All told, startups in Latin America raised a combined $1.3 billion across seed- and growth-stage deals in the three-month period ending Sept. 30. That was up 26% year over year but down 9% from the second quarter.

For perspective, we charted out total investment, color-coded by stage, for the past 12 quarters below.

Of the quarterly total, $757 million went into late-stage and growth deals, up 74% compared to the $435 million that flowed into such deals in the third quarter of 2025. However, that is down 21.3% from the $962 million in late-stage and growth rounds raised by LatAm startups in the second quarter. (Although it’s worth noting that Q2 2026 represented the most raised at that stage since the second quarter of 2022.)

Mexico startups have raised $1.52 billion in venture funding during the first three quarters of 2026, per ������Ƶ data. Notably, that’s about 40.7% more than the $1.08 billion Brazil’s startups raised in the same period. This is unusual as Brazil has historically been the largest recipient of venture funding in Latin America.

Still, Brazil continues to attract a broad range of investors.

“Over the past year, we have seen investments into Brazil from firms including , , , and ,” , managing partner of , told ������Ƶ News. “For several, this marked either their first investment in Latin America or their first in a long time.”

, Endeavor Catalyst’s vice president and head of Latin America, noted that Mexico drew more venture funding in the first half of 2026 than Brazil. But much of �ѱ�澱����’s funding went to a few startups, he pointed out, while Brazil recorded many deals.

“Investors are concentrating on a few Mexican winners, while Brazil retains the breadth,” Piquet said, adding that Brazil also leads in realized exits.

Table of contents

• Outsized rounds
• An uptick in seed funding
• ‘Another rediscovery moment’
• Methodology
• Glossary of funding terms

Outsized rounds

Several mega-raises took place in Latin America in the third quarter. And notably, the two largest funding deals were not for companies in Brazil or Mexico, which have historically raised the largest share of venture capital in the region. They also weren’t to fintech, which typically has the most funding recipients in the region, but rather to energy-related startups.

, the Chilean project company for ’s Black Giant lithium project, raised $225 million in a July round at a reported $900 million valuation. And Colombia’s , a clean energy company that builds and operates solar power systems for homes and businesses, landed a $129 million Series C in August at a reported $600 million valuation.

�ѱ�澱����’s , an AI-powered financial services company, raised a $125 million Series C in September at a $1.6 billion valuation. led the financing, which included a senior debt funding facility provided by .

And in August, Brazilian fintech brought in $106.9 million in an equity and debt seed round at a $626 million valuation.

Also in August, Brazil’s , an AI-native wealth advisory company, landed $85 million in  what ������Ƶ shows is the largest seed funding deal ever raised for a Latin American startup. Founded by , former CTO of , and , founder of , the startup is backed by ,,, and .

An uptick in seed funding

Latin America experienced a marked surge in very early-stage funding totals in the third quarter, largely thanks to the seed rounds mentioned above.

Of the $1.3 billion raised by Latin America’s startups in the third quarter, about 20.5% — or $266 million — was raised across the angel and seed stages.

That’s up 128% from the $117 million raised across those stages in the second quarter of 2026, and up 62% from the $165 million in the same quarter last year.

Just over 22%, or $288 million, was raised at early stages, down 18.9% from $355 million in the second quarter and 34% from $437 million in the same period last year.

We expect the Q3 deal counts to rise somewhat over time; however, as seed rounds in particular are commonly reported weeks or months after they close.

‘Another rediscovery moment’

Latin America is drawing renewed interest from international venture investors, according to Endeavor’s Taylor. He said international VCs were more active in the region, particularly Brazil, during the first three quarters of 2026 than in 2024 and 2025 combined, through both new investments and follow-on funding.

“I joke that investors from the U.S. ‘rediscover’ Latin America every five or six years, and I think we are approaching another rediscovery moment,” Taylor told ������Ƶ News.

Endeavor Catalyst recently closed its oversubscribed $320 million fifth fund. Latin America accounts for nearly 40% of its portfolio by both deals and dollars, and Fund V had made 14 investments in the region as of Sept. 22. Taylor also pointed to opportunities beyond Brazil and Mexico, including repeat founders building global businesses from Colombia and emerging companies in Venezuela and Central America.

Liquidity is improving, although acquisitions and secondary transactions are providing more opportunities than public listings, Piquet said. He pointed to approximately 60 private Latin American technology companies that have each raised at least $150 million as a potential pipeline for future IPOs.

“The exit door is open, although it is not primarily opening through IPOs yet,” Piquet said.

Taylor expects more exits could help bring global investors back consistently, with potential listings by companies such as , or contributing to another “rediscovery moment” in 2027.

International investors remain interested in Latin America but have become more selective about deploying capital, according to of . Firms with a longstanding presence in the region remain engaged, while many that entered during the 2020–2021 investment boom have shifted toward AI opportunities elsewhere and are concentrating on existing portfolios, she noted.

“Global investors are increasingly investing behind themes rather than geographies,” she said, putting Latin American startups in more direct competition with companies in the U.S. and other markets.

Investor interest is increasingly centered on AI-native businesses and financial infrastructure, particularly stablecoins and cross-border payments. Gadala-Maria said more founders are targeting global markets from the outset, marking a departure from the previous wave of startups that adapted established business models to underserved local markets.

“Increasingly, we’re seeing founders build globally competitive technology companies from Latin America, rather than necessarily for Latin America,” she said.

Gadala-Maria agrees that Brazil and Mexico remain the region’s largest markets, with Brazil offering a deeper, more mature startup ecosystem and Mexico providing substantial room for financial services innovation. She pointed to Argentina as an overlooked market, citing its strong technical talent and founders building companies for global customers.

Correction: Details regarding Kapital’s Series C were updated. The deal was a debt and equity raise.

Related ������Ƶ queries:

Methodology

The data contained in this report comes directly from ������Ƶ, and is based on reported data. Data is as of Oct. 5, 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.

������Ƶ 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 ������Ƶ 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. ������Ƶ 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. ������Ƶ 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 “Series [Letter]” 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 “venture” round. (So basically, any round from the previously defined stages.)

Illustration:

Overall, investors put $38.5 billion into reported seed- through growth-stage financings for countries in the region in Q3, per ������Ƶ data. Of that, a majority went to AI-focused companies, echoing the trends we’ve seen globally.

Deal counts, meanwhile, were relatively flat. That indicates concentration of capital into favored startups remains pronounced but is not intensifying.

Table of contents

• An AI-driven quarter
• China leads by far in country-by-country breakdown
• Late stage
• Early stage
• Seed
• A big quarter for China
• Methodology
• Glossary of funding terms

An AI-driven quarter

Around 55% of investment — an estimated $21 billion — went to AI-focused companies. Total funding is down substantially from the prior quarter, which was boosted by a $7.4 billion financing for China’s , but still the second-highest tally on record.

For Q3, a couple of extra-large rounds bolstered the AI investment tally. The largest went to Beijing-based foundational model company , which secured $3.5 billion in July at a reported $35 billion valuation.

, the AI spinout of China-based short video platform , was the second-biggest fundraiser. The generative video startup raised around $3 billion in a July financing that included and .

China leads by far in country-by-country breakdown

China was the leading Asian destination for venture investment by a very wide margin.

Per ������Ƶ data, roughly $27 billion — or 70% of all Asian startup funding in Q3 — went to China-based companies. India was a distant second, with $2.9 billion, followed by Singapore, with $2.5 billion.

For perspective, below we charted third-quarter startup funding tallies for the six countries with the largest totals.

Late stage

Most capital went to late- and growth-stage funding rounds.

Per ������Ƶ data, investment at this stage totaled around $20 billion in Q3. That’s down a bit from the prior quarter but nearly double year-ago levels and the second-strongest showing in four years.

Multiple jumbo rounds kept the total high. The largest was Moonshot AI’s aforementioned $3.5 billion Series F.

Several others raised financings in the multiple hundreds of millions. Shenzhen-based , a provider of robotics hardware and software, for instance, picked up $400 million in a September Series C. And Hong Kong-based , an e-commerce fintech platform, secured $300 million in Series C funding as it eyes an IPO.

Early stage

Early-stage investment drifted lower in Q3 but remained at historically high levels.

Per ������Ƶ data, financing for startups at the Series A and Series B stages totaled $13.6 billion for the just-ended quarter. That’s a decline of 28% from the prior quarter but up 65% from year-ago levels.

Seed

Reported seed funding hit its highest level in years, boosted by investor enthusiasm around AI.

In total, investors poured $4.9 billion into reported seed and angel deals across Asia, per ������Ƶ data. That’s up around 22% from the prior quarter and more than double year-ago levels.

A big quarter for China

Overall, Q3 was a robust period for venture funding to China-based companies, with far smaller sums going to other Asian startup hubs. Funding to startups based in India and Singapore was down significantly quarter over quarter, while Israel’s investment totals declined slightly.

We’ll keep an eye out in the coming months to see if this divergence of fortunes persists.

Related ������Ƶ query:

Related reading:

• ������Ƶ Data: Q3 2026 Posted A Record Count Of Billion-Dollar Rounds As The Global AI Race Heats Up

Methodology

The data contained in this report comes directly from ������Ƶ, and is based on reported data. Data is as of Oct. 5, 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. ������Ƶ 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 ������Ƶ 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. ������Ƶ 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. ������Ƶ 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 “Series [Letter]” 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 “venture” round. (So basically, any round from the previously defined stages.)

Illustration:

Two decades later, Herrin is building a business around the marketing problems she encountered along the way. She started in 2025 to help consumer brands decide which products to promote and prepare their campaigns. The startup has now raised $5 million in seed funding, it tells ������Ƶ News exclusively.

led the round, joined by and angel investors including former and current leaders.

Marklo helps consumer brands plan marketing campaigns using their sales, inventory and past marketing data. Its software shows which promotions drove sales, suggests what products to promote next and uses AI to draft campaign briefs and organize tasks.

While Marklo is still pre-revenue, more than 100 brands are already using its software in a pilot, according to Herrin. Those brands include , , , and .

The Burlingame, California-based company is now opening its software to the public ahead of the holiday shopping season. It plans to use its new funding to hire engineers, develop the product and expand customer support.

Planning campaigns

To decide what to promote next, marketers first need to understand what drove past sales. That can be a challenging endeavor when sales, inventory and marketing records all sit in separate systems.

Marklo collects that information from Shopify and services such as Klaviyo, , and , then puts past launches, promotions and sales into a calendar. Teams can see, for example, whether a rise in sales attributed to paid advertising coincided with a new product launch or a widely shared social post — factors they might miss when reviewing each service separately, Herrin said. Marklo can then draft a campaign plan and create related tasks for the team to review, edit and assign.

Using those records, along with competitors’ promotions and social media trends, Marklo suggests what a brand should market next. It also considers what the retailer has in stock and when a promotion would run.

From there, teams can use the software to plan campaigns, draft marketing materials and assign work, with suggested campaigns and reports also delivered through or email.

Herrin said the lack of broader-picture context with other AI tools frustrated her. For example, a tool might identify a Fourth of July sale as a successful promotion and suggest repeating it.

“Hey, no, I can’t. It’s not Fourth of July. We don’t have the inventory anymore,” she recalled thinking.

In one case, Herrin described how Marklo identified a color trending on social media and a matching handbag a retailer had in stock but hadn’t promoted recently. It offered to plan a post based on one that had performed well before.

Latico Leathers offers another example of how a brand uses Marklo. The company used the software to plan a month’s worth of marketing in one day, a process that had previously taken most of a week across meetings, spreadsheets and five tools, according to Herrin.

In the end, humans review and approve Marklo’s proposed work. The company says it does not use customer data to train AI models.

As for its revenue model, Marklo plans to charge a monthly subscription fee, with additional charges based on usage. For now, brands can install and try it for free.

“I’m very passionate about small and medium businesses, and I want to make it accessible to every single brand that runs on Shopify,” Herrin told ������Ƶ News in an interview, “so that they can operate like a big brand.”

A change of direction

The decision to build Marklo followed a change in how Herrin thought about Stella & Dot’s future.

That company began as a way for women to earn money on their own schedules by hosting trunk shows in their own homes. It expanded into apparel and skincare and paid out more than $500 million to its sellers, Herrin said.

“For me, it was never about the jewelry,” she told ������Ƶ News.

When COVID-19 put a stop to in-home gatherings, business dropped 80% almost overnight. Herrin also realized that women who might once have signed up to sell Stella & Dot products suddenly had other options. They could promote multiple brands as influencers or open their own Shopify stores.

She described Stella & Dot as “the COVID victim that had pre-existing conditions.”

Rather than rebuild the old model, Herrin sold the businesses and brands separately. Later, she bought back the Stella & Dot brand to sell through a different channel and test Marklo.

She was also reconsidering what she wanted to do next. As she approached her 50th birthday, Herrin questioned whether she would choose to start the same business again.

“As an entrepreneur, you don’t just start a business; you start a life,” she said.

She still wanted to help people build businesses. What had changed was the problem she wanted to solve: Opening an online store had become easier, but managing its marketing still meant gathering information from several systems and coordinating the next campaign.

“The mission was the same, but the solution needed to evolve,” Herrin said.

A return to venture capital

For Marklo, Herrin also returned to venture funding after relying more on profits to grow Stella & Dot.

She had raised venture capital for her first company, which became , but came away feeling that it had raised too much money. She took a different approach with Stella & Dot, building it with about $2 million in capital and a focus on profitability.

“Here’s a new growth strategy,” Herrin recalled thinking. “How about profits?”

With Marklo, she wanted to hire engineers and develop the software faster. Its 11-person team includes engineers who previously worked at Shopify and Google. She also sought investors with commerce experience.

“Raising capital isn’t just about having money for expenses,” Herrin said. “It’s about bringing a brain trust together.”

Experience as ‘the customer she’s building for’

, founder and managing partner of Forerunner Ventures, said Herrin’s experience building Stella & Dot was a central reason for backing Marklo.

“Jessica uniquely has been the customer that she’s building for right now at every stage, from starting a brand to having a brand at scale,” Green told ������Ƶ News in an interview. That experience gives Herrin firsthand knowledge of where teams lose time, which decisions affect profitability and what brands need before trusting new technology, she added.

While AI in general makes it easier to produce marketing content, Green sees the greater opportunity in helping brands decide on what exactly to promote, as well as in understanding the impact on margins and how to grow in ways consistent with their identity. Marklo, she said, incorporates the judgment needed to turn business data into useful recommendations.

The opportunity comes as AI is taking a larger share of investment in the broader sales and marketing sector. Startups in sales, marketing and customer relationship management raised $7.5 billion across 830 rounds globally this year through mid-September, with most of that investment going to companies in ������Ƶ’s AI-related categories. Funding is on pace to finish below 2025’s $11.1 billion, while deal volume could fall for a fourth straight year — a sign that investors are concentrating their bets in fewer companies.

“It’s one thing to collect the information; it’s another thing to understand how to present it and how to recommend an action against it,” Green added.

The investor also pointed to Marklo’s ability to serve businesses at different stages, noting that coordination becomes more complex and information harder to share as brands grow. As such, the prospect of software that can grow alongside its customers was another draw.

Green said she also valued Herrin’s decision to develop Marklo alongside brands already using it, giving the company customer feedback before its broader launch.

“I like the fact that she built this product while it was being used,” she said.

Related ������Ƶ queries:

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• Sector Snapshot: AI Takes A Growing Share Of Sales And Marketing Startup Funding

Illustration:

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

As the AI startup boom progresses, investors appear to be leaving few niches unfunded. That was apparent in this week’s lineup of large funding rounds, which featured AI infrastructure providers, a foundational model developer, a content protection platform for the AI age, and other AI-focused startups among the top investment recipients.

The biggest investment, $2 billion, went to , a spinout focused on cloud and power infrastructure that is hoping to benefit from the AI buildout. Other large rounds went to , developer of a fast-growing new model, and , a quantum computing startup.

1. , $2B, cloud and power infrastructure: Axiom Solutions International, a private cloud and power infrastructure company spun out of manufacturing services provider , secured $2 billion in new financing. and provided the strategic investment by purchasing shares of Austin-based Axiom from Flex at an initial enterprise value of $37.5 billion. Flex says it plans to separate Axiom into an independent publicly traded company early next year.

2. , $870M, foundational AI: TypeSafe AI, developer of Jev, a recently launched AI model with a large and growing early following, raised $870 million in new funding with as the largest investor, according to a . also participated in the round, which reportedly set a $7.5 billion valuation for San Francisco-based TypeSafe.

3. , $475M, quantum computing: Pasadena, California-based Oratomic, a startup working on fault-tolerant quantum computers, raised $475 million in fresh funding led by , , , , and . The company previously raised $300 million in a July financing.

4. , $400M, data and content protection: SignSplit, a provider of tools for protecting, licensing and contributing real-world human data and other forms of human contribution, emerged from stealth with $400 million in seed funding. backed the round, setting a $1 billion valuation for the New York-based company, which was founded in 2024.

5. (tied) , $250M, AI for engineering: Vinci, developer of an AI computational platform for hardware engineers to design products, closed on $250 million in Series B funding at a $1.5 billion valuation. , and led the round for the Palo Alto, California-based company.

5. (tied) , $250M, micro-manufacturing: Emeryville, California-based Atomic Machines, a startup working on AI-native digital manufacturing systems to build micro-machines directly from code, emerged from stealth and said it has raised $250 million to date from a long list of investors.

7. , $225M, energy distribution: Voltus, provider of a distributed energy platform aimed at bolstering grid flexibility, picked up $225 million in Series D funding. , and led the financing for the San Francisco-based startup.

8. (tied) , $200M, fusion: Knoxville, Tennessee-based Type One Energy, a developer of fusion energy technology, secured $200 million in Series B financing led by and .

8. (tied) , $200M, insurance: Ledgebrook, an AI-powered specialty insurance platform, closed on $200 million in equity financing co-led by and . The round brings total funding to date for Boston-based Ledgebrook to around $315 million, per .

8. (tied) , $200M, AI evaluation: Arena, provider of a platform for evaluating AI models, pulled in $200 million in Series B funding and said it has exceeded a $100 million annual revenue run rate. and led the round, which set a $3.1 billion valuation for the company.

Methodology

We tracked the largest announced rounds in the ������Ƶ database that were raised by U.S.-based companies for the period of Oct. 3-9, 2026. Although most announced rounds are in the database, there may be a small time lag, as some rounds are reported late in the week.

Per ������Ƶ data, a majority of the most active venture investors in Q3 participated in more deals compared to the prior quarter. This includes many of the usual busiest dealmakers, like , and .

The top lead venture investors also largely stepped up the pace this past quarter, even as the highest-spending among them appeared to put less capital to work. At seed stage, meanwhile, the typical top dealmakers largely held their ranks.

For a more detailed look, below we chart and analyze the most active investor ranks across multiple metrics, including venture dealmakers, high spenders, lead backers and seed funders.

Most active venture investors

We’ll start with the most active investors in post-seed rounds. By this measure, topped the ranks with 45 deals. The famed accelerator typically ranks high because it participates in follow-on rounds for startups it incubates.

Next on the list were Andreessen Horowitz, Insight Partners and Sequoia Capital. Overall, as charted below, at least 22 investors participated in 10 or more known venture rounds this past quarter.

Busiest lead investors

Among lead investors in venture rounds, Insight, Andreessen and ranked highest with 18, 16 and 12 rounds, respectively.

Another three investors — , Sequoia and — had 10 lead deals each in Q3.

Spendiest lead investors

We also attempted to get a sense of which lead investors put the most capital work in Q3. To approximate this, our ranking looks at investors whose lead rounds had the highest aggregate value.1

By this metric, Valor and Atreides tied for the No. 1 slot, with $7.7 billion in led or co-led deals for the quarter. The two had some overlap, with at least listing both firms as lead investors. This included ’s $3.9 billion Series F and ’s $375 million Series C.

Next in the ranking were Andreessen Horowitz and , with $6.5 billion and $6.3 billion in led or co-led Q3 deals. Andreessen’s tally largely stemmed from a $2 billion round for and a $1.7 billion financing for .  Nvidia’s standout deal was a $5 billion round for .

Seed investors

Seed investors also kept busy in Q3. Among them, the busiest by far was Y Combinator, which participated in at least 221 known seed rounds this past quarter, per ������Ƶ data.

also ranked high, with 31 reported seed rounds, followed by and with 24 and 23 reported deals, respectively.

Overall, another busy, AI-driven quarter

Overall, our active investor rankings paint the picture of another busy quarter for startup funding, with AI driving the bulk of dealmaking.

Mostly, it’s familiar names topping our various rankings. However, we are seeing a few firms significantly scaling up their investments, with Atreides and Valor in particular stepping up their game of late.

Related ������Ƶ query:

Related reading:

• North America’s Startup Funding Falls In Q3 As AI Giants Eye The Public Markets
• ������Ƶ Data: Q3 2026 Posted A Record Count Of Billion-Dollar Rounds As The Global AI Race Heats Up

Illustration:

������Ƶ startup funding reached $25 billion last quarter, well above the $14 billion invested in Q3 2025 and up slightly from the $24 billion invested in Q2. Quarterly funding was up 77% year over year, per ������Ƶ data.

While the U.K. continued to lead startup funding totals last quarter, Germany and France both posted their strongest quarters since the boom years of 2021 and early 2022. Last quarter’s funding totals were boosted heavily by a $3.5 billion investment in Paris-based , the largest venture round ever for a Europe-based company.

Table of contents

• Billion-dollar fundings
• Venture expands beyond the UK
• Late-stage rise
• Early stage
• Seed
• Looking forward
• Methodology
• Glossary of funding terms

Billion-dollar fundings

Four ������Ƶ companies raised billion-dollar-plus fundings, representing close to 40% of the region’s startup capital raised last quarter.

They include Mistral, which also announced its new open-source model Large 4, an LLM it claims outperforms competing open source models on several vectors.

Data center provider raised a convertible note of $3.36 billion that it says it will convert once it goes public, which it has filed plans to do.

Two defense tech startups also raised billion-dollar-plus rounds last quarter: raised a Series E of $1.8 billion, and raised $1.2 billion.

AI drove 75% of ������Ƶ funding this past quarter — totaling $18.8 billion — the highest proportion on record.

Investments in physical tech in Europe in defense, data centers, energy, aerospace and robotics accounted for roughly half of ������Ƶ funding in Q3.

Venture expands beyond the UK

The U.K. led the region’s quarterly funding totals with $7.5 billion even as Germany and France gained market share for venture capital funding in Q3 with $5 billion and $4.8 billion invested, respectively.

The fourth-largest market, Sweden, saw $1.5 billion in venture capital invested while the Netherlands and Spain posted their strongest quarter since the COVID boom years with $1.4 billion and $1.2 billion invested in their startup markets, respectively.

Late-stage rise

A total of $17.3 billion — 70% of Europe’s Q3 venture capital — was invested in late-stage deals in 83 companies.

Outside of the billion-dollar rounds, large late-stage fundings between $400 million to $700 million were raised by Stockholm-based health scanning provider ; Lisbon-based autonomous drone developer ; Spain-based , which offers model compression technology for enterprise AI adoption; Amsterdam-based AI deployment startup ; Bayern-based space transportation company ; and Stockholm-based AI web application builder .

Early stage

Europe’s early-stage funding totaled $5.7 billion into just over 200 companies in Q3, down quarter over quarter and flat year over year.

The largest Series A funding deals, each $200 million or over, were raised by Eindhoven-based AI semiconductor startup and Zürich-based autonomous construction company .

Large Series B rounds were raised by Munich-based fusion energy company and London-based optical computing provider .

Seed

Europe’s seed funding fell quarter over quarter and was flat year over year. Around $2 billion was invested in more than 750 companies at seed stage in Q3.

London-based managed inference company raised the largest seed round at $100 million, followed by Munich-based AI for robotics startup , which raised $55 million.

Looking forward

Europe’s momentum in 2026 continued in Q3, which was the second quarter this year when venture totals topped $20 billion. Those are figures not seen in the region’s startup scene since Q3 2022. Along with growth in AI funding, late-stage funding noticeably increased last quarter with many of the leading rounds sourced across multiple ������Ƶ countries.

Europe represented 16% of global venture capital in Q3, although the true impact of its technology and startups is higher, with many of the region’s startups expanding or moving to the U.S. to capitalize on the rapid growth of AI there.

At the same time, Europe’s ambition to build leading deep-tech companies and meet demand for sovereign AI will be tested in the quarters ahead by its ability to mobilize the substantial capital these businesses need.

Related ������Ƶ queries:

Related reading:

• ������Ƶ Data: Q3 2026 Posted A Record Count Of Billion-Dollar Rounds As The Global AI Race Heats Up
• Reporter’s Notebook: Europe’s Sovereign AI Push Needs Customers As Well As Capital

Methodology

The data contained in this report comes directly from ������Ƶ, and is based on reported data. Data is as of Oct. 5, 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. ������Ƶ 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 ������Ƶ 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. ������Ƶ 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. ������Ƶ 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 “Series [Letter]” 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 “venture” round. (So basically, any round from the previously defined stages.)

Illustration:

In total, investors poured $92 billion into seed- through growth-stage rounds for U.S. and Canadian startups in the third quarter, per ������Ƶ data. That’s a 35% decline from the prior quarter but up 50% from year-ago levels.

Deal volume held fairly steady, with late-stage and early-stage round counts remaining close to prior quarter levels.

Artificial intelligence remained the prevailing theme for startup investors. Per ������Ƶ data, roughly two-thirds of total funding this past quarter went to AI-focused companies. Of that, a big chunk went to large rounds for , and .

Overall, however, investment fell across most stages. Early-stage dealmaking posted a particularly sharp decline from a multiyear peak the prior quarter, while later-stage funding was also down.

As for exits, quarter-over-quarter IPO comps were always going to be challenging, given that Q2 featured ’s record-setting market entry. Even compared to a typical quarter, however, the IPO market was fairly sluggish in Q3, with a few biotech, energy and consumer-facing offerings, but no blockbuster tech debuts. M&A activity was more exciting, topped by ’s September acquisition of .

Below, we look over the quarterly numbers in more detail, breaking out investment by stage, charting AI funding, and analyzing exit activity.

Table of contents

• Late-stage and technology growth funding
• Early stage
• Seed
• AI
• Exits
• M&A
• IPOs
• Slower, but not a slowdown
• Methodology
• Glossary of funding terms

Late-stage and technology growth funding

We’ll start with late stage, since that’s where most startup funding went.

For Q3, investors poured $66.45 billion into late- and growth-stage deals, per ������Ƶ data. That’s up about a third from year-ago levels, but down sharply from Q1 and Q2 of this year, when OpenAI and Anthropic pulled in financings of $110 billion and $65 billion, respectively.

For the just-ended quarter, the largest late-stage and growth rounds went to Databricks ($5 billion), AI infrastructure unicorn Crusoe ($3.9 billion), ($3 billion), and AI coding startup ($2 billion). Overall, more than a dozen startups attracted late-stage or growth rounds of $1 billion or more, per ������Ƶ data.

Early stage

Early-stage investment also held up at historically high levels in Q3, albeit down from prior highs.

Overall, investors put $20.6 billion into early-stage rounds in the just-ended quarter, per ������Ƶ data. That was down sequentially from the prior quarter but still well above prior year levels.

A few exceptionally big rounds pushed up the latest quarterly tally. The largest funding recipients included open source AI company ’s $1.1 billion Series A, nuclear startup ’ $660 million Series B, and chip hardware and software developer ’s $500 million Series A.

Seed

Seed-stage dealmaking was also quite busy in Q3.

At least $5 billion went to seed, angel and pre-seed rounds in the just-ended quarter, per preliminary ������Ƶ data. That’s a bit below both the prior quarter and year-ago comps. However, we expect the Q3 tally to rise a bit over time as seed deals commonly get added to the dataset a few weeks or months after they close.

The AI space delivered some particularly large seed rounds. Of these, standouts were physical AI startups , which picked up $300 million, and . which secured $90 million.

AI

The percentage of funding going to AI-focused startups also held up at high levels in Q3, per ������Ƶ data.

A total of $61 billion went to AI-focused rounds, per ������Ƶ data. While that’s down sharply from the prior two quarters, it’s still one of the highest tallies on record.

Exits

As for exits, Q3 featured a number of large M&A deals, particularly in the AI space. The IPO market was a bit quieter, with much of the market’s attention looking forward to enormous offerings from foundational AI pioneers in coming months.

M&A

Acquisition activity was fairly robust in Q3, boosted by a handful of large AI-related purchases. Of these, the biggest was Nvidia’s acquisition of open model development platform Hugging Face for $12.93 billion.

The next-biggest M&A deal was ’s purchase last week of , an AI model and research lab led by AI pioneer , in a stock deal valued around $8.2 billion. Not far behind, in third place, was ’s acquisition of , a startup that routes prompts through different AI models, in an August transaction reportedly valued around $7.5 billion.

In total, there were 11 North American startup acquisitions at reported prices of $1 billion or more in Q3, per ������Ƶ data. We list them below.

IPOs

Overall, it was a light quarter for IPO activity. Per ������Ƶ data, 17 venture-backed North American companies went public on major U.S. and Canadian exchanges in Q3, per ������Ƶ data, collectively raising just under $4 billion.

Three biotech companies raised the largest sums in their IPOs: , focused on mRNA; , a developer of cardiovascular therapies; and , which is working on antibody therapeutics.

Other venture-backed companies that carried out good-sized debuts included , a developer of advanced nuclear fuel, and , the scooter and e-bike rental platform.

Notably, however, it was the IPOs that didn’t happen this quarter that attracted the most attention. By this, we are referring of course to Anthropic, which is reportedly eyeing a  public list as early as November, and OpenAI, which filed confidentially for an IPO in June and is expected to make its debut in 2027.

Slower, but not a slowdown

Overall, Q3 seems to exemplify the notion that funding activity can decline from peak levels without a clear indication that the investment climate has turned bearish.

Yes, giant funding rounds contracted. However, the maturation of the two most valuable startups, OpenAI and Anthropic, into even more valuable pre-IPO companies, is the kind of thing venture investors want to see.

Moreover, big rounds are still closing at a brisk clip. The AI space is still regularly minting fresh unicorns. And acquirers are snapping up leading names at historically high valuations.

Could things go south from here? Sure. But for now, the AI-driven momentum continues.

Related ������Ƶ query:

Related reading:

• North American Startup Funding Shattered Records In First Half Of 2026, Driven By AI

Methodology

The data contained in this report comes directly from ������Ƶ, and is based on reported data. Data is as of Oct. 2, 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. ������Ƶ 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 ������Ƶ 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. ������Ƶ 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. ������Ƶ 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 “Series [Letter]” 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 “venture” round. (So basically, any round from the previously defined stages.)

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Funding to private companies has skyrocketed this year, totaling $679 billion in venture funding globally in Q1 through Q3 2026, per ������Ƶ data. That is the highest amount in the first three quarters of any given year.

While global venture funding in Q3 was down 25% quarter over quarter from the $212 billion raised in Q2, it was up 53% year over year from the $104 billion raised in Q3 2025.

 Table of Contents

• Billion-dollar fundings
• US and sectors
• Late-stage funding
• Early-stage funding
• Seed
• Exits: IPOs and M&A
• Robust market
• Methodology
• Glossary of funding terms

Billion-dollar fundings

A notable shift in 2026 has been the number of startups that have raised billion-dollar-plus rounds. An all-time record of 27 companies raised such sizable rounds in Q3 2026, an increase from the previous record, set in Q2, of 16 companies and Q1’s total of 14 companies.

Around a third of all global venture capital raised in Q3 went to those 27 companies. In the two prior quarters, billion-dollar raises pushed total funding to well above historical norms.

No single company raised funding in the tens of billions last quarter. However, eight companies raised funding rounds of $3 billion or more, with frontier labs and data centers leading by company counts for the biggest raises. Of these eight companies, five were founded within the past four years.

The largest funding deals went to and , which each raised $5 billion. Close behind, , , , , and each raised more than $3 billion.

US and sectors

U.S.-based companies continued to raise the dominant share of venture capital with $91 billion invested in American startups, or around 57% of the global total in Q3. The San Francisco Bay Area alone accounted for 24% of global venture investment in the quarter.

AI-driven startups across the stack raised $102 billion, or 64% of global venture capital, down from the two previous quarters, but still 14 percentage points above Q3 2025 global funding.

The realm of physical AI has attracted significant capital in 2026. That continued in Q3 with the aerospace, robotics, data centers, semiconductor and energy sectors each raising $10 billion or more in the quarter.

Late-stage funding

Late-stage venture funding totaled $105 billion in Q3, down 23% from Q2 but up 73% from Q3 2025, ������Ƶ data shows. Funding rounds of $100 million and above accounted for close to 90% of late-stage financings.

Early-stage funding

Early-stage funding totaled $40.6 billion in Q3, up by 25% from a year earlier. The number of companies raising jumbo sized rounds at $100 million and over, represented 50% of early-stage financings.

Seed

Global seed funding totaled $13 billion in Q3, ������Ƶ data shows. Of that, $2.6 billion went to seed rounds of $100 million and over, around 20% of seed financings.

Exits: IPOs and M&A

Q3 was a fairly strong quarter for exits. China dominated on the IPO front for the largest exits  with semiconductor and robotics listings surging on their first day of trading.

• China-based , developer of DRAM chips, was the largest IPO in Q3, raising  $8.6 billion at an $85.5 billion value. Its stock surged more than 500%  on its debut to become the most valuable listed company in the local market.
• The second-largest was Singapore-based fast fashion company listing at a $26.3 billion valuation, well below its 2022 valuation peak of $100 billion. Shein was the one exception that closed its first day around its opening price, after falling by about 10%;
• Shanghai-based AI chipmaker , a competitor to , went public in September, raising $912 million at a valuation of $25.5 billion.
• Milan-based , acquirer of and , raised $1.6 billion on its debut at a value of $18.4 billion.
• Hangzhou-based humanoid robotics company went public raising $905 million debuting at a valuation of $9 billion.

U.S.-based companies, meanwhile, dominated the largest M&A deals.

Semiconductor companies were the largest acquirers in Q3. bid to acquire New York-based open-source AI platform for $12.9 billion. Semiconductor giant announced its intent to acquire ’s , a San Francisco-based builder of models for physical intelligence, for $8.2 billion. The third-largest acquisition was payments provider ’s acquisition of New York-based AI model router for $7.5 billion.

Robust market

Over the past few quarters, larger checks across funding stages have pushed venture investment higher as young AI companies gained traction rapidly. Half of startup capital invested in Q3 went to companies founded since 2022.

Venture funding has also expanded beyond software into physical infrastructure and robotics, reindustrializing economies. And a dynamic seed funding climate for AI-native startups signals continued appetite for the next wave of companies.

Methodology

The data contained in this report comes directly from ������Ƶ, and is based on reported data. Data is as of Oct. 2, 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. ������Ƶ 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 ������Ƶ 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. ������Ƶ 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. ������Ƶ 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 “Series [Letter]” 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 “venture” round. (So basically, any round from the previously defined stages.)

Related reading:

• VCs Pour Billions Into Physical AI As The Next Wave Of AI Investing Takes Shape
• Jumbo-Sized Series A Rounds Are On The Rise

Illustration:

Ten years ago, a seed-stage startup needed a product, a team and a pitch deck to raise capital. Today, that’s just the start. Technology and strategy have become inseparable, each fueling the other, and the rules that once defined success have quietly shifted under everyone’s feet.

Last month, my firm reviewed more than 2,500 inbound applications. Here are the key shifts we’re seeing in the startup ecosystem at the seed stage.

Broadening capital strategy

Equity is a powerful tool for building high-growth companies. But it’s no longer the only option. Non-dilutive growth capital is increasingly playing a strategic role for companies with revenue visibility and clear ROI channels.

For example, we recently financed a company with $1 million in growth capital it needed immediately to expand its team and infrastructure. Raising that through equity alone would have likely taken months, with significant time and execution cost along the way.

We’re now writing financing checks like this on a near-weekly basis.

Distribution focused

Leading with a “better” product isn’t enough to propel growth. The breakout companies are investing in building stronger distribution systems — aka what founders refer to as “traction.” Distribution is a critical moat for early-stage startups. Rapid scaling is no longer achieved by launching new products; it’s through distribution loops.

Distribution is something startups can now architect intentionally with social platforms, marketplaces and other ecosystems. One of the most common founder mistakes we see is delaying the distribution strategy until after the product launch. At that stage, the architecture is harder to retrofit. Strong startups design distribution before they scale their product.

For example, some of the fastest-growing startups now design their products around existing ecosystems from day one — building apps that tap into merchant marketplaces, AI tools distributed through or Teams integrations, or fintech products embedded directly into banking and payroll workflows. In many cases, the distribution channel becomes more valuable than the underlying product itself.

One of the most common mistakes we see is founders postponing distribution strategy until after the product is built. By then, the architecture is far harder to retrofit. The strongest startups design distribution into the company before they scale the product itself.

Learning over speed

“Move fast” is often dolled out as the best startup advice. Operating in a fast-paced environment remains a strategic asset, but it is not enough to maintain a competitive advantage.

Everyone is fast. It’s no longer a unique attribute. Instead, learning velocity is becoming the defining advantage in early-stage startups. How quickly can you reduce uncertainty? Competitive edge is achieved not by executing blindly, but by closing knowledge gaps faster than everyone else. Execution without learning equals wasted motion.

The founder focus advantage

Last year, my team reviewed close to 25,000 applications for our investment funds and bespoke accelerators. The ones that stand out are the companies doing the fewest things exceptionally well. The most-fundable companies can describe their business in one tight sentence. They can also defend exactly what they are not doing.

Disciplined constraint is one of the highest-leverage traits in venture-backed companies. When we review applications, this pattern consistently stands out.

When a company is focused, the residuals compound: stronger early retention, faster iteration cycles, cleaner capital deployment. In a capital-selective market, focus compounds faster than ambition.

Based on tens of thousands of applicants, close to 82% of the ones that stayed in business a year later had a strong go-to-market foundation in their deck. GTM is built on agility and learning fast.

AI as infrastructure, not experimentation

There’s no lack of interest in AI. But there is an implementation problem. We’ve seen companies struggle when AI is approached as experimentation rather than architecture. Rather than bolting tools onto already fragmented stacks and workflows, designing intelligent systems should be mapped from the ground up.

More than 78% of the founders applying to today are leveraging AI in at least one way in their startup.

The most successful playbook combines execution with operational clarity and emphasizes infrastructure over experimentation. We’ve seen successful implementations that center around two practical paths. The first is validation, with rapid prototypes and identifying market signal opportunities before investing in a full build. The second is system, designing and integrating custom AI agents directly into operating workflows for revenue-generating companies facing operational complexity. Both are required to move AI agents from concept to capability. A disciplined system design often matters more than flashy tooling.

Marketing is the moat

Marketing execution is one of the largest performance gaps we see across early-stage startups. Startups lose when they don’t distribute fast enough once there is something worth selling. Marketing is the propeller for the distribution engine.

Most startups fail at marketing because it is a business function that becomes a founder hustle with support from one junior hire. But breakout growth requires process, cadence and accountability. That’s not achievable without an experienced team and clear plan.

One of the biggest mistakes founders make is treating marketing as something that starts after launch. Founders must create unique strategies, test them and then analyze what works and what doesn’t. From there, they must keep iterating and creating to unlock the most product-market fit and traction.

If we see classic strategies in a pitch deck, it is an auto-reject. And beyond being unique, your strategies must have been tested by your team.

The key is simple: Test ideas early, measure what actually works, refine aggressively and scale the strategies that compound over time.

, a serial technology entrepreneur since age 12, is now a value-driven venture capitalist with a track record of backing more than 1,000 startups across the globe. He is a co-founder and general partner at , one of the world’s most active venture capital firms. Before becoming involved in venture investing, he built and scaled into the world’s largest debate-focused social network and edtech platform, reaching millions of users and serving students across more than 500 school districts, colleges and universities.

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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 ������Ƶ 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.

������Ƶ 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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