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.

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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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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.”

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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.

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Founded in 2016, Los Angeles-based Fifth Wall has grown into one of the largest investment firms focused on real estate technology, with roughly $3 billion in commitments and capital under management. Its portfolio includes , , and .

Notable exits include , which went public in 2024, and flexible workspace provider , which real estate giant of in January 2025 at a valuation of more than $800 million.

Major real estate and hospitality companies — including CBRE, , and — are among its investors, giving the startups it backs a direct connection to potential customers.

Wallace, who serves as CEO and chief investment officer, brings experience on both sides of that relationship. He worked in real estate finance at and before co-founding workforce analytics startup , which was acquired by in 2014, and ridesharing company .

As AI makes certain products easier to replicate, Wallace sees growing potential in startups that use technology to own and operate real estate themselves.

In a recent interview with ������Ƶ News, we discussed that shift, why proptech funding totals may overlook some of the sector’s biggest investments, what it all means for founders, and the housing problems he believes still need solving.

This interview has been lightly edited for brevity and clarity.

������Ƶ News: Our recent proptech funding analysis showed capital on pace to roughly match or slightly exceed last year, but across fewer deals. What does that tell you about the market?

Brendan Wallace: My sense is that statistic might belie the actual amount of funding flowing in, because what was previously characterized as proptech in the narrowest sense is probably representing a smaller share of where proptech investors are deploying capital.

There are increasingly horizontal solutions that are just as good, if not better, than many of the vertical solutions we’re seeing. We recently made a very big investment out of our growth fund into , the visualization software company. Most people reflexively think of that as being for movies or rendering scenes. But we saw real estate agents and commercial leasing brokers using it to represent spaces.

For an unbuilt home, you could feed it blueprints, have it build an entire home, put your family inside and walk through it in a full scene. That had surpassed the industry-specific solutions for space visualization that would have been narrowly defined as proptech.

Another category is investment flowing into full-stack businesses: real estate companies themselves. We just invested $135 million into , and I would be surprised if that fell under the definition of proptech.

Those are probably the two categories that might not be captured: horizontal software, with Higgsfield as an example, and businesses that reimagine physical space based on autonomy, AI or robotics. They’re actually building a physical thing. They’re building a real estate company, directly or indirectly.

How much is AI driving that shift toward software that serves multiple industries?

Wallace: It’s a big part of it. Without something profoundly better that you can’t replicate on your own, there’s less justification for buying outside software. There still is a justification, to be clear. There’s just less of one.

No real estate company can build the kind of visualization software Higgsfield has. I don’t believe they ever will. But a tenant engagement app they might have previously purchased and rolled out to their assets, they can now replicate over a long weekend.

The imperative to buy these third-party solutions has been reduced, and more value has been placed on the best horizontal solutions, whether that’s a foundation model or a specific use case like sound, audio or visual.

I don’t know the statistic, but it would be interesting to know how much real estate companies are spending on foundation models versus proptech applications. If I had to guess, we’re probably close to, or at, an inflection point where it’s passing it.

No one would characterize as a proptech company, but it might be taking a significant amount of the upstream proptech dollars, and an even larger share downstream once you go through the application layer.

Has AI reset the bar for what makes a venture-scale proptech software company? What does a startup need beyond adding AI to existing workflows?

Wallace: We’re still figuring that out, but I think it has to be something that can’t be replicated. Anything where the intellectual property moat is not extremely defensible is very challenged, and I think it will be for some time.

Simple application point solutions are becoming less financeable by venture investors because the capacity of one of the large labs to build that as an interface, or of a company to build it on its own, has caught up so dramatically.

The flip side is that bespoke AI development labs are now building solutions for the real estate industry. We backed one called , which is kind of like a for real estate. Antares works with a number of our strategic limited partners. They go in-house, identify a problem they think can be solved with an AI-based solution, build the intellectual property specifically for the organization, and leave it with them.

It’s more of a fee-for-development model than an intellectual property licensing model. You’re seeing that across industries, and you’re absolutely seeing it in real estate.

In some sectors, founders argue that domain expertise gives specialized AI companies an advantage over broad models. How durable do you think that advantage is?

Wallace: I’m a little more optimistic about foundation models’ and general intelligence’s capacity to adapt rapidly to specific use cases.

I wouldn’t argue that specific legal expertise, for example, is not valuable. But I think that moat collapses over time. You might be on a treadmill.

Think about what ChatGPT looked like in 2023 versus what Claude looks like today. At a basic level, it’s the same thing, but they’re totally different things. The sophistication, memory, capacity to be personalized, and ability to build off natural language instructions are unlike anything I think anyone could have anticipated in 2023.

What will that look like in 2029? I think what you’re saying is true today. It’s less true than it was, and it might become even less true in three years.

Is construction technology still an area of focus for Fifth Wall?

Wallace: It is, but it’s less of a focus today. When we look at our performance, it has generally favored two things: pure software businesses, whether marketplaces, consumer software or enterprise software, and full-stack businesses.

Anytime you get into physically doing things, the risk profile changes pretty profoundly. I don’t think it should be surprising that construction tech broadly is probably the biggest graveyard in all of venture. Maybe there’s a bigger category, but if there is, it’s not obvious to me.

Why do you think construction tech continues to attract significant funding?

Wallace: Because it’s still a massive market and a huge problem. If someone can bring greater efficiency to construction, you’re talking about one of the largest markets on earth. It’s such a massive prize that the largest funds are going to focus on it.

For founders raising seed or Series A funding, what opportunities would you encourage them to pursue that might not have been fundable a few years ago?

Wallace: You can actually build new real estate companies. That hasn’t really been conceptualized as being within a venture mandate, but it’s absolutely something we’d like to see.

For example, we have a better approach to buying multifamily assets, stripping out costs, and running more of the processes, operations and management with AI. That’s something I think is eminently fundable today by Fifth Wall and many venture funds. I don’t think that would have been the case five years ago.

I’d encourage founders to look at building full-stack, capital-R real estate businesses.

The second opportunity is around data. Real estate is characterized by extremely opaque data in a way that’s different from most large financial markets. Nothing that’s happened in proptech in the past 10 years has fundamentally changed that.

Where can generative AI provide signal through that opaque data to make capital allocation decisions? Real estate is generally a cash-flowing asset. We don’t necessarily think of it as comparable to bonds or stocks, but it is, and it should be.

Can you derive signal by looking at more data or different data, or use generative AI to predict what kind of real estate will perform better? The quantitative model that has existed for securities for a very long time now has the potential to affect real estate, because we have computational capacity that wasn’t previously possible.

Are there opportunities you’re interested in that have less to do with AI?

Wallace: We’re intrigued by the intersection of land, real estate and the financial instruments around them. To make most of what we describe as real estate, you usually have to build something on land. Land is an input to almost all real estate, but many real estate owners don’t want to own it or take on that risk profile.

Is there a way to decouple having to own land from owning and operating a building? That’s less about AI and more about financial engineering. There are new financial solutions emerging in that category that interest us.

How could AI, robotics and autonomy change the kinds of real estate businesses founders build?

Wallace: I’m interested in entrepreneurs who can conceptualize real estate through a sociological lens: New catalysts are changing how humans use space compared with the past.

That’s happened for a long time. E-commerce built the modern industrial real estate industry. Cloud computing, the internet and now AI built the data center industry. Cell towers were born out of mobile phones and smartphone technology. Genome sequencing helped create the lab-space real estate asset class.

I think we’re on the precipice of three new catalysts that will spawn entirely new real estate asset classes: AI, robotics and autonomy. In many ways, they’re entangled.

Do you expect fewer dedicated proptech venture firms? What would that mean for founders?

Wallace: I do think you’re going to see fewer vertical funds, in the narrowest sense of where we started this conversation. Dedicated venture capital funds investing in consumer and enterprise software focused on an industry —– I think you’ll see less of that, and funding will probably continue to go down in that category.

The inverse is venture capital funding real estate businesses themselves. I think that’s about to explode.

If you were starting a company in this sector today, what problem would you most want to solve?

Wallace: Housing drives everything. Housing costs drive our economy, and the U.S. is grappling with a very real housing affordability crisis. It’s unclear how to solve it.

There are multiple approaches. One is building homes better, faster and cheaper — that’s construction tech. Another is financing homes at a lower cost. How do you bring efficiency to the housing finance market?

That’s a place where we’ve made a lot of money and invested a lot, but I would argue it’s still unsolved. Getting a mortgage is still painful, archaic, slow and too expensive.

Related to that is making regulation more efficient to improve housing affordability. That’s not something an entrepreneur can solve alone, but there’s potential to bring efficiency to how cities deal with this problem.

There’s an intersection of regulatory technology, policy work and consulting. How do we make it so more people can afford homes in the cities they live in? That problem isn’t going away. Despite everything that’s happened, housing has gotten more expensive, not less.

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and co-led the round, bringing the Minneapolis-based startup’s total funding to about $15 million since its 2023 inception, according to co-founder and CEO .

The company says its revenue has grown 357% year over year. Its customers include major AI companies and businesses in telecommunications, entertainment and retail, although it declined to identify them, citing the sensitive nature of its work.

Gudea’s premise is that tracking mentions and hashtags tells companies only part of the story. The startup aims to map how information moves across people, groups and platforms, then predict how far a narrative will spread, when it will take off, and when it will fade.

Presley describes Gudea as the “storm tracker for the internet.”

“As a meteorologist uses patterns to predict the weather, we’re using patterns to predict information,” he said in an interview, adding that the startup covers over 600 social media platforms.

From disrupting disinformation to tracking brands

The business grew out of the George Washington Initiative, a nonprofit that adapted tactics used by the intelligence community to disrupt online Al Qaeda and ISIS networks for domestic information campaigns. The team initially searched for existing software that could show how information traveled, but found social listening tools insufficient.

, Gudea’s CTO and one of its founders, began working on technology to map those pathways. When the team examined the backlash around Bud Light’s marketing campaign with actor Dylan Mulvaney, it reached a turning point. The campaign’s critics used the same information pathways that had carried COVID disinformation, noted Presley.

The team realized “that these patterns were repeating, and that there was a much broader use case,” he recalled.

The technology spun out into a company in 2023. Its initial commercial focus has been reputational risk management, which entails helping large businesses spot potentially consequential stories before they spread widely.

“We don’t need to know what we’re looking for to find it, so we can find all of those good or bad narratives before you know what keywords you should be searching for,” Presley said.

Who’s driving the conversation?

One way Gudea operates is by assessing whether users or accounts exhibiting unusual behavior are driving online conversations. It also examines how narratives move from less visible online communities into more mainstream platforms.

For example, the startup conducted an analysis of online claims linking to Nazism around an album release. 1 , Gudea’s director of client experience, told ������Ƶ News that the analysis uncovered that the narrative was being manipulated.

The company says its work has also involved cases of corporate espionage and stock market manipulation. More recently, it has been examining how conversations about data centers affect businesses in AI and energy. Its technology can also identify positive trends companies might capitalize on, according to Paul, in addition to reputational threats.

Predicting what spreads next

Gudea uses deep learning, including graph neural networks, to analyze behavior, and uses a large language model to summarize findings.

“Those behavior patterns are like fingerprints, and so our AI then recognizes those fingerprints, pulls it out, and then we use an LLM to summarize,” Presley said.

The company sells its software to businesses through offerings that include alerts, platform access and automatically delivered reports. The latter emerged from its work with senior teams that were unlikely to log into a platform themselves.

Presley cited , and as competitors in narrative intelligence, while positioning Gudea’s predictions as its distinguishing feature.

Gudea tells customers “how long till it goes viral, how many people will be impacted, and how long till it goes away,” he said.

For Gudea, the broader aim remains connected to its nonprofit origins: making the mechanisms behind online information more visible.

“People are making real-world decisions off of what they see online, and not all of that information is authentic,” Presley said.

The startup plans to use its new capital to expand its team, develop new features and broaden its coverage across platforms, languages and regions. It currently has 39 customers and approximately 25 employees.

, investor at Mudita Venture Partners, notes that AI is changing how stories are spread on the internet.

“Damage to a brand is now starting in the fringe parts of the internet and builds momentum before it ever reaches a headline. It’s a big problem,” he wrote via email. “Gudea has built a solution that has the potential to own the market and know more than just the headlines. They can really see what is coming before it’s a problem.”

Most other tools on the market are “reactive and surface-layer,” in Foster’s view, whereas Gudea is more proactive.

“Gudea models how information moves across the internet and hundreds of platforms, so it can spot a problem before anyone knows to search for it,” he added. “Since it looks at behavior instead of content, its ability to be proactive gets better even as the internet gets more clouded.”

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Clarification: The co-lead investors in the article were updated.

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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The buying spree has pushed acquisitions of AI startups by other venture-backed AI companies to 195 through Sept. 29, according to ������Ƶ data — 14% more than in all of 2025. Yet the number of buyers grew just 2%, indicating that increasingly active acquirers are driving much of the increase.

Those deals point to a new phase of competition in the AI sector: Well-funded startups are using M&A to broaden their products and reach new customers faster than they could by building everything themselves. In legal tech, for example, acquisitions are bringing research, regulatory monitoring and litigation tools into broader platforms.

CFO described that calculus in a earlier this year explaining the company’s back-to-back purchases of multiple startups: “M&A is explicitly part of how we accelerate what we’re building. The question we always ask is: does this deal get us somewhere faster than we’d get there ourselves?”

Repeat buyers step up dealmaking

Some of the AI acquirers have returned to the dealmaking table more than once in recent years, ������Ƶ data shows. Across the three-year period, 67 repeat buyers accounted for about 42% of all transactions tracked. OpenAI was by far the most active, with 20 AI-related acquisitions, including 10 this year.

This year’s other repeat buyers include and legal AI startup Legora, which have each announced five acquisitions, followed by legal AI startup with four. Customer-service AI provider and coding company have each made three acquisitions this year, while announced two. Many of the buyers are vertical AI startups acquiring companies in their respective areas.

Several of this year’s transactions are sizable.’s reported $1.65 billion acquisition of was the largest with a recorded price, followed by’s $1 billion acquisition of identity security startup.

Anthropic’s acquisition of, which develops AI for pharmaceutical research, was valued at $400 million. �����Դ���’s $300 million acquisition of, a Los Altos, California, startup that uses customized AI in camera hardware for computational photography, and’s acquisition of, valued at up to $285 million, rounded out the five largest deals recorded in the dataset through Sept. 29.

Overall, prices were disclosed for only 12 of the 195 deals, making it difficult to gauge how much AI startups are spending on acquisitions overall.

Dealmaking has clearly picked up as more AI companies turn to acquisitions — and, in some cases, make them a recurring part of their growth strategy. 1

“It’s all about speed in the AI world,” according to , partner at , which has backed numerous AI startups including Anthropic and Legora. “It’s faster to acquire a team or product than build it yourself. If you’re not growing 10x, you’re not interesting to growth investors, which leaves a gap in the funding market for AI startups that need a home. High valuations have also given AI startups cheap currency to use their stock to get these deals done with minimal dilution.”

What AI startups are buying — and why

The specific companies being acquired offer insight into what AI startups hope to gain from their stepped-up M&A activity.

�����Դ���’s purchases have ranged widely, from healthcare data and scientific-writing software to developer infrastructure, security tools and specialized talent. The San Francisco-based company announced three acquisitions in January alone, setting the tone for a busy M&A year.

In January, it acquired:

• , which built AI software to help executive coaches automate leadership assessment reports.
• , an AI-powered health app that aims to unify scattered medical records from hospitals, labs, wearables and consumers.
• , which provides LaTeX editing, error detection and team collaboration.

In February, OpenAI participated in an deal involving open-source AI agent and its creator, . Then in March, it announced plans to , a creator of open-source tools for software developers. It also snapped up , an open-source tool for testing AI applications.

In June, OpenAI agreed to buy , formerly known as Gitpod, which provides secure cloud environments where developers — and, increasingly, AI agents — can continue working after a user’s laptop is closed. In August, it also picked up , an AI presentation company that converts prompts, notes and documents into editable presentations.

Vertical AI roll-ups

Well-funded vertical AI startups, particularly in legal tech, have also been busy this year buying smaller companies, an analysis of ������Ƶ data shows.

San Francisco-based Harvey’s AI-related purchases have focused on filling gaps around its core platform. developed tools for creating product demos, videos and guides, while built software that helps companies connect customer data and applications with AI systems.

New York-based developed software that helps asset managers capture insights from previous investments and apply them to new deals. That acquisition helped expand Harvey’s presence in the asset management space. Its fourth known acquisition this year, announced Sept. 9, was , which builds open-source tools for testing, monitoring and managing AI agents.

, COO of Harvey, told ������Ƶ News that the company’s M&A strategy is rooted in finding “technical talent with high ownership and deep experience in legal tech or an adjacent space to legal.”

She pointed to Benchmark as an example. The co-founders, she said, “know the asset management space cold, and their name was dropped so many times in customer conversations that it was a natural fit for them to join our team.”

Burke further described the startup’s M&A strategy as “selective but aggressive.”

“We hold an incredibly high bar for talent and when we identify an additive company, we move quickly and will continue to do so this year and beyond,” she added.

Legora has pursued an even broader legal-tech rollup. The Stockholm-based company’s five announced acquisitions this year include:

• , a nine-person Canadian startup whose agents work inside Word and Outlook;
• , a Stockholm company building AI-native legal research tools;
• , an Australian regulatory-intelligence platform that monitors more than 100 areas of law for changes;
• , whose AI agents analyze documents and data for commercial real estate companies; and
• London-based , which helps litigation teams extract facts from large collections of documents, identify inconsistencies and build case timelines.

Sierra’s acquisitions reflect an effort to expand both geographically and beyond conventional customer-service automation. In March, it acquired Tokyo-based enterprise AI startup as part of its expansion in Japan, followed by Paris-based , which helps businesses automate operational work with AI. In July, Sierra bought , a 14-month-old startup developing “long-horizon” agents.

For acquisition targets, joining a larger platform can offer a shortcut to scale even when their own businesses are growing rapidly. TakeOff founder wrote in a July that his company was posting a “near 8-figure run rate” with a team of just three people. “The advice for an AI startup growing at our pace is to hire out a sales team, raise again, and keep going,” he wrote. “We had capital, customers, and great traction,” but the Sierra acquisition offered an opportunity to “accelerate our shared vision and simultaneously build it at a grander scale.”

The surge in M&A activity is driven by both a wider pool of buyers and increasingly active serial acquirers. At this pace, we should expect even more in the months and years ahead.

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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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Meanwhile, on Monday, details from AI giant ’s IPO prospectus, giving potential investors a peek into its financials.

Oura had planned to offer 50 million shares at $40 to $44 apiece and was expected to begin trading Wednesday. At the top of that range, the offering would have raised $2.2 billion. The company says it is delaying the deal despite strong demand and has not set a new date. CEO said Oura has “the luxury of choosing our moment.”

Anthropic is still moving toward an IPO, although its timing remains unclear. A prospectus leaked by Reuters showed that revenue climbed twelvefold to nearly $4.6 billion in 2025 with an operating loss of $8.06 billion. Its staggering nearly $42 billion net loss included roughly $34 billion in accounting charges tied largely to earlier financing.

The document also outlined an eye-watering $518 billion in future cloud, computing and infrastructure obligations. Reuters has reported that a listing is likely to come after the November midterm elections.

Anthropic, the world’s most valuable venture-backed startup, has indicated it plans to beat rival to the public markets. The company could debut as soon as October and raise up to $100 billion via the offering, according to a recent in , while OpenAI, which Reuters says filed confidentially in June, is reportedly now looking toward early 2027.

(������Ƶ’s predictive intelligence tools, meanwhile, point to a slightly longer timeline for an Anthropic IPO, saying it’s more likely to happen in six to 12 months.)

Who’s next

So far, the 2026 IPO class already has a record-setting headliner in .

There are some other candidates. -backed AI cloud provider filed publicly this month , reporting $140.6 million in first-half revenue and a $1.02 billion net loss. , a -backed specialty insurance underwriter, on Sept. 24.

Neither has announced a trading date.

Data center operator is another possible fourth-quarter entrant. Reuters that it had hired banks for an IPO that could raise as much as $10 billion, although the timing remains subject to change.

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“I learned that you can course-correct if you focus on the early life of the baby. If they’re missing certain beneficial bacteria, it can really cause a lot of issues for the infant,” Sew Hoy recalls. “I was reading all this literature and asked my doctors about it, and none of my doctors knew what I was talking about.”

A week after her son’s birth in 2020, she incorporated Austin-based . Today, the company announced it has raised $33 million in a Series B funding round led by , it told ������Ƶ News exclusively.

The financing brings Tiny Health’s total funding to $46 million, following a $4.5 million seed round in 2021 and an $8.5 million Series A in late 2023. Existing investors , and participated in the latest round, along with new investors including and . B Capital’s will join the company’s board.

Demand for Tiny Health’s at-home microbiome tests is growing. The startup’s overall revenue has more than doubled each year, according to Sew Hoy. Its B2B arm, Powered by Tiny, which sells tests through healthcare providers and other companies, grew fourfold last year. Sew Hoy did not disclose revenue figures or the company’s valuation, though she said the valuation was “much higher” than in the Series A.

From baby gut tests to adult testing

Tiny Health spent two years developing its platform before launching an at-home baby gut test in 2022. Healthcare was new territory for Sew Hoy, whose previous startup, digital coupon company , was sold to in 2013. Before raising a seed round, she put $50,000 of her own money into an initial study and spent about a year collecting stool samples and building the platform.

The baby test gave Tiny Health a focused entry point. In Sew Hoy’s view, parents of children with conditions such as eczema wanted more information as to the cause, while clinicians had few practical tools to apply emerging microbiome research. The company also offered pregnancy, vaginal microbiome and adult tests, but initially focused on infant testing. Adults have since become its larger testing segment, according to Sew Hoy.

So, how does it work? Customers collect a small stool sample with a swab. After sending in the swab, they receive a report on the microbes detected, along with explanations and suggested next steps. Tiny Health also sells a subscription called Tiny Plus that includes a baseline test and a retest.

Sew Hoy believes one of Tiny Health’s biggest differentiators is that its tests use shotgun metagenomic sequencing to analyze microbial DNA. The method provides a broader view of the organisms in a sample than tests that look for a limited set of microbes, she said. Chief science officer , who joined Tiny Health in 2021, leads its scientific work. The company’s other leaders include co-founder , who joined Sew Hoy two years after she started Tiny Health and leads its technology work, and chief medical officer , an integrative pediatrician who previously advised the company.

The reports examine what the detected microbes may be doing and suggest steps such as dietary changes, with links to supporting research.

“We are a wellness test,” Sew Hoy said. “We’re not a diagnostic … It’s very actionable, very evidence-backed.”

Insurance does not cover the tests, which can identify microbes in a sample, but cannot establish what caused a person’s symptoms.

Other startups are taking different approaches to digestive health. Austin-based makes a device that attaches to a toilet and tracks stool patterns and hydration. Tiny Health analyzes microbial DNA from a collected sample. Throne recently raised $10 million in a Series A round led by .

Beyond direct-to-consumer testing

Tiny Health’s fastest-growing business is Powered by Tiny, which sells testing through healthcare providers and companies that incorporate it into their own services. Partners include , and ’s Executive Health and Longevity Programs, according to Tiny Health. It also works with supplement makers and academic partners that want to measure the microbiome in clinical studies.

Customers began taking their direct-to-consumer results to doctors, according to Sew Hoy. Some clinicians then approached Tiny Health for help interpreting the reports. Today, the startup serves more than 6,000 practitioners and offers training on using its tests in patient care.

Its enterprise business supplies testing to other health and wellness companies, including through technology integrations. As mentioned earlier, that B2B arm is growing fourfold. Expanding both, along with clinician training, is a priority for the new funding.

, senior principal at B Capital, told ������Ƶ News that his firm sees an opportunity to make microbiome research more useful to consumers as interest in preventive health grows.

“We’re in the middle of a real shift in how people engage with their own health. Consumers are paying out of pocket for wearables, blood panels, and full-body scans because they want to understand what’s happening inside their bodies before something goes wrong,” he wrote via email. “The gut microbiome is one of the most important and least understood pieces of that picture … Tiny Health turns that science into something people can actually act on, and we believe the company that does this well will define the category.”

Whitehead also cited Tiny Health’s standing with clinicians the firm consulted during its diligence.

“Tiny Health was consistently the test they rated highest,” he said.

Another attractive feature, Whitehead added, is the company’s data from families tested beginning in infancy.

Putting its data to work

Tiny Health has collected nearly 200,000 microbiome samples over time, according to Sew Hoy. To make use of those samples, the startup is developing a tool called TinyAI that will draw on its data and research reviewed by its scientific staff to help people understand their results. The company also uses health information customers provide, with identifying details removed, to inform that work.

Long-term, Tiny Health aims to identify patterns that could help spot health risks before a condition develops. has associated gut microbiome imbalances with more than 100 diseases.

“We want to be able to predict disease before it happens and intervene before it happens,” Sew Hoy said in an interview with ������Ƶ News.

Indeed, one pressing question is whether microbiome-guided interventions can improve health outcomes. Tiny Health says it has published four scientific papers, including a study involving infants, and plans to support further research involving adults.

Presently, the company has about 40 employees and plans to hire 30 more. It will use the new capital to expand its work with healthcare providers and other companies, and to fund research into whether changes in the microbiome can improve health outcomes. It plans to devote $5 million to a program that will give researchers and clinical partners access to its testing and data.

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