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.)

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

Startup investors aren’t exactly hitting pause, but they did scale back on giant rounds this past week, with just two startup financings in the multiple hundreds of millions. The biggest round went to AI infrastructure provider , which picked up $750 million, followed by construction automation unicorn , which secured $200 million. Other sectors that attracted larger rounds this past week included biotech, insurance and AI.

1. , $750M, AI infrastructure: Modal Labs, a provider of cloud infrastructure for AI inference and other applications, secured $750 million in a Series D funding round led by at a $15.75 billion valuation. The New York-headquartered company said it recently exceeded an annual revenue run rate of $1 billion.

2. , $200M, construction tech: Austin-based Icon, a developer of robotic construction systems known for its 3D-printed homes, closed on $200 million in Series D funding led by�� and . The company says it is on pace for 4x revenue growth in 2026.

3. , $135M, RNA therapies: Boston-based Soufflé Therapeutics, a developer of RNA therapies, raised $135 million in Series B funding led by as part of a large syndicate of investors.

4. , $103M, gene therapies: Menlo Park, California-based Estuary Biotherapeutics, a developer of genetic medicines for patients with serious kidney diseases, launched with $103 million in financing. The funding includes $93 million in a Series A round led by as well as $10 million in previously undisclosed seed capital.

5. , $100M, AI tools: Labelbox, a developer of technology to train and evaluate AI models and to help deploy agents that improve with experience, picked up $100 million in Series E funding. led the financing for the 8-year-old, San Francisco-based company.

6. , $90M, health AI: Redwood City, California-based Suki, a provider of AI tools that turn clinical conversations into intelligence for documentation, coding and other healthcare workflows, announced a $90 million Series E financing from backers including and .

7. , $82M, caregiver platform: Abby Care, a platform for family members to become certified, paid caregivers and deliver care at home, closed on $82 million in Series C funding, per a . led the financing for the 5-year-old, San Francisco-based startup.

8. , $70M, insurance: Stand, a provider of insurance for homes in areas at higher risk of natural disasters, secured $70 million in Series C funding at a $1 billion valuation. led the financing for the 3-year-old, San Francisco-based company.

9. , $65M, semiconductor systems: Mueon Corp., a semiconductor systems company building a modular platform for AI and hyperscale computing, completed a $65 million Series A funding round. led the financing for the Portland, Oregon-based company.

10. , $60M, AI spend management: New York-based North.cloud, provider of an infrastructure spend intelligence and automation platform, raised $60 million in a Series B round led by .

Methodology

We tracked the largest announced rounds in the ������Ƶ database that were raised by U.S.-based companies for the period of Oct. 10-16, 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.

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He also discovered mass arbitration, a way to pursue individual claims when companies’ contracts prevent customers from joining class actions. At the same time, he also realized that relatively few law firms were set up to manage thousands of those claims at once.

That gap became the basis for , which has raised $10 million in Series A funding led by to help consumers pursue claims over alleged privacy violations, hidden fees and subscriptions that are difficult to cancel. , , , , , , , and also participated in the financing.

The New York-based startup works with law firms to identify potential cases, find affected consumers and gather information needed to pursue compensation. The round brings its total funding to $15.7 million, which includes a $3.6 million seed investment in April 2025 and an earlier pre-seed round.

Chariot’s latest round comes amid a surge in investment across legal tech. Funding to the legal tech space hit a record high last year, with $4.6 billion invested, per ������Ƶ . So far this year, legal tech startups have pulled in more than $3 billion, putting the sector on pace to match or exceed the 2025 total.

The Chariot process works like this: For each case, consumers complete an intake questionnaire that assesses preliminary eligibility in real time. Chariot’s team then reviews these pre-qualified claims through a multi-layered system of technology and human oversight before sending it to the partner law firm handling the case. Hang, the company’s CEO, told ������Ƶ News that Chariot typically receives more than 200,000 claim submissions per month and that it has taken on roughly 80 cases since shifting to its current business model just over a year ago.

The company has about 15 employees and is currently breaking even, he said. It plans to spend the new funding primarily on hiring and product development, including AI tools to review cases and help determine whether consumers qualify to participate.

A gap in consumer legal services

Chariot is Hang’s third startup. His first company grew out of sleep research he conducted while studying psychology and neuroscience at . He turned that research into a smart-pillow business and later sold its intellectual property to a medical-device operator. He later worked in healthcare technology and fintech, founded a startup in the Web3 space, and then moved into legal technology.

Across those industries, he said, he encountered complicated systems in which the interests of businesses and their customers did not always align. His experience helping the class-action settlement startup brought those concerns into focus.

He described being “frustrated and mystified and horrified by how our justice system works.”

Chariot started about three years ago, adopting its current model after Hang saw an opportunity to help law firms handle mass arbitration. Firms accustomed to class actions could struggle with the work required to manage large numbers of individual claimants, he said.

“It’s just really inefficient for them to try to build workflows around 10,000 claimants or 100,000 claimants,” Hang said.

Chariot handles parts of that administrative work, while its partner firms handle the legal claims. The startup charges the firms flat service fees, and they work on a contingency basis. Hang emphasizes that since it’s not a law firm, Chariot itself doesn’t file claims.

It helps consumers pursue a variety of claims. Those claims include allegations that websites or apps tracked their information without consent, that companies added fees during checkout, or that businesses made subscriptions easy to start but difficult to cancel, for example.

Finding evidence and drawing objections

Chariot starts by looking for potential cases involving privacy violations, hidden fees and other consumer complaints. Its software scans public records, including federal court filings, and uses AI to analyze the allegations and prepare research for its partner law firms.

That research includes legal memos based on publicly filed complaints. Chariot is also developing tools to track changes in laws and court decisions that could affect whether a case can proceed. The work remains in the early stages, with the goal of automating more of the research that associates and paralegals would otherwise do, according to Hang.

Chariot reviews a few hundred potential cases each month, he said. It tests ads for about 30 potential cases to gauge whether it can find consumers who may have a claim, then selects roughly 10 to pursue more extensively with its partner law firms. Each case can involve many individual consumers, whom Chariot reaches through advertising and partnerships with consumer financial technology companies.

To determine whether they have a claim, consumers must provide information to help assess it. For example, in the case of a data breach, that could be a notice from the company saying their information was exposed. For a hidden-fee complaint, it could include what they purchased, when they bought it, and how much they paid.

Chariot is building AI tools to help review that supporting information and determine whether a consumer has a claim, according to Hang. The required evidence, and the difficulty of verifying it, varies by the type of alleged violation.

The startup plans to make that step easier by allowing users to connect their email accounts so its software can look for relevant documents, rather than asking consumers to fill out forms.�� Hang estimates that such improvements could help the company handle 10x to 100x its current claim volume.

Companies push back

Not everyone welcomes Chariot’s approach. Advertising for potential claimants has brought strong objections from some of the companies involved. In fact, Chariot has received cease-and-desist letters challenging, among other things, its use of company names and trademarks in ads, noted Hang.

But he asserts that identifying those businesses is necessary to reach people who used their products or services.

“As a part of our business, we need to mention the name of the company that has this alleged violation,” he said.

Chariot reviews the letters with legal counsel and complies with demands it considers valid, Hang said. He declined to name specific companies for this article.

His broader goal is to make alleged consumer abuses more costly for businesses. If more affected customers pursue compensation, he reasons, companies will have a stronger financial incentive to change those practices.

“We want to make unethical unprofitable,” he said.

, general partner at Silverton, told ������Ƶ News via email that his firm was attracted to Chariot’s vertical AI approach to working with law firms, which he called “exciting and defensible.”

“It’s a greenfield market with space to expand horizontally and eventually into a generalized consumer legal AI solution,” he wrote. The firm was also drawn to what Dodd described as “a business model that aligns capitalistic incentives with access to justice.”

“When a company breaks the law and breaks what it promises to its consumers, the consumer rarely seeks justice,” he added. “Chariot has built the technology to make individual consumer claims work at scale, and the team to operate it in a category where execution is genuinely hard.”

Related ������Ƶ query:

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A first venture usually follows a well-worn playbook: a gap in the market, obsessive refinement of concept and pitch, eventual conviction that the solution is as bulletproof as it is revolutionary.

Then, the dreaded phase of product-market fit. Instead of building the future of an entire industry, you find yourself forced to focus on a narrow use case and spend the first invaluable years proving that your idea can make money and scale. The grand vision gets put on pause.

For most founders, this journey is the only one available. After all, investors are betting on someone who has never built a company before, so a small check and a narrow product limit what everyone stands to lose. But some ambitions need total commitment from the start, and having built a company before helps when taking them on.

Lessons from the front line

After selling my first venture, , to for €1.8 billion (about $1.9 billion USD) in 2022, I found myself in a new position — and it wasn’t horizontal on a sun lounger. My co-founder and I had a real war chest of our own, and a brand-new entrepreneurial bug. For the first time in our lives, we had the experience and the resources to undertake something truly world-changing.

Compliance is a gauntlet that any founder will be painfully familiar with. Scaling Tink across Europe, to 700 people operating under a host of regulators, my team and I got used to tearing our hair out over small wording tweaks, reviews that dragged on for months, and perpetual uncertainty that stopped us from iterating fast and boldly. Products were often delayed by months, a slip that meant the world in an industry moving as fast as ours.

A problem with too many heads

Compliance was a problem that could never be solved piecemeal. Every company’s obligations depend on a million different factors, each of which sits in a different part of the business that rarely talks to one another.

Legal tracks regulations; another department oversees how they are implemented. Product teams make their own calls on features, and yet another team opens a case to check whether it was compliant. Policies, standards and regulations belong to other departments entirely, and those are usually the part of a silo a compliance startup builds for — a clear buyer and a budget.

“Solving compliance” was a mission akin to fighting the Hydra: cut off one head and two more grow back. There is no minimum viable product here. Fixing one head changes nothing. What it takes is a maximum viable product from day one.

Why the second time is different

In recent years, we’ve seen a series of inspiring examples of successful founders coming back to take on new problems. Stockholm knows this well: alumni of and have gone on to found and back a long list of new companies, using the credibility from their first successes to try something harder.

The second time around, capital and access both come easier. A successful first exit opens doors to talent, partners and investors that we simply didn’t have with Tink. It is a fantastic opportunity, and one I’m grateful for. You get to bring every lesson from what went well and what went badly, and you start with a real tailwind when people want to work with you and back you.

Money also means you can fund the full build yourself, so no investor asks you to shrink the idea before you’ve tested it.

Maximum viable product

Experience and capital used to get you only so far. Ten years ago, building something this broad would still have needed hundreds of people of various backgrounds, and many years. Language models have changed that. Our team today is 22 strong and growing, and ships at a pace I could only have dreamed of when we first built Tink.

We also feel we’ve grown thicker skin from the bruises of our first 15 years as entrepreneurs.

You know the setbacks are coming, and you know that a venture is never a one-man sprint but a team marathon. None of that guarantees success. But it’s a good place to start if you want to stand your ground and build your biggest vision yet.

is the CEO and co-founder of , the Stockholm-based AI-native compliance company that came out of stealth in September 2026. He previously co-founded the open banking platform in 2012 and led it as CEO through its growth to a multimarket operation with around 700 employees before its €1.8 billion acquisition by in 2022.

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Twenty-one of last month’s new unicorns are U.S. headquartered. Six new unicorns joined the board from China and three from the U.K., while Canada, Saudi Arabia, Japan, Israel, Italy, Finland, Germany and Bulgaria each added one new unicorn.

Through September, 311 companies have joined the board so far this year, putting 2026 on track to be the second-highest year for new unicorn creation, following only the venture peak year of 2021, when counts topped 600.

Several companies already on the board stand out for significant valuation increases via new raises last month. They include San Francisco-based , developer of AI for software engineering, which saw its value climb to $48 billion, up from $26 billion only four months earlier. Data center provider was valued at $31 billion last month, up from $10 billion a year ago. And Paris-based frontier lab was valued at $24.4 billion in its more recent funding, up from $13.7 billion a year ago.

New unicorns in September

Here are September’s 38 new unicorn companies:

Semiconductors

• , an Austin-based semiconductor manufacturing startup, closed a $500 million Series A at a $3.7 billion valuation, led by . The 3-year-old company builds compact chip factories and develops their manufacturing equipment internally, aiming to make semiconductor production more accessible.
• , an Irvine, California-based semiconductor company, raised a $275 million Series C, valuing it above $3 billion and bringing total funding to $415 million. , and led the round. The 2-year-old company develops digital signal processing chips for high-speed optical connectivity in AI infrastructure.
• , a Hangzhou-based AI chip developer, announced a $149 million Series C. Its IoT inference chips combine memory and computing to reduce power consumption and data movement. The 5-year-old company was valued at $1 billion.
• , a Beijing-based AI chip company, raised $298 million at a valuation of $2.2 billion. The 4-year-old company develops AI computing chips using the open RISC-V architecture.

• , a San Jose, California-based developer of specialized AI chips and software, raised a $150 million Series C at a $1.45 billion valuation, co-led by and , bringing total funding to $500 million. The proceeds for the 8-year-old company will support its software platform and next-generation hardware for robots, vehicles and drones.

Financial services

• , a Texas-based prediction-market platform, announced a strategic partnership with , which will take an equity stake following OG’s separation from . The less than 1-year-old company was valued at $5 billion. The investment amount was not disclosed; the partnership will route Robinhood event-contract trading through OG’s regulated exchange and clearing infrastructure.
• Saudi Arabia-based , a digital payments company, raised a $329.5 million Series A at a $1.85 billion valuation. Investors included , and . The 3-year-old company has processed more than $117 billion in 2 years.
• , a Nevada-based financial software company, raised a $250 million Series E at a $1.43 billion valuation led by founder and chairman . The 8-year-old company provides an AI-based investment management platform for asset and wealth managers.
• , a Miami-based remittance platform for Latino immigrants operating through , secured $200 million in financing: an $87 million Series C equity round led by valued at $1.4 billion and $113 million in debt from ’s Customer Value Fund. The 5-year-old company plans to expand to lending and add to its Latin American reach.

Space technology

• Munich-based space company raised a $450 million Series C, co-led by , and at a valuation of $2 billion. The financing for the 5-year-old company will advance its reusable Nyx spacecraft for an International Space Station mission and support development of its Storm rocket engine.
• , a Seattle-based satellite connectivity company, raised a $200 million Series C at a $1.6 billion valuation, led by , bringing total funding to approximately $300 million. The 5-year-old company enables standard Bluetooth devices to connect directly to satellites for tracking and sensor-data applications.
• Oxfordshire, U.K-based , a satellite company, secured $346 million, co-led by and, valued at $1 billion. The 11-year-old company manufactures satellites and provides infrastructure, connectivity, Earth observation and intelligence services.
• Bulgaria-based , a satellite company, raised $205 million in a round co-led by and , reaching a $1 billion valuation. The 11-year-old company has raised financing that will expand standardized spacecraft production, including new manufacturing capacity in the U.S. and Europe.

Biotechnology and medical devices

• , a Framingham, Massachusetts-based developer of treatments for Alzheimer’s disease and other neurodegenerative disorders, raised around $79 million. The �� 13-year-old company was valued at $1.9 billion. Investors were not disclosed.
• Shanghai-based , an AI drug discovery company, raised $290 million at a $1.5 billion valuation following its spinoff from . , , and co-led the round. Anew develops tools for biomolecular prediction and drug discovery; ByteDance retained a 56% stake.
• , a New York-based brain-computer interface developer, closed a $250 million Series D, bringing total funding to $430 million and reaching a valuation of approximately $1 billion. and led the round. The 5-year-old company is building a brain–computer interface that is minimally invasive and removable.
• Toronto-based , a biotechnology company, raised $153 million at a $1 billion valuation led by the , with participation from and other investors. The 3-year-old company uses AI to identify abandoned drug candidates that could succeed under different treatment approaches. The financing will expand clinical development and support additional drug acquisitions.

AI and internet infrastructure

• , a San Francisco-based AI cloud infrastructure company, raised a $300 million Series B at a $3 billion valuation, led by . The 3-year-old company distributes AI inference workloads across different types of chips to improve performance and efficiency. It announced in March that its customers include one of the leading frontier labs.
• Helsinki-based , an AI cloud company, raised a $189 million Series B led by . The financing valued the 6-year-old company above $1 billion with total funding over $450 million. The company manages physical data centers along with its cloud platform.
• London-based , an internet infrastructure company supporting content delivery for large streaming, gaming and software companies, raised $570 million in its first external financing led by . The 15-year-old company was valued at $1.9 billion.

AI training

• , a San Francisco-based AI training-data company, raised more than $100 million led by at a $4 billion valuation, an eightfold increase from its valuation in September 2025. The 4-year-old company recruits and vets specialists who create training and evaluation data for AI developers. that participants included two frontier AI laboratories and two co-founders.
• , a San Francisco-based provider of expert-created AI training data, reached a $3.2 billion valuation in September, earlier, according to . The funding amount and lead investor were not publicly disclosed. The 1-year-old company’s datasets capture professional reasoning in fields such as software engineering, law and finance. AfterQuery was part of the Winter 2025 batch.

Robotics and autonomous driving

• , the Shanghai-based operator of Hello’s robotaxi business, raised about $100 million at a valuation close to $3 billion. fund led the round. The financing to the 1-year-old company will support a 10,000-GPU computing cluster, AI model development and commercialization of Level 4 autonomous driving.
• , a Sunnyvale, California-based robotics perception company, raised a $165 million Series C at a $1.6 billion valuation, led by . Founded by former and engineers, the 5-year-old company combines custom chips, sensors and spatial software to help robots perceive their surroundings. The financing will accelerate deployments across logistics, manufacturing and inspection applications.

Health insurance

• , a San Francisco-based health benefits company, announced a $200 million Series C at a $2.7 billion valuation. led the financing. It also includes $400 million in secondary financing for existing investors. The 7-year-old company provides a benefits platform using AI to make healthcare more affordable for small and midsize employers. The company services 5,000 businesses.
• , a San Francisco-based health benefits platform, raised a $108 million Series C at a $1 billion valuation. Investors included , , and . The 5-year-old company helps employers provide individualized health budgets for employees to select their own medical plans.

Energy and EV infrastructure

• China-based , a battery-swapping and charging company, agreed to a strategic transaction that gives a 30% stake. Geely will contribute its Yiyi battery-swapping operation and a $95 million investment. The 9-year-old company was valued around $2.4 billion.
• , an Austin-based developer of off-grid power systems for AI data centers, raised a $120 million Series A at a $1 billion valuation, led by . The less than 1-year-old company builds modular systems for renewable energy and battery systems as data-center operators seek access to electricity.

AI applications

• raised $150 million led by , at a valuation just over $2 billion. The 3-year-old company, headquartered in London with offices in Los Angeles and Mumbai, built an enterprise audiovisual content platform for media, advertising, sports and healthcare customers. The financing will support research, commercial expansion and a larger Silicon Valley presence.
• , a New York-based AI ranking and personalization company, raised a $90 million Series B at a $1.44 billion valuation, led by . The 2-year-old company’s software helps enterprises respond to customer behavior in real time, improving the relevance of recommendations.

Cybersecurity

• Rome-based , a cybersecurity company protecting connected devices and autonomous machines, raised $270 million at a $1.7 billion valuation, led by . The financing to the 8-year-old company will support U.S. and Asia-Pacific expansion and development of AI security models.
• Tel Aviv-based , a consumer cybersecurity company, raised $40 million at a $1.1 billion valuation, bringing total funding to $167 million. co-founder joined existing investors including and , among others. The 8-year-old company protects consumers against phishing, scams, malicious websites and AI-generated fraud.

AI models

• Beijing-based , a language-model startup, raised $120 million reaching a valuation of $1.4 billion. Investors include , , and . The less than 1-year-old company raised $400 million across three rounds so far this year, before releasing its first public model.
• , a San Francisco-based developer of open-weight foundation models, announced a $150 million Series B led by , and , valuing the company above $1 billion. The financing will support the 3-year-old company’s Trinity models and products for customizing and operating them.

Manufacturing and construction software

• , an AI company for manufacturing with dual headquarters in Tokyo and Chicago, raised a $114 million Series D at a $1.2 billion valuation, bringing total funding to $234 million. Investors included and . The 9-year-old company’s platform organizes design and procurement and production; the financing will deepen its technology and accelerate North American expansion.
• , a Georgia-based construction software company, secured a growth investment of $250 million led by , valuing it above $1 billion. The 17-year-old company manages construction projects, with the investment supporting its AI capability build out and commercial growth.

Defense technology

• , a Washington, D.C.-based defense company, emerged from stealth with $250 million raised across three rounds at a valuation above $1 billion. The 2-year-old company develops long-range cruise missiles with manufacturing in Texas, Germany and Israel. Backers who have led across three rounds include , , , 1, and .

Food

• , the New York-based parent of consumer food brands David Protein and HallPass, raised a $250 million Series B at a $2.25 billion valuation. and co-led the round. The financing to the 2-year-old company will expand retail distribution, develop new products and support additional brands.

Related ������Ƶ unicorn lists:

• (1,901)
• (666)
• (321)
• (198)
• (119)
• (102)
• (998)
• (547)
• (258)
• (39)
• (489)

Related reading:

• ������Ƶ Data: Q3 2026 Posted A Record Count Of Billion-Dollar Rounds As The Global AI Race Heats Up
• 29 Companies Joined The ������Ƶ In August, Led By AI Software And Semiconductors

Methodology

The ������Ƶ ������Ƶ is a curated list that includes private unicorn companies with post-money valuations of $1 billion or more and is based on ������Ƶ data. New companies are as they reach the $1 billion valuation mark as part of a funding round.

The unicorn board does not reflect internal company valuations — such as those set via a 409a process for employee stock options — as these differ from, and are more likely to be lower than, a priced funding round. We also do not adjust valuations based on investor writedowns, which change quarterly, as different investors will not value the same company consistently within the same quarter.

Funding to unicorn companies includes all private financings to companies that are tagged as unicorns, as well as those that have since graduated to .

Exits analyzed here only include the first time a company exits.

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.

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You have likely never heard of . You should have.

Over the past decade, Tosin and his team built into the operating system for more than 6 million Nigerian businesses, , or .

As a Nigerian American, I’ve witnessed my father make trips to Western Union to send money back home for decades, and I experienced Nigeria’s fee-laden payment system when visiting the country. Moniepoint is transforming that system.

Moniepoint is not alone. , , , , ��1 — these are companies most Americans have never heard of, despite them being worth several tens or hundreds of billions, following the trail blazed by , and .

These are super apps that bundle banking, commerce, ride-hailing and bill pay into one trusted application. The idea never took hold in the U.S. for one reason: trust is cheap here. With , a specialist app inherits the credibility of the financial system. Where trust is cheap, there is no need for a super app.

Build trust first

In emerging markets, trust is the whole problem. Four conditions tend to precede a super app: High mobile penetration, which makes distribution cheap; weak incumbent competition; poor existing financial services; and the condition most investors screen past, a financial crisis severe enough to strip incumbents of legitimacy. These populations are not merely underbanked. They were harmed, and the institutions that harmed them still hold the market.

Brazil froze roughly 80% of bank deposits and financial investments for 18 months in 1990 in an effort to break hyperinflation. The banking consolidation that followed left five banks and . That was the void Nubank was born into.

Kazakhstan went through it twice: savings erased by inflation in the thousands of percent when the ruble zone collapsed in 1993, then a 2007–09 banking crisis in which the country’s largest bank, BTA, holding roughly a quarter of the system’s assets, Kaspi grew into that void.

Southeast Asia’s 1997 crisis was harsher still. Indonesia closed 16 banks in a single announcement, the %. Two decades later which enabled Sea to build and into that gap.

Kaspi also answers the objection I hear most from American investors, which is that these markets are too small to produce large exits. Kazakhstan has only 20 million people, and according to company , around 14 million — nearly 70% of its population — use Kaspi. The . It earns . Depth of spend, not population, sets the ceiling.

Compare Nubank to . Nubank has 14x the customers, to , about 7x the revenue and a market capitalization more than 6x larger. Nubank . A technology applied in an overlooked market with a large unaddressed pain point can build a bigger and more defensible company than the same technology applied in a rich one.

Screen for the four conditions and a few markets stand out as places where the next super app could emerge:

• Bangladesh: , with the government now promising to pay 7.5 million savers whose money is gone.
• Egypt: Repeated devaluations of the pound between 2016 and 2024, shrinking savings held at banks the state itself owns.
• Vietnam: after its owner was arrested in a $24 billion fraud.
• Pakistan: , then government-built rails and a national ID that makes onboarding nearly costless.

One boundary condition: The crisis must be severe enough to delegitimize incumbents but contained enough that the currency and payment rails still work.

The first generation of super apps created enormous value for the investors who backed them early. In 2001, the South African media company paid roughly $34 million for a 46.5% stake in Tencent, and . ’s investment in Nubank’s $2 million seed round, combined with its lead Series A investment, was worth $7 billion at the company’s IPO.

The second generation is scaling now. The third will be built on stablecoins and AI technologies, in Abidjan, Buenos Aires, Karachi and Lagos, by founders like Tosin Eniolorunda who will play an increasingly important role in the growth of emerging market economies.

�� is co-founder and managing partner of , where he oversees the firm’s investing strategy, governance and compliance, with a focus on fintech and enterprise technology. Since co-founding 645 Ventures in 2014, he has invested in and partnered with companies including , , , , and . Previously, he was an investor at , where he invested in 19 companies and had nine exits representing more than $9 billion in exit value.

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Before was building cybersecurity software, he was performing in his father’s magic shows.

The son of a magician and an acrobat, Cielen spent his first five years living on a cruise ship, followed by five years in Las Vegas. At 10, he moved to Montreal, where he entered an intensive ballet program, spending mornings dancing and afternoons in school.

“I was rather introverted as a child, but I became extroverted through the unique upbringing,” Cielen recalls.

By 15, he had skipped two grades, started college and launched a website design and development business. A later trip to a hackathon in Waterloo introduced him to venture capital investors. That same week, he said, he dropped out of school, quit an algorithmic trading internship and flew to San Francisco to start.

Now, the startup is emerging from stealth announcing it has raised $4.2 million in seed funding to help companies detect and stop unusual data activity, including the theft of sensitive information, it tells ������Ƶ News exclusively.

led the round, joined by,, Brickyard,,, the and. The financing brings Hilt’s total funding to $4.7 million, including a $500,000 pre-seed round led by in October 2025.

Finding the problem

When Cielen, Hilt’s co-founder and CEO, arrived in San Francisco, he had settled on cybersecurity but was still figuring out which problem to tackle. He had previously attended in Montreal and worked as an algorithmic trading intern at the.

“I had to do a lot of customer discovery,” he said, describing his efforts to understand the market and talk to potential customers, “to see what the real problems were, not to build in the dark.”

A pivotal conversation came in January, when the chief technology officer of a large hedge fund described a security problem in its high-frequency trading operations. Those systems trade in microseconds, Cielen said, leaving little room for security software that introduces delays.

The hedge fund offered a potential contract worth $1 million to $2 million if Hilt could solve the problem, Cielen said. It then paid a six-figure sum upfront before Hilt had even built the solution.

Hilt’s software monitors how data moves across cloud infrastructure, computers and networks, building behavioral baselines for users and resources. It flags unusual activity, even when a user has permission to do it, and claims it can do so without slowing down the company’s systems.

For example, a late-night login might be normal for an employee who often works late. But if someone who only works during the day suddenly logs in at midnight — and has just changed their password — Hilt could flag the combination as suspicious.

Hilt can alert a company’s security team to investigate or, in some cases, quarantine the activity as it happens.

“They don’t have to wake up and see that it happens, but we can actually stop it as it happens,” Cielen said.

The startup’s approach was to work at the kernel, the core of an operating system, and stream activity data to graph neural networks, a type of AI model, that identify anomalies. Cielen said that gives Hilt visibility beneath the different software applications its customers use, allowing it to deploy across a range of environments.

He also said one customer’s measurements showed that deploying Hilt sped up its cloud systems.

The company continues to work with the hedge fund and has added another high-frequency trading firm, Cielen said. He said its customer count doubled in the month after it began making a more concerted push to market, though he did not disclose the total.

Hiring and expanding beyond finance

Beyond trading firms, Hilt is seeing interest from neobanks, healthcare businesses, professional services firms and other businesses that deal with sensitive information. Customers run the product within their own infrastructure, retaining control of their data, and pay an annual fee per data collector.

The startup has 11 employees, including co-founder and CTO and founding engineer. Originally based in San Francisco, the team moved to Chattanooga, Tennessee, with investor as it works toward product-market fit.

Cielen said the new capital will primarily support hiring and building a market presence.

“The money is very useful for hiring the best people,” he said.

Investor POV

, general partner of Array Ventures, said most tools in this space do one of two things — either predict what’s sensitive upfront “and get it wrong a lot, or they tell you what happened after the data is gone.”

“Hilt can find and stop these breaches in real time, with accuracy,” she wrote via email. “It also runs entirely inside the customer’s own environment, so nothing leaves the company. For a bank or government entity, that is the difference between proactive vs. reactive response.”

She also pointed out that today’s commonplace breaches don’t always look like attacks.

“They look like normal activity such as an employee using valid access, a connected vendor, or an AI agent doing what it’s allowed to do,” she said. “Hilt connects these actions and detects when normal behavior becomes suspicious. As AI agents increasingly interact and act autonomously, we think this problem will only grow, and we wanted to get ahead of it.”

, founder and managing director of Verdict Capital, said he was drawn to invest in Hilt mainly because of its founder.

“At Verdict Capital, we back founders who are obsessed, have high velocity and are learning animals,” he wrote via email. “Will exemplifies these traits.”

Bonatsos, a former investor at who founded Verdict in early 2026 and also backed Mercor, said he was also impressed with Hilt’s approach, noting that Hilt was one of the first checks the Verdict team wrote.

“Most security tools look at content: files, signatures, known threats. Hilt looks at how data moves, at the kernel, which is the one place you can’t hide from,” Bonatsos said. “Everyone assumed you couldn’t sit that deep without slowing systems down. They did it in live financial environments… Selling security into banks is about as hard as enterprise sales gets, and I watched them do it.”

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, an alternative investment firm specializing in asset-backed credit, led the round, which also included participation from , , , and as well as , , , and .

Homeward has now raised $360 million in equity since its 2018 inception. The company declined to disclose the valuation at which it raised the latest round, saying it was similar to its valuation at the time of its in 2021, when it was reported to be “just north of $800 million.”

Austin-based Homeward has also secured a $330 million asset-backed debt facility to fund more home transactions. The equity funding will support expansion of its financing products and investment in its technology platform.

Its recent funding comes amid an uptick in startup investment to the proptech category this year. So far in 2026, global real estate-related startups have pulled in about $12.7 billion in seed- through growth-stage investment, per ������Ƶ , putting this year on pace to top last year’s funding, which totaled $12.3 billion. Investment in the sector still pales compared to the peak years however: In 2019, the second-highest year on record after the 2021 venture funding spike, real estate-related startups raised $24 billion, ������Ƶ data shows.

Cashing out before a sale

Homeward works through real estate agents to help clients access the equity tied up in their homes and navigate the timing of buying and selling. Its Buy Before You Sell program provides short-term financing so homeowners can purchase their next house before selling their current one, along with a guaranteed backup offer for the existing property.

For homeowners seeking a faster sale, its Sell Before You List program offers a cash purchase and a closing in a matter of weeks. Homeward then fixes up the property and resells it on the open market, returning the profit to the original homeowner while charging a program fee.

“We realized that there’s an opportunity to help homeowners sell their home fast without sacrificing all of their home equity like they would have to if they sold to an investor,” founder and CEO told ������Ƶ News in an interview.

The financing has helped Homeward roll out its cash-offer program across the 48 contiguous states, Heyl said. The company also plans to make its Buy Before You Sell program available nationwide by year-end.

The expansion follows a pivot that Heyl credits with helping Homeward more than quadruple revenue since 2021, even as U.S. home sales fell roughly 30%, according to his estimates.

“Our ability to really exponentially grow over the last four years or so was a huge thanks to the pivot,” Heyl said, pointing to its Sell Before You List product, which is aimed at “the home sellers that are still transacting.”

Over the years, Homeward says it has partnered with more than 25,000 real estate agents and facilitated over $4 billion in transactions.

A pivot as homeowners stayed put

From 2019 through 2022, Homeward focused exclusively on helping homeowners buy their next house before selling their existing one. The offering appealed to agents and consumers competing in a tight housing market, and the company grew quickly, Heyl said.

But rapidly rising interest rates made that customer base harder to reach. Homeowners who might otherwise have moved into a larger or smaller house stayed put as moving costs rose.

“It became more expensive, definitely a lot more expensive, to move up, but even for a lot of people, more expensive to move down,” Heyl said.

Homeward responded by broadening the types of sellers it could serve. While fewer people were buying and selling at the same time, some homeowners still needed to sell without buying another property. And with homes taking longer to sell and prices less predictable, Heyl saw a growing demand for cash offers.

In early 2023, Homeward launched Sell Before You List. The distinction, in Heyl’s view, is that Homeward offers a service to sellers rather than seeking to capture the upside from buying and reselling their homes.

“Once we fix the house up and sell it for its full price on the open market, we send that profit back to the original homeowner,” he said.

Homeward also reworked its original Buy Before You Sell offering, lowering its cost and simplifying it for a market in which homes no longer routinely sell over a weekend with multiple offers. That business has contributed significantly to growth over the past year or so as more homeowners have begun making moves again, Heyl said.

“Most homeowners that are trying to move up or move down still plan to use the majority of their home equity to make that next purchase,” he said.

Homeward also offers Buy With Cash, which lets buyers make cash-backed offers and refinance into a traditional mortgage after closing.

Direct-to-consumer marketing without the cost

The company’s distribution strategy centers on real estate agents. Homeward has partnered with more than 25,000 agents and facilitated more than $4 billion in real estate transactions, according to Heyl.

Rather than pursuing individual consumers, it seeks ongoing relationships with agents, teams and brokerages that can repeatedly bring clients to its programs.

“We don’t spend a dime going direct to consumer,” he said. “We don’t advertise. We don’t market.”

Some agents incorporate Homeward’s offerings into their own marketing under their own brands, also known as white-labeling. Others turn to the company when a client’s existing home or access to equity keeps them from making a new purchase.

“Sometimes it’s just unblocking the transaction,” Heyl said.

That growth in a difficult market helped attract Saluda Grade, which is backing Homeward for the first time. , who runs the firm’s growth equity fund, said the team’s understanding of the problems facing buyers, sellers and agents stood out when compared with other “similarly situated” operators it had met.

“They really understood the core issues they were addressing,” Stepp said. “It was evident in their financial performance and their growth.”

Geographic expansion was another draw, he said, with the capital raise creating an opportunity to bring Homeward’s products to more markets.

“We recognize the product-market fit, and how useful this product set really is to eliminate some of the friction in the home transaction process for consumers,” Stepp told ������Ƶ News in an interview, “and how useful of a tool it is for agents to be able to offer this.”

Using AI to speed up underwriting

As many other startups, Homeward is incorporating AI into its workflows. For example, the company is using AI to reduce the manual work involved in processing transactions and underwriting properties.

Large language models extract information from documents and help underwriters review property videos, photos and inspection reports. It does this by pulling out relevant details about roofs, heating and cooling systems, and a home’s condition, according to Heyl.

“AI has been huge for streamlining operations and underwriting,” he said.

For Heyl, the broader opportunity is to continue addressing the financing and timing problems that complicate home purchases and sales, even as the housing market changes.

“There’s been a major pullback, but it hasn’t changed the opportunity that exists to solve problems for buyers and sellers,” he said.

The company makes money in several ways. Buy Before You Sell carries a 1% program fee and a monthly interest cost. Sell Before You List carries a single program fee, with no monthly charge. Heyl did not specify the fee for that offering.

Homeward also generates revenue through its in-house mortgage and title businesses. Heyl said providing more services within the transaction can simplify the experience for buyers and sellers while reducing the program fee Homeward needs to charge.

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Related reading:

• Sector Snapshot: Proptech Funding Holds Up, But Investors Are Placing Different Bets
• Sector Snapshot: Real Estate Tech Funding Sees Slight Rebound, But Still Far Lower Than Peak Years

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From January through August U.S. tech layoffs reached at least 94,046, up 16.8% from 80,486 in the same period of 2025. Interestingly, and unsurprisingly, many of the cuts came as tech companies redirected spending toward AI and restructured operations to reduce costs.

The year started off on a busy note on the layoff front. After job cuts dropped sharply in December 2025 to 5,151, they surged in January to over 20,000. May was particularly brutal. The month drove the year-to-date increase, recording 31,513 layoffs — including ’s 8,000-job reduction — the highest monthly count since March 2023, when layoffs reached 36,602.

Recent months indicate a slowdown. Layoffs fell each month after May, reaching 2,347 in August. Overall, June-August 2026 layoffs totaled 19,331, down 16.2% year over year. The decline suggests recent easing, though it is too early to establish a lasting reversal.

Artificial intelligence has become a much more common explanation for layoff decisions, noted , founder of AI was cited in 33% of tech layoff events this year, up from just 1% in 2024. His tracker attributes 92,913 layoffs globally, or 72% of this year’s total, to AI.

“There’s been little evidence that AI is actually replacing the work of the human employees let go,” Lee said of this year’s largest AI-attributed layoffs. He believes established tech companies are spending heavily on AI and cutting costs elsewhere, hoping to increase productivity with smaller workforces.

Companies cutting

This year, we’ve seen a number of Big Tech and publicly traded companies, as well as startups, make deep cuts.

But interestingly, as with last year, public tech companies have dominated layoff headlines in 2026 so far, led by and Meta.

“Big companies [have] made up about 87% of everyone laid off in 2026, which is similar to last year, when they made up 85%,” Lee said.

Amazon accounted for 17,388 cuts this year so far through August. Those included a 16,000-worker RIF announcement in January and several smaller subsequent rounds. Meta was next with 10,400 layoffs, including an 8,000-job reduction carried out in May that represented 10% of its workforce.

and recorded the next-largest totals, letting go of 4,800 and 4,760 employees, respectively. , and each recorded 4,000 layoffs, followed by with 3,000, with 2,900 and with 2,600. Notably, the Top 10 list spans a variety of sectors, including cloud computing, social media, payments and enterprise technology.

We should also note that according to reports, ’s workforce fell by about 21,000 employees in its fiscal year ended May 31, 2026, but the worker count and exact timing for each of�� those reported cuts was unclear, so we did not include that total in our tracker.

Among privately held companies in the tracker, recorded the largest disclosed total at 1,000, followed by HR software provider with 950 and with 500. Those figures were substantially smaller than the largest public-company reductions, although undisclosed layoff counts limit comparisons between the two groups.

And in early September, reportedly laid off 3,300 workers, or 10% of its workforce.

An AI focus

, of , says AI is affecting jobs in two ways. Some work, including coding, can now be done with fewer people. “There are jobs that are literally being replaced by artificial intelligence,” he told ������Ƶ News.

But companies are also changing their priorities. They’re putting more money into AI and cutting teams working on other parts of the business. “They’re letting people go from one area of their organization while they might even be hiring in an area that is focused on AI,” Challenger said. That’s why a company may lay people off and advertise new jobs at the same time.

Tech has announced more job cuts than any other industry this year, Challenger said. Across the U.S. economy, layoffs are down somewhat from last year, though that comparison is skewed by the large number of federal job cuts in 2025. When compared with the period just after the pandemic, when employers struggled to find workers, layoffs remain elevated.

Few companies outside tech have blamed job cuts on AI so far, Challenger said.

It’s not all negative though, in his view. There’s potential upside for programmers, he said. If AI makes software less expensive to build, companies in other industries might embark on projects they couldn’t afford before. That could mean new jobs outside tech, though it’s too early to know whether those jobs will make up for the ones being cut.

Also, it appears that some companies might be regretting their layoff decisions. Amazon is reaching out to eligible former employees about open roles across the company, including in its cloud-computing and AI businesses, according to a�� report.

Methodology

Layoffs figures are from The ������Ƶ Tech Layoffs Tracker, where we record reported job cuts at U.S. tech employers. The tracker includes layoffs conducted by U.S.-based companies or those with a strong U.S. presence — both privately and publicly traded — and is updated at least bi-weekly. Layoff and workforce figures are best estimates based on reporting. Actual layoff figures are likely much higher than reported as many companies do not disclose the number of jobs cut when announcing layoffs. For more about our methodology for tracking layoffs, refer to the tracker’s methodology section.

Related reading:

• The ������Ƶ Tech Layoffs Tracker

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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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