The company brings together two founders who previously built businesses that help patients get treatment outside a traditional doctorā€™s office. co-founded, which supports practices offering ketamine-assisted psychotherapy, and co-founded , which provides birth control and other healthcare services online.

led the financing for New York-based Siggy. Notably, several investors in the round previously backed one or both founders. They include of, co-founder, and co-founder, through. Other participants include, and.

The founders said they began building Siggy in late 2025. The round, which they plan to use to hire more clinicians and engineers, develop the software and work on regulatory requirements,

is the first outside funding for the company. The startup recently began accepting paying patients ahead of its public launch, and the founders said they next plan to test the service with paying patients before expanding further.

Between appointments

Sabbagh, Siggyā€™s CEO, told °µĶų³Ō¹Ļ News in an interview that the company is addressing a problem he encountered in mental healthcare. Therapists and the clinicians prescribing their patientsā€™ medication often work separately. Patients may see a therapist weekly but have only a brief appointment every few months with their prescriber. This leaves little time or opportunity to discuss changes in symptoms or medication side effects.

To address that problem, Siggy uses AI conversations and daily check-ins to gather information clinicians can review between visits.

ā€œAI helps maintain the conversation and organize what patients share, so clinicians have a richer picture of the person that theyā€™re treating,ā€ said EngesƦth, the startupā€™s COO, in an interview.

Patients begin by answering questions about their history through a free AI conversation. They then meet a licensed clinician by video, who reviews that information. The clinician then makes a diagnosis and prescribes medication if appropriate.

Patients can talk with Siggyā€™s AI between appointments and can also check in each day to report their sleep, mood, medication and how they feel physically. The company combines those answers with data from connected wearable devices to produce a daily ā€œSiggy Scoreā€ out of 100. The score is visible to both the patient and clinician.

Patients can opt to connect wearables such as , or Watch, adding sleep, activity, heart rate and heart rate variability data to the daily check-ins that underpin the Siggy Score. The company aims to use those patterns to flag difficult stretches earlier, including when patients report feeling fine despite worsening sleep or other physical changes.

If the score changes, the software flags it for a clinician to review. Patients also receive weekly check-ins during their first eight weeks of treatment, according to the company.

Clinicians decide whether to continue treatment or adjust medication, and also handle all medical questions. When appropriate, they can help patients taper off gradually. Siggy does not prescribe controlled substances and is not a crisis service, the founders said.

One important note: Patients can continue seeing their existing therapists while using Siggy, Sabbagh said. A planned feature would let patients share information with other providers and involve loved ones in their care.

A prior working relationship

As with many startup founders, Sabbaghā€™s interest in mental health treatment grew out of his own experience. After two decades in finance, he experienced burnout and was eventually diagnosed with PTSD related to childhood trauma. He said ketamine-assisted therapy helped him recover, leading him to return to school to study psychology at 38.

He subsequently co-founded Journey Clinical. Sabbagh said he has since become its executive chairman, remaining involved while taking on the CEO role at Siggy.

EngesƦth, a physician by training, was an early investor in Journey and advised Sabbagh as he built the company.

Before that, EngesƦth co-founded Nurx, which initially helped patients obtain birth control prescriptions and receive medication at home. He said the company grew to more than 2 million patients and an annual revenue run rate exceeding $100 million before merging with in 2022.

The two had considered starting a company together for years. With Siggy, they say they want to make the regular contact and coordination Sabbagh had with his own providers available to more patients.

Accepting insurance

Siggy accepts commercial insurance in all 50 states and is expanding into government insurance programs. Patients can also pay directly; insured patientsā€™ costs vary by plan.

Insurance was a priority because many prospective patients cannot afford treatment out of pocket, EngesƦth said. The founders also say Siggyā€™s service will be permanently free to veterans.

Investor POV

, a general partner at Village Global, told °µĶų³Ō¹Ļ News via email that the foundersā€™ experience building healthcare companies was a major reason he invested.

The fact that Siggy accepts insurance was important too. ā€œPairing that vision with an insurance-based model makes the ambition about access as much as technology,ā€ he said.

Mercury co-founder and CEO Immad Akhund, who invested personally, is a repeat backer of both founders.Ģż He pointed to their longer-term ambition of using AI to understand each patientā€™s brain health well enough to detect changes early.

ā€œThatā€™s why Iā€™m backing them again with Siggy,ā€ he added, ā€œand why Iā€™m excited to be in early on what they build next.ā€

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Founded by former engineers, Sunnyvale, California-based Tigris is building a network of localized data storage centers that it claims can meet the distributed compute needs of modern AI workloads.

Tigris has raised about $31.9 million since its founding in 2021, . Its October 2025 Series A brought in $25 million from lead investor, with participation from and , which also led its seed round. Other earlier backers include.

Co-founder and CEO told at the time of its Series A that the startup had grown 8x every year since its founding in November 2021.

The planned deal would give Dropbox a storage platform built for developers whose applications run across multiple cloud providers.

A push into AI infrastructure

The acquisition news coincides with what San Francisco-based Dropbox describes as ā€œa significant shiftā€ in its AI strategy as it expands beyond storing and sharing files into selling the infrastructure that companies use to build AI applications.

Publicly traded Dropbox also unveiled DBX Agent Cloud, which will initially offer standalone object storage ā€”Ģż a way to store and retrieve large collections of data, including images, video and the files used to train and run AI models.

For Dropbox, buying Tigris offers a faster route into a market that serves a different audience from the individuals and businesses that use its file-sharing software.

ā€œTigris brings together a product already running in production, an experienced team, and established relationships with AI developers,ā€ , Dropboxā€™s chief business officer, told °µĶų³Ō¹Ļ News via email. ā€œThat combination would accelerate our entry into infrastructure for AI applications through DBX Agent Cloud.ā€

A bigger bet amid a slower deal pace

Dropbox has made 35 known acquisitions, according to °µĶų³Ō¹Ļ, with much of that activity taking place in its earlier years. Between 2012 and 2015, the company conducted 23 publicly reported acquisitions, including nine in 2014 alone. In contrast, it made four acquisitions across 2024 and 2025, averaging two per year, roughly 65% below its earlier pace.

Its recent purchases suggest a focus on AI-powered productivity, search and security. Dropbox acquired scheduling startup and document security company in 2024, followed by and in 2025.

While the planned Tigris purchase would be its largest yet, Dropbox has made other sizable purchases over time. Its acquisitions of e-signature company in 2019, document-sharing platform in 2021 and business forms provider in 2022 had purchase prices of $230 million, $165 million and $95 million, respectively.

Two paths into AI

Dropboxā€™s push into AI infrastructure is one part of a broader strategy that also includes adding AI capabilities to its existing file-sharing product.

For existing customers, the company is bringing AI directly to their Dropbox files to help them find, understand, create, edit and organize content, according to Webster. Customers can switch between supported AI models and work with their Dropbox files in tools like ChatGPT and Claude, with results returning to Dropbox.

For companies and developers, meanwhile, DBX Agent Cloud extends Dropboxā€™s storage capabilities to the infrastructure behind AI applications and agents.

ā€œDBX Agent Cloud opens a new developer and infrastructure market for Dropbox, while AI inside Dropbox is intended to deepen engagement, retention and expansion among existing customers,ā€ Webster said.

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Companies spanning construction and robotics have raised about $1.6 billion this year through Oct. 29 ā€”Ģżmore than 4x the $389 million recorded in all of 2025 ā€” according to °µĶų³Ō¹Ļ data. The surge was driven by three companies that raised the majority of the funding.

The broad trend: For contractors struggling to hire, the appeal of construction-oriented tech offerings is straightforward: They need to get work done and there arenā€™t enough skilled workers to do it. The AI-driven data center building boom is only adding to that competition for workers. Labor shortages remain the biggest cause of project delays, according to by the and .

Some of the technology is already at work on job sites.

San Francisco-based , this yearā€™s largest funding recipient in the sector, said in August that excavators equipped with its autonomous systems were operating without human operators on commercial projects in Texas and Nevada.

The numbers: With roughly two months left in the year, funding has already surpassed the previous five years combined.

Companies spanning construction and robotics raised about $1.6 billion through Oct. 29, 3x the previous high of $506 million in 2021, according to our dataset that goes back to 2018. This yearā€™s total is also more than 3x the 2021 high of $506 million.

So far, the funding surge reflects much bigger bets rather than more deals. The sector has recorded 30 rounds this year, compared with 28 in all of 2025. Bedrock alone accounts for $870 million across two deals ā€” more than half of this yearā€™s total. This underscores just how much a few large financings are impacting the recovery.

Austin-based , which builds homes using 3D printing, also raised two rounds in 2026. It has raised nearly $800 million since its 2017 inception. A company spokesperson told °µĶų³Ō¹Ļ News that the company has taken its technology from an experiment to ā€œan in-the-field system that can build faster, with fewer people, less waste, greater design freedom and lower cost.ā€

To date, the company has built more than 270 homes and structures across five states and two countries. It says that itā€™s on pace to grow revenue by 4x this year.

ā€œEarly on, the question was whether a robotic construction system could build a good home,ā€ the spokesperson wrote via email. ā€œToday, the question is whether a company can deliver at volume, across geographies and project types, and improve its economics with each build. Thatā€™s only answerable with time in the field.ā€

Notable deals

Bedrock Robotics was the largest funding recipient in 2026, impressively raising $870 million across two rounds. The 2-year-old company, which converts existing heavy construction equipment into autonomous machines, announced a $600 million Series C in October led by and. That round, which valued Bedrock at $4.1 billion, followed a $270 million Series B in February led by CapitalG and.

Austin-based construction technology company Icon also raised two rounds, bringing its listed 2026 funding to $265 million. Its largest financing was a $200 million Series D in October led by and, following a $65 million Series C in March.

Another $200 million round went to, based in Zurich, Switzerland, which develops technology to retrofit construction machinery for autonomous earthmoving and excavation. led the companyā€™s Series A in August, which valued the startup at $1 billion post-money.

Beyond those large financings, investors backed companies automating homebuilding and specific construction tasks.

• , based in Andover, Massachusetts, uses AI, robotics and automation to build homes. It raised $40 million in an August venture round led by.
• Amsterdam, Netherlands-based, developer of robots for on-site masonry and other building workflows, secured a $32 million Series B in July led by.
• Meanwhile Las Vegas-based raised a $30 million Series B in May led by. Its autonomous systems serve construction, exhibitions, industrial fit-out and facility operations.
• Belmont, California-based, which develops AI-powered robotic systems for infrastructure construction, followed with a $26 million Series A in July led by.

Sizable seed rounds also made the list.

London-based, which uses AI and robotics to design, manufacture and assemble buildings, raised $25 million in April led by., based in San Francisco, developing a general-purpose construction robot, secured $20 million in October, led by and.

Exits

Acquisitions have dominated exit activity in construction robotics and related jobsite automation this year.

One of the largest disclosed deals was Carpinteria, California-basedā€™s acquisition of, a San Francisco-based platform that combines imagery from drones, ground robots and cameras to track construction progress and site conditions. Procore announced the approximately and closed it in September.

Other buyers have focused on automating the work itself. In January, subsidiary developed by, a San Francisco-based startup known for robotic drywall finishing.

Heavy-equipment autonomy also attracted buyers. In March, of Palo Alto, California-based , whose technology lets operators remotely oversee heavy machinery.

The following month, San Francisco-based confirmed that, ā€™s physical AI company, had completed its acquisition for an undisclosed price. Prontoā€™s autonomous haulage technology now reportedly underpins Atomsā€™ mining division.

Public offerings have been less prominent, with no known IPOs this year by companies focused specifically on construction robotics. The broader construction technology market did produce a sizable debut: Columbia, Missouri-based, an equipment rental and connected-jobsite technology company, raised approximately $747 million in gross proceeds in its January IPO, selling 30.5 million shares at $24.50 each.

For all the variety in the companies attracting funding, this yearā€™s surge has so far largely rested on three: Bedrock, Icon and Gravis, which together accounted for more than $1.3 billion, or about 83%, of the roughly $1.6 billion raised. Investors are placing unusually large bets on a small group of companies, even as acquisitions give others a route into larger businesses already serving construction customers.

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Startups in the travel tech space have raised $2.2 billion this year through the third quarter, according to °µĶų³Ō¹Ļ data. The largest funding recipients span a wide range of categories including hotel management software, travel booking platforms, alternative accommodations and corporate events. The mix also includes electric aviation, travel finance and insurance, and consumer hospitality businesses, reflecting a broad definition of travel tech.

The broad trend: Investors are making far fewer bets on travel startups than immediately before and after the COVID-19 pandemic, °µĶų³Ō¹Ļ data shows. This year could be the lowest since at least 2018 when it comes to dollars raised and deal count.

AI is a recurring theme among the largest funding recipients, with many using it to perform functions such as automating hospitality operations, personalizing bookings and streamlining travel planning.

The numbers: In the first three quarters of 2026, startups in the travel tech space have raised $2.2 billion globally across just 302 funding rounds, °µĶų³Ō¹Ļ data shows. Thatā€™s down fairly significantly so far from the $3.7 billion raised in 2025. Deal volume is on track to fall for a third consecutive year ā€” pointing to a market where investors are putting more money into fewer companies.

Funding and deal volume in recent years remain far below past levels. In 2021, for example, funding in the sector topped $12 billion. Thatā€™s a bit surprising considering that so much travel was halted in the midst of the COVID-19 pandemic. But even prior to the pandemic, funding and deal totals were much higher ā€” totaling $9.4 billion across 1,277 deals in 2018 and $10.4 billion across 1,190 transactions in 2019.

Even travel industry researcher noted the funding downturn in a recent newsletter, saying: ā€œThough it’s too early to say whether this is a long-term market movement, it’s a clear sign of the times.ā€

Notable deals

Interestingly, several of the yearā€™s largest deals involved startups headquartered outside of the United States.

The yearā€™s largest funding recipient through the third quarter was, which raised a $300 million Series D in January led by, with participation from,,, and. The Amsterdam-based hospitality software company helps hotels manage reservations, payments and operations, and says it plans to expand its use of AI agents to automate workflows. The financing valued the company at $2.5 billion.

Chinese electric aircraft developer raised about $144 million in February in a financing led by , joined by, and other investors. Chengdu-based Aerofugia, also backed by automaker, develops electric passenger aircraft that take off and land vertically, often called flying taxis.

Montreal-based secured a from in February. The startup uses AI to help publishers, creators and event organizers turn their audiencesā€™ interest in travel into bookings and affiliate revenue.

Home-swapping platform announced an led by in February. The San Francisco-based startup operates a members-only network where travelers exchange stays in one anotherā€™s homes. Its announcement also included a $40 million Series B co-led by and CEO , bringing the combined funding disclosed that day to $125 million.

Another large deal went to Paris-based, which announced a in February led by with participation from, and . The company uses AI to help businesses source venues, organize corporate events and manage related purchasing and payments.

Exits

Several travel startups have found buyers in 2026, including companies developing AI tools for planning and booking trips. acquired corporate travel AI assistant in February, while acquired AI trip-planning startup in July. Both deals illustrate a trend of established travel companies buying startups to expand their AI capabilities.

Expedia also completed its acquisition of venture-backed , a booking platform for museums, attractions and experiences, in February.

On the IPO side, a potentially prominent prospective exit fell through. Travel experiences platform withdrew its planned U.S. offering in October after having filed last November.

Still, the downturn in startup funding and dearth of IPOs in the sector hasnā€™t affected one of the bigger now-public players in the space. Corporate travel booking and expense management platform has seen its stock rise nearly 60% this year. Formerly called TripActions, it began trading on under NAVN in October 2025. Its stock closed at $27 on Oct. 28, up about 58% this year from its Dec. 31 closing price of $17.08. It was also 8% above its $25 IPO price, meaning much of this yearā€™s gain recovered from losses following the listing.

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The McLean, Virginia-based company verifies businesses and links their identities to the phone numbers they use to contact customers. It shares that information with the systems carriers use to screen calls and works to remove incorrect labels.

The financing brings Numeracleā€™s total funding to $34.8 million since its 2018 inception. That total includes a $6.8 million Series A raised in December 2023, founder and CEO told °µĶų³Ō¹Ļ News in an interview. Edison was the sole investor in the new round. Numeracle declined to disclose its valuation.

The company says it has roughly 4,000 business customers and about 85 employees. It became profitable this year, sooner than Johnson had expected.

Numeracle plans to use its new capital to hire and expand internationally. The company also plans to adapt its business verification tools for use beyond phone calls. For example, Johnson said the company is eyeing messaging, chat apps, marketplaces and AI agents.

Its expansion comes as businesses simultaneously face two related problems. For one,Ģż fraudsters are increasingly impersonating them. Meanwhile, call-screening systems can prevent their own calls from reaching customers.

For example, that could mean a patient ignoring a call from a hospital about an upcoming procedure. For a bank, it could mean a customer declining a legitimate call because the phone displays a fraud warning.

Numeracle charges an annual subscription to monitor and address incorrect spam labels. Customers can also pay a per-call fee to display their business name, logo and reason for calling on a recipientā€™s phone.

From a regulatory warning to a company

Johnson, an engineer who previously worked in regulatory compliance at telecom provider , said she recognized the problem while participating in the ā€™s Robocall Strike Force in 2016.

She warned carriers that their efforts to identify unwanted calls would also affect legitimate businesses because the screening systems lacked information about who was calling.

About three months later, she said, a carrierā€™s federal regulatory counsel called her while she was in her parentsā€™ kitchen.

ā€œEverything you said was going to happen is happening. What do we do?ā€ she recalled him asking.

Johnson said that conversation prompted her to start Numeracle.

She was a newly single mother who had lost her job and used her life savings to start the business. Living on a farm in Grand Bay, Alabama, without internet access, she worked from cafes.

ā€œWhen you need to feed your children and provide a roof over their head, youā€™re going to count every penny,ā€ Johnson said.

That experience shaped her spending decisions as Numeracle grew, she said. The company operated for several years before raising its Series A.

Johnson said about 90% of Numeracleā€™s sales inquiries come through unpaid inbound channels. With the new funding, she plans to spend more on marketing to specific industries, including healthcare.

The companyā€™s customers also include businesses in financial services, home services and higher education, as well as government organizations and charities. Johnson declined to identify individual customers.

Verifying increasingly convincing fakes

Numeracle first checks that a business is real and does what it claims. Once it passes those checks, the company links it to the phone numbers it uses and shares that information with the systems carriers use to flag or block calls.

Other companies can also pay Numeracle to run those checks on businesses theyā€™re considering taking on as customers.

Johnson said Numeracle built its own verification tools because existing services werenā€™t thorough enough. Fraudsters have an incentive to get through: If Numeracle approves them, their calls are less likely to be flagged as spam.

AI has made it more difficult to tell which businesses are real, she said. Numeracle has encountered fake companies with state registrations, employer identification numbers and supposed employees who have active profiles.

ā€œThe scary part for me isnā€™t necessarily the AI voices,ā€ Johnson said. ā€œItā€™s actually AI-built businesses.ā€

She said Numeracle uses AI to help identify those fabrications, though she declined to describe the methods in detail.

Numeracle currently operates in the United States. Johnson said interest from Europe has prompted it to move forward with its international expansion plans, with some of the new funding going toward that effort.

The broader question for the company is whether businesses will pay to use its verification services across other forms of communication. For now, its business centers on a more immediate problem ā€” helping customers recognize a legitimate phone call.

Investor POV: ā€˜Doing more with lessā€™

For , a general partner at Edison Partners, Johnsonā€™s telecom and engineering experience was one major reason to invest. In an interview with °µĶų³Ō¹Ļ News, he said her industry knowledge helped her build both the product and relationships with companies that could bring it to customers.

He was also drawn to how much Numeracle had accomplished with relatively little funding, describing Johnson as ā€œsomeone who was frankly doing more with less.ā€

Customer interviews helped make the case. Marcus recalled one contact center operator who said Numeracle had increased the number of calls answered from 19,000 to 22,000 out of 40,000 calls a month. For businesses trying to reach prospective customers, that increase in conversations could lead to more sales.

Marcus also believes that Johnsonā€™s years in telecom give Numeracle an advantage over newer competitors. In addition to understanding how the different parts of the industry work together, Johnson has used those relationships to get Numeracle in front of large companies, he said.

ā€œSheā€™s sales. Sheā€™s engineering, and sheā€™s just a very, very good leader,ā€ Marcus added.

Looking ahead, the investor also sees demand across healthcare, retail, home services and finance, with AI making impersonation more prevalent.

ā€œThis is a communications problem, not one for one industry,ā€ he said.

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was 16 and had been repeatedly hospitalized for Gravesā€™ disease when her mother suggested they move to China and become monks. Frustrated with the care her daughter was receiving through Medicaid, she wanted to try something different.

Chen left high school and spent about two years as a monk, ordained in the United States before spending several months at a monastery in China. She meditated, reread the same books, and gradually felt well enough to consider returning to school.

She went on to enter without a high school diploma, briefly play video games professionally, and become an engineer at . When she quit that job, she didnā€™t have a startup idea. She just wanted to find work she believed in.

That mission eventually led her to ,ā€ a Philadelphia-based company thatā€™s building software for some of the governmentā€™s least glamorous tasks, including administering school food services and managing public records.

After her brief stint at a large tech company, Chen realized she wanted to tackle the everyday problems that make peopleā€™s lives harder, even if solving them wouldnā€™t generate much excitement in Silicon Valley.

ā€œWhat does it actually take to solve the really unsexy, boring stuff?ā€ she remembers asking herself.

A different route to college

Before Chen was thinking about government software, she was trying to get well enough to return to school.

At the monastery in China, she meditated, ate food grown on-site or brought by nearby villagers, and lived without internet access. She continued taking thyroid medication and said her health became more manageable during that period.

She also read. A lot. With no nearby place to buy books, she reread the ones she had brought, finding different places around the monastery to sit with them.

Her attachment to those books prompted a conversation with a fellow monk who asked what she enjoyed about reading and where she might find more books. The discussion eventually turned to colleges, and why she wasnā€™t attending one.

Chen explained her health problems. He observed that she seemed well. She realized she was.

So Chen returned to the U.S., homeschooled herself and enrolled at Colorado College without having earned a high school diploma. She turned 20 during her freshman year and graduated in 2019 with a double major in mathematics and economics.

While she was in college, Chen briefly played Dota 2 professionally. She also played against ā€™s game-playing bots, an early encounter with AI technology she would later help support as an engineer.

After an initial job in Boston, she joined Facebook, where she built infrastructure used to train AI models.

Leaving without a startup idea

Then on Jan. 6, 2021, Chen was attending a remote company all-hands meeting while watching coverage of the attack on the U.S. Capitol on another screen. Her concerns about Facebookā€™s role in enabling the organization of violence made her question whether she could continue working there.

ā€œI realized that I couldnā€™t work for Big Tech anymore,ā€ she recalls.

She quit shortly afterward.

To figure out her next move, she returned to the sort of questions she had encountered as a monk. What made her happy? What mattered to her? What was she good at?

Programming remained her most concrete skill. She just needed to figure out where to apply it.

An introduction through , a student-run accelerator focused on nontraditional founders, connected her with , a venture firm that has backed the likes of and . The firm wrote Chen her first check in 2021, before she had even settled on the business that would become FSH.

Although she didnā€™t have a developed company pitch, Chenā€™s earnest explanation of what motivated her and her passion for solving a meaningful problem won investors over. That investment gave her room to experiment, she said.

FSH took shape into what it is today in 2024. The Contrary investor who first backed her, , has since joined the company as its chief operating officer.

The company has raised $25 million in total funding, including a recent $20 million Series A that Chen said came together in about a week. Participants in that raise included , , Ramp, , , . Contrary also led its seed financing.

Finding the problem beneath the paperwork

Ultimately, Chen landed on government software because in her view, it had the potential to solve many consequential problems that attracted relatively little excitement.

For example, permits, licenses, grant applications and other administrative processes can be slow for reasons that extend beyond an outdated interface, Chen noted. Information may exist in separate departments. Updating a website may require approvals from multiple stakeholders including policymakers, communications staff and an IT team.

Putting a chatbot on top of that system, Chen argues, leaves much of the underlying problem unresolved.

Her approach to solving some of the problems that exist within governments draws on an exchange she had years earlier at the monastery, where one of her chores was feeding koi.

The head monk would periodically ask her if she thought she was the fish or the pond?

Initially, Chen didnā€™t understand what he was asking. But he kept returning to the question, and she began thinking about it. Eventually, she picked a fish she thought resembled her: one that stayed out of fights, swam with the group and occasionally ventured off on its own.

The head monkā€™s response was, ā€œYouā€™re the pond, not the fish.ā€

Chen viewed the exchange as a lesson in looking beyond individual pieces to understand how a whole system works. Looking at government software, she believed that it meant examining why information is scattered or processes are slow before deciding what technology to build.

One early area for FSH has been K-12 food services, where administrators must perform tasks such as coordinating meal planning, nutritional information and reimbursement requirements. Another is records and archive management, including the paper documents that can still require residents to visit a government office to retrieve them.

FSH does use AI for tasks such as optical character recognition, translation and natural-language search. But, Chen said, the company treats it as a tool within its software, rather than relying on a chatbot or an AI agent to handle an entire process.

Government sales have required patience. The company generated less than $100,000 in revenue in its first year, Chen said, reflecting the time it takes to win contracts. At the time of this interview, FSH had roughly eight or nine employees, with additional offers outstanding.

Thinking slowly, moving quickly

Chenā€™s time as a monk has also influenced how she runs the company.

She admits she is skeptical of startup culture that treats sleeping in the office or working extremely long hours as evidence of commitment or a badge of pride. Rather, Chen views some of that behavior as performative, especially when it comes at the expense of the rest that she believes people need to work effectively.

Her preferred motto to the team is, ā€œSlow is smooth and smooth is fast.ā€

ā€œWe think slowly about a lot of things, and then we do things quickly,ā€ she said.

Chen believes itā€™s crucial to first understand the people, departments and procedures behind a government service before trying to improve it.

Looking back, Chen also credits her success to finding people willing to back someone whose experience didnā€™t resemble the usual rĆ©sumĆ©. That includes the college that admitted her without a high school diploma and an investor who wrote a check before she had settled on a company idea.

ā€œYou definitely end up finding your own way if you just stick to being weird,ā€ she said.

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and co-led the round, with participation from insurance industry veterans including , who will join Slingshotā€™s board. Rally is also a co-founder of the Minneapolis-based startup, as part of the firmā€™s broader approach. So far, it has co-founded roughly eight portfolio companies that have either launched or remain in stealth.

Slingshot, which is led by first-time founder and CEO , focuses on small insurance policies that consumers can buy as part of another purchase, such as coverage when booking a flight. Known as embedded insurance, the model puts coverage in front of customers when they might need it.

The startupā€™s software helps businesses offer those policies by connecting them with insurers that back the coverage. It uses AI to process and share data between the two sides, aiming to reduce the administrative work that can make inexpensive policies costly to offer.

Its first customer and design partner is , which serves more than 750,000 customers at an average premium of $25, according to Slingshot. Genteman told °µĶų³Ō¹Ļ News that Slingshotā€™s first program will launch this month.

For now, Slingshot earns revenue as a technology provider working with outside insurers. But the six-person company, which formally began operating July 1, is also pursuing an acquisition that would allow it to back policies itself.

ā€œWe’re not a carrier yet, but we are rapidly closing on our carrier,ā€ Genteman said in an interview.

Making the math work on a $25 policy

One product Slingshot is working on would let parents buy insurance when signing a child up for youth sports, Genteman said. A parent spending $2,000 on a volleyball league, for example, might be offered a $25 policy covering cancellation or an injury during the season.

Each policy includes paperwork and coordination with an insurer, and can bring potential claims. But when policies cost so little, managing them can quickly eat into the money they bring in, noted Genteman.

He believes that as vertical SaaS companies increasingly look beyond traditional subscription fees for growth, embedded insurance is ā€œa largely untapped opportunityā€ to generate incremental revenue from transactions already happening on their platforms while delivering additional value to customers.

ā€œThe challenge is that the insurance and regulatory landscape is incredibly complex, and most SaaS companies don’t have the expertise, industry relationships or understanding of where to begin,ā€ he said.

Slingshot aims to solve this by providing a white-glove service for those vertical SaaS companies, helping them go from an insurance product idea to ā€œa fully operational offering.ā€

He offered a hypothetical example: A program collecting $500,000 in premiums with a 10% margin would have just $50,000 in margin.

ā€œThat’s not a viable program for the way incumbent carriers have set themselves up operationally,ā€ he said.

Slingshotā€™s goal is to replace the spreadsheets, emails and disconnected systems used to manage that work with software that connects policy distributors and insurers directly. The company says its AI automates data-heavy tasks while keeping a record of decisions that the businesses involved can review and check.

It charges a 5% technology fee to administer programs through its platform. Acquiring an insurer would let it provide both the software and the financial backing, according to Genteman.

A customer helped shape the business

The difficulties facing Slingshotā€™s first customer helped bring the startup together.

Rally had already helped start Vertical Insure, which uses software platforms to sell insurance to its customers. According to Genteman, that business had opportunities to introduce more products but struggled to find insurers whose technology and processes could keep up.

ā€œWe can design the products our customers need almost overnight, but the industry is highly regulated, and we need delegated authority just to write and distribute what weā€™ve built,ā€ Vertical Insure co-founder and CEO said in a statement. ā€œThe antiquated approval process on the carrier-side slows everything down.ā€

Even after finding an insurer willing to back a product, connecting the two companiesā€™ systems could create more delays, Genteman said.

Slingshot was built to address those problems, with Vertical Insure helping shape its product as a design partner. Noland is also a Slingshot co-founder.

The opportunity in vertical SaaS

Genteman sees a broader opening among vertical SaaS companies: businesses that sell software tailored to a particular industry.

As vertical SaaS companies look for ways to grow beyond subscription fees, insurance could give them another avenue to make money from purchases customers already make through their platforms, argues Genteman. They already know their customers and what theyā€™re buying, putting them in a position to offer coverage that fits the purchase.

A babysitting platform, for example, could offer coverage to help parents pay for replacement childcare if a sitter cancels at the last minute. Software used by pet boarding facilities could offer coverage for unexpected vet bills if a pet is injured during a stay. An equipment rental platform could let customers add protection at checkout against accidental damage or theft.

Those are examples of what could be developed, Genteman said. Slingshot aims to help vertical SaaS companies take ideas like those and turn them into insurance they can sell, providing both the software and help navigating the insurance industry and its regulatory requirements.

ā€œInsurance becomes another product that can be offered naturally within the existing customer experience,ā€ he said.

For , managing director at Rally Ventures, that opportunity is familiar. Before joining Rally, he ran , where insurance sold through its software became a key revenue source.

ā€œThat experience gave me firsthand insight into the opportunity for software companies to generate revenue through embedded financial products,ā€ he wrote via email.

Kaufenberg sees similar potential across Rallyā€™s portfolio, where most companies combine AI products with financial services. He said founders increasingly want insurance partners that can help them introduce coverage quickly.

Rally co-founded Slingshot to bring insurance backing, underwriting, reporting, claims handling and distribution together in one business.

ā€œTo get the carrier, the reinsurance, the underwriting platform, the data flow engine, the reporting capabilities, the claims handling, the embedded distribution engine, and every other part of the offering from a single vendor is unheard of,ā€ Kaufenberg said.

From insurance executive to founder

Before starting Slingshot, Genteman was chief actuarial officer at publicly traded , where he also led data. He joined in 2019 and helped build its actuarial and data team as the company expanded beyond earthquake insurance into other coverage types.

That work led him to explore whether newer technology could reduce the costs of running insurance programs. About a year ago, he began coding and building prototypes in his basement. He started talking with Rally toward the end of 2025 and left Palomar on July 1 to run Slingshot.

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The partner began his career as a high school math teacher with after studying astrophysics at . He later worked in college access and Yale admissions, and earned graduate degrees in business and education from before joining Reach. As a teacher, he was an early user of , an experience he describes as ā€œgame-changing.ā€

His investment firm, Reach Capital, has also evolved. Founded in 2015 after spinning out of , the San Francisco-based firm initially focused on technology for K-12 schools and districts. Its mandate has since expanded to learning, health and work, with investments in companies including ClassDojo, , and .

In August, Reach announced its fifth fund, a $265 million vehicle that brought its assets under management to nearly $1 billion. The firm, which has backed more than 180 companies, plans to invest in approximately 50 additional teams through the new fund, targeting pre-seed, seed and Series A rounds.

°µĶų³Ō¹Ļ News spoke with Kim about how Reachā€™s education roots inform its broader strategy, what it saw in AI detection company , and why some of its best investments initially divided its own team. We also discussed how ownership stakes and secondary transactions have shaped the firmā€™s approach to returning capital.

This interview has been edited for length and clarity.

°µĶų³Ō¹Ļ News: You started your career as a high school math teacher. How did that shape your view of education technology?

Kim: I taught ninth through 12th grade, mostly Algebra I and geometry. I was very early to ClassDojo. Back then, it was a very simple classroom management tool, and it was game-changing for me. It has since evolved into a sprawling suite, but I already knew technology could move the needle.

Reach began as an education investor. How did the firmā€™s focus evolve into learning, health and work?

Kim: Reach started in 2015, and our original focus was exclusively on learning and education technology ā€” more specifically, technology sold into schools and districts.

Our founding partners were seeing the growth of devices in schools, one-to-one device ratios and broadband penetration. The belief was that you would start to see a proliferation of technology serving students, teachers and administrators and moving the needle on learning outcomes. That is what ended up playing out. Some of our early bets are now household names in edtech, such as , and ClassDojo.

Reach spun out of NewSchools Venture Fund, where three of our four founding partners had started doing for-profit seed investing before 2015. Over time, we branched out from K-12 into higher education, and then into consumer learning.

We also started getting pulled toward healthcare and work. Health and wellbeing affect a learnerā€™s readiness for the classroom, so we were being pulled toward mental health, behavioral health and developmental health. On the work side, formal learning typically ends in college, but you still need the bridge to a job. Once youā€™re on the job, you need to continue learning, especially in the current environment.

A few years ago, we officially put a stake in the ground and said we invest across learning, health and work. The common thread is that these are the most important systems underlying human development and flourishing.

So far, the breakdown has been roughly 50% learning, 25% health and 25% work.

These sectors have different buyers, regulations and business models. What did investing in education teach you that translates to healthcare and work?

Kim: Education is highly regulated, and institutional buying is complex. Many stakeholders must provide input, and decisions often require board-level approval. We were familiar with and comfortable with regulated products and complex go-to-market motions.

Selling to a university or a K-12 district, in terms of the complexity and the need to intersect with regulation and policy, is quite comparable to selling to a health system, hospital or insurance carrier.

Cartwheel is a good example of where our experience gave us an advantage. It provides mental health teletherapy, but the customer is the school district and the care setting is in schools.

While we were relatively new to behavioral health when we made that investment, we were very familiar with selling to school districts and implementing an intervention within a school setting. That gave us an advantage both in winning the investment opportunity and supporting the company afterward.

Reach talks about ā€œelevating human potential.ā€ What makes an investment fit that mandate?

Kim: We look for products and services that increase access to quality education, quality care or quality earnings, or some combination of those. We really have to see the mechanism for that happening.

Itā€™s not good enough to be pitched a SaaS or AI product and have the founders say, ā€œThis will make people more productive at work, and therefore maybe they will earn more or enjoy their jobs more.ā€ Thatā€™s plausible, but it isnā€™t a good enough theory of how the product actually increases access to quality earnings.

Several teammates, including myself, are former educators. We care about meaningful, needle-moving impact.

We address access from both the demand side and the supply side. On the demand side, we build products that create delightful, impactful experiences for consumers: , Stepfulā€™s allied healthcare training, and Replit for what its founder calls ā€œcitizen developers.ā€

On the supply side, itā€™s helping schools, health systems and companies function more efficiently and effectively. , for example, helps logistics and hospitality companies hire hourly workers better and treat them better. We think about the problem from both sides of the market.

Reach backed GPTZero, which agreed to join . Was that an investment in solving a problem created by AI?

Kim: That wasnā€™t actually our investment thesis. In my opinion, they have the best AI detector on the market. But their thesis was that AI use in education should not be banned. It shouldnā€™t be punitive or become a cat-and-mouse game between the educator and the learner.

Since all of us as professionals use AI in our jobs, students should learn how to use it responsibly and thoughtfully. It was the first AI detector company I had seen with that positioning, as opposed to helping schools, districts and universities clamp down on AI usage.

Thatā€™s why I liked it. I donā€™t see it as a problem for students to use AI for certain purposes, such as brainstorming, organizing thoughts and editing. GPTZero helps educators work with students and teach them how to use AI responsibly.

Do you see other opportunities to build companies around the problems AI creates?

Kim: Yes, most notably in AI governance and evaluations.

Going back to regulated categories, you need to make sure AI is not irresponsibly using personally identifiable information in education or healthcare. Those categories have very strict regulations, and infrastructure companies are emerging to help ensure AI products interact with that data responsibly.

I do think there are opportunities for large, successful, profitable companies to be created in response to the problems AI creates.

What does GPTZeroā€™s sale tell you about which AI products can become durable standalone companies and which belong within larger platforms?

Kim: I donā€™t know whether GPTZero is an example of either. They had been fielding acquisition offers from pretty early on. This particular opportunity arose earlier this year, and there was a compelling synergy story with Superhuman, formerly .

The founders and the board agreed that it made sense to combine the companies. But they could just as easily have remained standalone. There is another AI detection company called thatā€™s quite good and is still a standalone, venture-backed company.

Itā€™s not clear to me that this category canā€™t exist on its own. We have to be very case-by-case. We donā€™t know until we see the trajectory, financial sustainability and evolution of the market, whether it makes sense to explore a strategic acquisition or grow independently and perhaps one day become a publicly traded company.

Reach has backed more than 180 companies. What patterns have you noticed among those that exceeded expectations?

Kim: The reality of venture is that a very small share of investments yields the overwhelming majority of returns. Given the outlier nature of those successes, itā€™s hard to identify unifying principles that always predict a successful exit. If we could, we would only make those investments.

But there are a few things we think are somewhat common across our wins. One is a very smart, gritty, genuinely mission-driven founder or founding team, often with a strong personal connection to the problem.

Second is some sort of nonconsensus insight about the market. That often comes from experiencing the problem themselves, sometimes as practitioners in the industry ā€” a former educator, for example.

Third is a defensible and scalable business model.

The nonconsensus insight is funny because itā€™s what makes these companies look weird and maybe uninvestable in the beginning. Even within our team, theyā€™re often the most polarizing opportunities. You look at the votes, and a bunch of people vote no, but it gets just enough yeses to pass. Then, 10 years later, itā€™s one of our best investments.

People lose sight of this in the current environment, but the best opportunities are often the most nonconsensus. Those can be the most creative and interesting founders, and you can get in at reasonable valuations early and help them become consensus bets.

Reach says its first two funds have returned investorsā€™ capital. What produced those returns?

Kim: Weā€™re no exception to the power-law distribution in venture. Our first fund has been returned 2.2x by literally two investments. Our second fund has been returned 1.2x by one investment. These are cash distributions, by the way.

Especially in the second fund, thereā€™s still remaining value, so weā€™ll see how high that number gets. One fund-returning exit would be great; two or three would be amazing. Thatā€™s what weā€™re striving for.

How has that experience changed your approach to ownership and follow-on investing?

Kim: Weā€™ve had some great exits where, given how prominent the company is, you might be surprised that our share of the returns wasnā€™t that large. Thatā€™s purely an ownership calculation.

From our first fund to today, weā€™ve meaningfully increased our initial ownership target. We now try to get as close to 15% ownership upfront as possible.

That means writing slightly bigger checks and reserving relatively less for follow-on investments and more for the initial check. Itā€™s important for the exit math and distribution math.

What role do secondary transactions play in getting liquidity?

Weā€™ve become very proactive and conscientious about liquidity opportunities. Much of our distributions to investors come from secondary sales ā€” selling our shares in a subsequent round, before an actual exit.

Whenever thereā€™s an opportunity, we evaluate it. We consider how long weā€™ve been in the company, how much we can get out, and how much upside we think remains.

As companies stay private longer, early-stage investors are achieving liquidity much more often through secondary transactions. I like to think we were early to that trend, but itā€™s certainly mainstream now.

Sometimes, when we see enough upside, weā€™ll buy secondary shares. GPTZero was an example: After our Series A investment, we bought secondary shares, and Iā€™m really glad we did because it worked out well. For us, we sell more often, but occasionally we buy.

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All told, fintech startups raised $10.6 billion globally in the third quarter of 2026, down 28.4% from $14.9 billion in Q2 2026 and 21.4% from $13.5 billion in Q3 2025.

The pullback comes as investors draw sharper distinctions between companies attracting capital and those struggling to raise, according to partner .

ā€œThe market remains bifurcated ā€” AI vs. not and market leaders vs. not,ā€ she said.

founder similarly described capital concentrating in fewer, larger rounds, with infrastructure, payments and stablecoin rails attracting investor interest, supported by greater regulatory clarity.

Deal count drops

Notably, deal count in Q3 was the lowest in the quarters covered by our analysis, dating back to the first quarter of 2018. Just 687 fintech funding rounds were recorded globally in the third quarter, compared with 789 in the previous quarter and 995 in the same period a year earlier. That represents declines of 12.9% quarter over quarter and 31% year over year.

Investors are demanding stronger evidence of performance before writing checks, noted Green. For Series A and B rounds, ā€œevidence counts for more than narrative,ā€ she said.

In emerging categories, actual usage and momentum can matter more than revenue multiples. Elsewhere, investors want efficient growth, a credible path to profitability and stronger evidence of lasting customer demand before committing to a large Series B, Green said. More startups are also combining debt and equity to limit dilution.

Pullback in large rounds

The quarter-over-quarter funding decline was largely driven by a pullback in large rounds. Funding from rounds of at least $100 million fell 43.3%, from $9.07 billion in Q2 to $5.15 billion in Q3, accounting for approximately 93% of the overall dollar decline. Funding from rounds below $100 million declined just 5.1% sequentially.

Compared with Q3 2025, funding from rounds of at least $100 million decreased 7%, while funding from smaller rounds fell 31.4%. Large transactions remained more resilient than smaller-round funding year over year.

That divide also extends to pricing. Green said a small group of companies with clear momentum command aggressive valuations, while others face greater discipline.

Bock pointed to and as similarly sized businesses with widely different valuations, attributing Rampā€™s premium to investor enthusiasm for its AI momentum and growth trajectory.

Global mega-rounds

The United States remained the largest market for fintech funding last quarter. All told, U.S. startups attracted $5.38 billion, or 50.5% of the $10.64 billion global total in Q3.

The next-largest markets were Singapore with $1.28 billion (12.1%); Saudi Arabia with $626.6 million (5.9%); India with $452 million (4.2%); Brazil with $352 million (3.3%); and the United Kingdom with $337.8 million (3.2%). Singaporeā€™s total was heavily concentrated in ā€™s $1.2 billion round. Despite the U.S. being the largest market for fintech funding, the quarterā€™s five largest funding rounds went to companies based outside the United States, ironically.

• Ant International, a Singapore-based provider of digital payments and financial services for businesses, raised the largest round in Q3 2026, a $1.2 billion Series A at a listed $11.2 billion post-money valuation. The data does not identify a lead investor but lists and as participants.
• , a financial app provider based in Riyadh, Saudi Arabia, raised a $329.5 million Series A at a $1.85 billion post-money valuation. , and participated in the financing.
• Hong Kong-based , which provides financing to e-commerce businesses, secured a $300 million Series C led by at an estimated $1.36 billion post-money valuation.
• Jakarta, Indonesia-based , an online investing platform, raised a $270 million Series C led by at a $1.35 billion post-money valuation.
• Rounding out the top five, Riyadh-based , a digital financial services provider, raised $233 million in a Series F round led by at a $6.5 billion post-money valuation.

Late-stage fintech funding fell to $4.8 billion, down 40.4% quarter over quarter and 17.3% year over year, in Q3, per °µĶų³Ō¹Ļ data.

One startup lifts early-stage funding

Early-stage fintech funding was comparatively resilient at $4.23 billion, up 11% quarter over quarter and down just 0.6% year over year. However, Ant Internationalā€™s $1.2 billion Series A accounted for 28.4% of that total. Excluding that transaction from Q3 2026 alone, early-stage funding would have fallen 20.4% sequentially and 28.8% year over year.

Early-stage deal count also dropped, from 173 in Q2 to 165 in Q3, suggesting that the increase in funding dollars did not reflect a broad expansion in activity.

Fundraising expectations are rising as AI makes products faster to build and launch, Bock said. Early revenue carries less weight than sustained growth. While $1 million in annual recurring revenue once served as a common Series A benchmark, investors now want greater traction and stronger momentum, including revenue that has at least tripled over six months.

ā€œEfficiency still matters, but growth is back in focus,ā€ she said, adding that expectations of larger potential outcomes are pushing valuations higher.

Meanwhile, angel and seed funding totaled $1.12 billion, down 19.7% from Q2 and 35.2% from Q3 2025.

AI reshapes investor priorities

AI is primarily redirecting investment within fintech, although agents and payments are attracting some new capital, Green said. Companies without an obvious AI offering can still raise funding, but investors increasingly expect evidence that the technology improves their economics, speed or ability to reach customers.

ā€œThe product has to carry that story,ā€ she said.

Bock said the distinction between companies adding AI to existing processes and those building their products around it matters. The strongest AI products deliver substantial improvements that drive rapid adoption and customersā€™ willingness to pay.

ā€œWhen investors say a company is ā€˜AI,ā€™ they usually mean its growth rate is high, so growth has become the proxy,ā€ she said.

QEDā€™s recent investments span customer support, analytics, financial advice, banking infrastructure and fraud prevention. Bock sees a durable opportunity for startups that handle the specialized integrations and accuracy requirements financial services demands ā€” work she argues frontier AI labs are unlikely to prioritize.

Green, meanwhile, said payments initiated by AI agents have moved ā€œfrom ā€˜ifā€™ to ā€˜whenā€™ā€ in her conversations, as major networks and processors introduced protocols to support them. She is also seeing more fintech companies seek ownership of regulated infrastructure rather than rely on outside providers.

But she sees potential overfunding in stablecoin infrastructure, where many startups are pursuing the same customers, and in tools that let AI agents complete purchases for buyers, where, in her view, startup formation has outpaced transaction volume.

Green sees more opportunity in the systems that make agent-driven commerce trustworthy, including fraud prevention, identity verification, agent permissions and tools that help merchants accept those purchases.

ā€œI suspect the market is treating the rails as the moat,ā€ she said. In her view, payment infrastructure is likely to become commoditized, leaving more value with the companies that own customer relationships and earn their trust.

Bockā€™s broader thesis is that AI could reshape financial services by sharply reducing the costs of underwriting, compliance and customer service while enabling more personalized financial products. QED is particularly interested in advice and wealth management, underwriting, insurance claims, risk and compliance, and finance back-office operations, alongside stablecoins and tokenization.

ā€œThe financial services operating system will be rebuilt end-to-end,ā€ she said.

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Methodology

The data contained in this report comes directly from °µĶų³Ō¹Ļ, 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.

°µĶų³Ō¹Ļ 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 °µĶų³Ō¹Ļ long after the event was announced, foreign currency transactions are converted at the historic spot price.

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• Fintech Funding Surges 23% In H1 2026 As Investors Concentrate Their Bets On AI And Financial Infrastructure
• °µĶų³Ō¹Ļ Data: Q3 2026 Posted A Record Count Of Billion-Dollar Rounds As The Global AI Race Heats Up
• LatAm Startup Funding Jumps 26% In Q3 As VCs Begin ā€˜Rediscoveringā€™ The Region
• North Americaā€™s Startup Funding Falls In Q3 As AI Giants Eye The Public Markets

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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 itā€™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 °µĶų³Ō¹Ļ data. Notably, thatā€™s about 40.7% more than the $1.08 billion Brazilā€™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.

ā€œOver the past year, we have seen investments into Brazil from firms including , , , and ,ā€ , managing partner of , told °µĶų³Ō¹Ļ News. ā€œFor several, this marked either their first investment in Latin America or their first in a long time.ā€

, Endeavor Catalystā€™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 ²Ń±š³ę¾±³¦“Ēā€™s funding went to a few startups, he pointed out, while Brazil recorded many deals.

ā€œInvestors are concentrating on a few Mexican winners, while Brazil retains the breadth,ā€ 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 werenā€™t to fintech, which typically has the most funding recipients in the region, but rather to energy-related startups.

, the Chilean project company for ā€™s Black Giant lithium project, raised $225 million in a July round at a reported $900 million valuation. And Colombiaā€™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.

²Ń±š³ę¾±³¦“Ēā€™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, Brazilā€™s , an AI-native wealth advisory company, landed $85 million inĢż what °µĶų³Ō¹Ļ 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 Americaā€™s startups in the third quarter, about 20.5% ā€” or $266 million ā€” was raised across the angel and seed stages.

Thatā€™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 Endeavorā€™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.

ā€œI joke that investors from the U.S. ā€˜rediscoverā€™ Latin America every five or six years, and I think we are approaching another rediscovery moment,ā€ Taylor told °µĶų³Ō¹Ļ 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.

ā€œThe exit door is open, although it is not primarily opening through IPOs yet,ā€ Piquet said.

Taylor expects more exits could help bring global investors back consistently, with potential listings by companies such as , or contributing to another ā€œrediscovery momentā€ 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 2020ā€“2021 investment boom have shifted toward AI opportunities elsewhere and are concentrating on existing portfolios, she noted.

ā€œGlobal investors are increasingly investing behind themes rather than geographies,ā€ 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.

ā€œIncreasingly, weā€™re seeing founders build globally competitive technology companies from Latin America, rather than necessarily for Latin America,ā€ she said.

Gadala-Maria agrees that Brazil and Mexico remain the regionā€™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 °µĶų³Ō¹Ļ, 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.

°µĶų³Ō¹Ļ 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 °µĶų³Ō¹Ļ 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. °µĶų³Ō¹Ļ 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. °µĶų³Ō¹Ļ 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 ā€œSeries [Letter]ā€ 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 ā€œventureā€ round. (So basically, any round from the previously defined stages.)

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