alumni network.

“McKinsey has a similar view with their alumni. They invest heavily in them, and people are part of that McKinsey network for life,鈥� he said. 鈥淭hey have some business objectives there, but actually, a more buoyant entrepreneurial ecosystem helps everyone. I鈥檇 be so proud if Omnea can fuel that.鈥�

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First, San Diego-based announced its of a Palo Alto, California-based software startup focused on making it easier for developers to run AI models across different types of computer chips.

At the same time, reports emerged that chip startup is finalizing an $800 million funding round led by , valuing the company at $10 billion. Together, the two deals underscore a growing reality in tech: As hardware remains scarce and expensive, the software layers that connect these chips are becoming just as valuable as the silicon itself.

Watching these shifts unfold firsthand is , a managing partner at who led early investments and holds board seats at both Modular and SambaNova.

Munichiello brings a pragmatic operational background to tech investing, having served as a captain and paratrooper in the U.S. military before transitioning to the private sector. He later worked as an early executive at , helping scale the warehouse automation company through its $775 million acquisition by .

With a background in mathematics and computer science from and an MBA from , Munichiello has spent his venture career focused on core software infrastructure, developer tools and data systems, including early backing of companies such as , and .

In this interview, he discusses the mechanics behind the Qualcomm-Modular deal, the practical realities of managing hardware scarcity, and what the current wave of consolidation means for the future of independent startups.

This interview has been edited for clarity and brevity.

小蓝视频色情网页版 News: The acquisition of Modular by Qualcomm highlights a massive push to decouple AI software from hardware fragmentation. Does this signal that the ultimate value in the AI stack is permanently shifting away from proprietary hardware architectures and toward developer-friendly software layers that can run across any compute environment?

Munichiello: The types of hardware required for AI in the future are becoming heterogeneous. Originally, it looked like it was just GPUs from , and then also GPUs from and other players. But now, the direction hardware is going is toward “disaggregated inference,” which basically means splitting apart the different compute used for different parts of answering a question when engaging with a model.

It increasingly looks like there will be three types of chips used in disaggregated inference: an AI-specific chip, a CPU and a GPU.

For a player like Qualcomm, all three of those components are present, so they need a software layer that sits across them. Everywhere else, Nvidia included, they usually sell alongside CPUs and accelerators, and there hasn鈥檛 really been a software solution that works across all of those.

When did you first start investing in this wave of AI infrastructure and semiconductors?

Munichiello: We鈥檝e been investing in AI since 2016, starting as early as a company called , which was first company, sold to , and became part of the Siri team. After that, we invested in , co-founded by , which was later sold to and became an important part of its stack. HPE actually went on to be the compute partner for and worked very closely with as well.

We also got excited about semiconductors early, long before this current wave, when we led the Series A for SambaNova. I first met that company when it was just three people and a slide deck. We led that round in December 2017 鈥� after led the seed investment 鈥� and I鈥檝e sat on the board since. That initial investment was $15 million at a $480 million valuation.

It seems like a lot of legacy chip giants and major cloud providers are aggressively buying up infrastructure startups. What does this consolidation mean for early-stage founders? Are we entering an era where standalone startups need to plan for an early acquisition, or is there still a path to an independent IPO?

Munichiello: There is definitely a path to an independent IPO. showed that trajectory beautifully, and I’m really happy for and that team. There is absolutely a trajectory to build big, standalone businesses because the demand for compute is completely off the charts. We can’t make semiconductors fast enough, nor can .

Everyone is trying to find extra capacity by making everything more efficient. Technology often emerges with a big boom in mass demand and high prices, and then we figure out how to make it cheaper. We are in that efficiency step right now. Demand for inference is everywhere, from medicine and law to coding, customer support and finance.

We are trying to squeeze every last bit of value out of chips. Squeezing that value comes from using multiple types of chips: using cheaper CPUs when we can, GPUs when we need them, and the most expensive chips only for the most complicated parts of the process.

We are also evaluating software across the stack to ensure every aspect of these queries is as efficient as possible. It鈥檚 not surprising that there are a lot of acquirers. The universe of buyers has expanded from just semiconductor companies buying other semiconductor companies to software companies, hyperscalers and model companies buying chip companies, too. Amazon has Trainium and Inferentia; has Maia; has the TPU, and every big tech company wants to be able to say it has a chip.

How does the rise of open-source models shift this dynamic?

Munichiello: The universe of potential buyers expands even larger when open-source models become prolific. In the Qualcomm announcement, they talked a lot about their enthusiasm for open source 鈥� not just keeping Modular open-source, but for models to be open-sourced. When that happens, instead of enterprise companies paying hundreds of millions of dollars to model providers to do inference, the companies themselves will own their models and run them on their own hardware.

So you firmly believe that IPOs are not totally off the table for early-stage tech and hardware companies?

Munichiello: Not at all. Look at , which is highly hardware-intensive. I think we will see many IPOs here in the next six months. I know of at least 15 or 20 companies that are planning to go public, so it is going to be a very busy period.

In a market where valuations are multiplying rapidly based on technical metrics like chip throughput, how are you able as an investor to separate real, sustainable product-market traction from early hype?

Munichiello: There are a lot of AI companies getting valuations that are disconnected from the business outcomes they are driving. True traction comes down to quarter-over-quarter execution, hitting sales demands and actually fielding physical systems for customers.

A company becomes highly attractive to investors when it delivers a massive volume of technology into production environments 鈥� like data centers for major enterprise brands and devices we use every day.

That, combined with incoming demand from “Neo-Clouds” (new data centers built specifically for inference), shows real traction. These players are looking for any chips they can get their hands on, and the concept of disaggregated inference 鈥� combining three different chip types to lower the total cost of ownership 鈥� is highly compelling. It also alters the competitive landscape; it shows that the market isn’t just a runaway race for one dominant player, but an opportunity for CPU providers to catch up as well.

GV has a track record of backing foundational tech long before the generative AI hype cycle. How has your framework adapted now that AI infrastructure capital requirements have skyrocketed? When a startup needs hundreds of millions just to compete at the frontier, how do you maintain a focus on the team and relationship without getting bogged down by the sheer scale of capital?

Munichiello: It has always been complicated to start from scratch and build a meaningful, generational company. We are not in the business of momentum investing. We don’t invest in something just because we think it will be marked up by other investors over time. We look for fundamental technologies and consequential businesses that can stand on their own.

When we met Modular, it was just Tim and Chris with an idea, and we convinced them to take our $23 million investment. At the time, we were nervous about valuing the company at more than $80 million or $90 million, and it ended up getting valued at $155 million in that first round.

We took 15% of the company right off the bat in a round that felt way out over its skis for that moment in the world. But they hired an amazing team of compiler engineers, started growing and built in a space that became the most strategic in all of AI.

We value different companies based on their specific markets. Some are incredibly capital-intensive and require billions of dollars, meaning we can’t do it alone. As an investor, we must bring our network and a syndicate of other investors who can write hundreds of millions of dollars in checks.

Software companies can move a bit faster, make more mistakes and pivot. In hardware, if you tape out a chip and it doesn’t work, you are set back for years and have to raise significantly more money. It鈥檚 much more binary when it comes to the physical world. A hundred million dollars goes a lot further in software because you can always optimize your token usage or engineering to shift directions, which is incredibly hard to do in robotics or hardware.

This acquisition represents a massive return on your initial investment. What does this success say about your broader investment philosophy?

Munichiello: It鈥檚 a fantastic outcome 鈥� a 27x return on our initial investment and roughly 10x on our total dollars invested. But we aren’t a firm that just leads a Series A and then steps back. We look to write massive checks and co-lead later rounds, especially when things get difficult.

It is inevitable that every company will hit a wall at some point 鈥� whether due to macroeconomic factors, team dynamics or customer challenges. We call these “crucible moments,” and they are what make companies truly interesting. In an internal email I sent to our team, I talked about loving curveballs. We are used to things going sideways, and that’s when we really step up and help our companies. We like to find these incredibly hard problems, back exceptional people with the character and grit to survive those moments, and help them build standalone businesses.

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小蓝视频色情网页版 data tells us Black startup founders still receive only a tiny sliver of venture funding. What the numbers don鈥檛 tell us is why investors continue to overlook those entrepreneurs, and more importantly, how the industry can improve the odds for Black and other underrepresented business leaders.

To better understand what’s driving the persistent gap 鈥� and what it will take to close it 鈥� 小蓝视频色情网页版 News spoke with six venture capitalists who actively back Black founders about where they believe the ecosystem continues to fall short and how it can improve outcomes.

While they offered different perspectives, several themes emerged: Venture firms need to broaden the networks they rely on to source deals, founders continue to face structural barriers long before they pitch investors, and lasting progress will require changes from both investors and entrepreneurs.

Expand beyond familiar networks

Underrepresented founders face distinct pressures as the venture industry retreats to its traditional networks, according to partner , who said the pullback in funding to Black founders overlooks where investors can discover market-outperforming businesses.

鈥淭he bar for all founders has gotten higher in recent years, and I don’t necessarily think that’s a bad thing,鈥� she said, pointing out that the surplus of capital during the previous market peak meant startups that probably should not have been funded received investment anyway.

Still, the subsequent market correction has triggered a familiar defense mechanism among institutional investors, she said. 鈥淲hen things get hard, it’s human nature to revert to what you know and what feels safe,鈥� Kidder said. 鈥淯nfortunately, that means back to the same networks, and so there’s been extra pressure on underrepresented founders.鈥�

Instead of viewing diversity through a philanthropic lens, Kidder argues that the current environment means venture investors need to look outside of their conventional circles to beat the market. 鈥淎lpha is more likely to be found outside that comfort zone in founders who bring different perspectives and solutions to the table, especially in healthcare,鈥� she said.

To date, Boston-based Seae has backed nine Black startup founders. Kidder notes that those entrepreneurs, like with the rest of the founders in the firm鈥檚 portfolio, bring 鈥渆xtraordinary grit, experience and passion to building sustainable solutions for the market.鈥�

, partner at , agrees that venture firms’ existing networks tend to limit who gets funded and he argues that expanding those networks requires deliberate action. To that end, his firm several years ago launched Lobby: Elevate, an event designed to support underrepresented startup founders.

The entrepreneurs who attended the firm鈥檚 Founders of Color Summit demonstrate that 鈥渨hat is lacking for Black founders is opportunity and investment, not talent,鈥� he said.

Hornik said more venture firms need to intentionally create opportunities to meet founders they would not otherwise encounter, whether through events or by bringing more investors into direct conversations with underrepresented entrepreneurs.

Simply agreeing that bias exists, he said, won’t change investment outcomes.

“I don’t think there is a single white VC I respect who has funded a large cohort of Black founders, myself included,” Hornik said. “I can certainly do better.”

Because venture investing is inherently subjective, Hornik argues investors must actively push back against the implicit bias that can shape sourcing and partnership discussions. The funding statistics for Black founders won鈥檛 change unless investors are 鈥渋ntentional about the problem,鈥� he said.

That view is echoed by , co-founder and general partner of , who believes that the many public commitments made by firms to back more Black founders in the summer of 2020 following George Floyd鈥檚 death were 鈥減erformative and not permanent.鈥�

The 鈥渦nironic and quick鈥� retreat in the years since has been actively harmful to Black founders, he said. Going forward, the industry needs to make truly structural changes to see long-term improvement.

鈥淭he warm intro network is the biggest filter in venture, and it鈥檚 viewed as an asset, not a structural problem,鈥� he said. 鈥淚f you’re inside, you get meetings. If you’re not, you don’t, no matter how strong the company is. Pattern matching gets the headlines, but it’s downstream of who walks through the door.鈥�

Rhodes argues that many venture capital funds treat sourcing as a “passive intake.鈥�

In contrast, funds that systematically expand their top-of-funnel reach beyond traditional networks tend to discover companies that competitors miss.

That鈥檚 not a diversity initiative, he noted, but a distinct 鈥渋nformation advantage.鈥�

Break down barriers before the pitch

For , managing partner at , a quality often overlooked by investors is resourcefulness. Having built a startup himself before becoming an investor, Johnson said many Black founders learn to build high-quality businesses with far less capital than their peers.

鈥淏lack founders innovate at the same quality and scalability as others, with a fraction of the capital,鈥� he said.

Ironically, that same scrappiness often stymies Black founders during the pitch process, according to , founder and general partner at and the author of

O鈥橠onnell argues that many of the biggest obstacles emerge well before founders ever walk into a pitch meeting, though they continue there.

Venture firms recruit heavily from elite universities where Black computer science students make up only a small share of the student body, he said, while the broader tech ecosystem in Silicon Valley can feel unwelcoming to many Black engineers.

鈥淪ilicon Valley itself is alienating,鈥� O鈥橠onnell said. 鈥淭he Bay Area has no meaningful Black community, the interview panels are all-white, the lunchroom is all-white, and the neighborhoods are all-white. Qualified Black engineers rationally choose to work somewhere they won’t be isolated.鈥�

鈥淣ot wanting to be the only Black person in the room isn’t a failure of ambition,鈥� he added. 鈥淚t’s a reasonable response to a visible signal about what the environment will be like.鈥�

That disparity continues into the fundraising process itself, according to O’Donnell, who argues that underrepresented founders often ask for less capital and make more conservative projections because they’ve spent their careers facing greater scrutiny and are often expected to justify every dollar.

Venture investors, however, are by their very nature looking for founders who pitch ambitious, risky, fund-returning visions.

As one example, O’Donnell recalled a Black urban mobility startup founder whose pitch to VCs became caught between describing the large company he hoped to build and the modest business he had already created on the path to profitability.

The founder was 鈥減itching the way someone pitches when they’ve been taught that financial responsibility matters, but he was pitching in front of people who don’t care about financial responsibility at all,鈥� he said. 鈥淭hey care about whether 鈥� if the risk was ramped up high enough 鈥� this could return a fund.”

Change the funding playbook

Many investors and Black founders who spoke with 小蓝视频色情网页版 News came to a similar conclusion: Improving venture outcomes for underrepresented founders will require changes on both sides of the table, with investors broadening who they meet and founders building businesses that make it increasingly difficult to overlook them.

For venture firms, that starts with intentionally expanding how deals are sourced, rather than relying on warm introductions and longstanding networks.

, general partner at , argues that the responsibility for changing outcomes rests primarily with the institutions that control the vast majority of venture capital.

鈥淰enture firms led by white people and ‘model minorities’ should be asked the hard questions,鈥� said Robinson, whose early-stage venture fund is designed to back Black entrepreneurs. 鈥淭heir track records should be examined. Their implicit and explicit bias should be called out and they should have to answer for it.鈥�

Robinson believes firms need to do more than wait for investment-ready companies to appear. Instead, she said, they should actively expand their sourcing pipelines and create programs that help founders reach the stage where they’re ready to raise institutional capital.

For founders, her advice is pragmatic. Entrepreneurs should spend less time chasing investors and more time building businesses customers want, she said.

“Black founders need to relentlessly pursue sales and customers as they have been indoctrinated to pursue investors,” she said, arguing that strong commercial traction gives investors “less of a choice but to invest” once the metrics become undeniable.

Rhodes, the general partner at Fictive Ventures, also offered a reminder that venture capital is only one potential financing path. Before pursuing that path to funding, startup founders should first determine whether their business actually fits the venture capital model and the growth expectations that come with it, he said.

The venture model is built around risk-taking, he noted, but there鈥檚 a double standard for white and non-white entrepreneurs: 鈥淎 Black founder’s first failure gets treated as confirmation,鈥� he said. 鈥淎 white founder’s first failure gets treated as experience.鈥�

Still, if a Black founder is determined that venture capital is the right financing source, he or she should recognize that investors are buying a stake in the future outcome of the business.

That means personal backgrounds, stories and community impacts only matter to investors in so much as they serve to predict a financial return. 鈥淣obody is investing in you just because you’re Black,鈥� Rhodes said.

In fact, he believes that investors who frame their investment decisions around founder identity are typically the first to 鈥渄isappear in a downturn.鈥�

Instead, Rhodes advises founders to focus on finding and building for the investors who 鈥渢ruly understand鈥� the business and are committed to helping build it over the long term.

That鈥檚 a view echoed by Kidder. 鈥淔ocus on the build, get creative to show early proof points 鈥� build and leverage relationships where you’ve built trust and delivered results to seek out investors who believe in you and what you’re building,鈥� she said. 鈥淎nd, don’t let the stats dissuade you from the dream. Trust your gut and focus on delivering sustainable results.鈥�

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• 鈥楾his System Wasn鈥檛 Built For Me鈥�: Black Founders Became Investors To Change Venture Capital

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