led the financing, which included participation from , and angel investors from companies such as , , and .

Miravoice has developed an AI interviewer that it says can conduct phone surveys and voice interviews for 鈥減recision data collection鈥� without human interviewers. The surveys are long-form and quantitative, with some including more than 120 questions and lasting over 40 minutes. They span open-ended responses, numerical inputs, multiple choice questions, Likert scales and matrix questions.

鈥淚magine talking to 100,000 people and instantly capturing what they know,鈥� said CEO and co-founder . 鈥淲e make that as simple as creating a Google Form.鈥�

Voice interviews have long been the gold standard for rigorous data collection, but the costs and operational frictions of talking to people have made it more challenging, Jain contends.

鈥淗aving to hire call centers made running quantitative research surveys infeasible for most organizations,鈥� he said.

Miravoice claims its agent is designed to be simple for anyone to deploy and not require technical backgrounds to operate.

A user can build a questionnaire, spin up a phone number, and launch its trained voice agent 鈥渢o get results back in hours rather than weeks,鈥� Jain said.

Multiple languages and 鈥榤essy realities鈥�

Miravoice is hyper-focused on precision, according to Jain.

鈥淯nlike other voice agent companies, we focus on structured conversations in which most questions are known in advance,鈥� he explained. 鈥淥ur customers know what information they want to get ahead of time, which is why we focus on extracting as much information as possible from respondents while minimizing bias.鈥�

He said Miravoice鈥檚 agent will ask every question in a survey without hallucinating responses.

鈥淎nd when the messy realities of human conversations arise, like interruptions or pauses, our AI can handle them seamlessly,鈥� Jain said.

The Miravoice interviewer is also multilingual by design, a capability that Jain believes is difficult for individual call centers to match.

Using Miravoice鈥檚 agent is also cheaper than hiring and training call centers to conduct the same surveys, Jain contends. The platform can handle both outbound and inbound calls if a respondent calls back at any time of day.

Idea and business model

Miravoice was founded by Jain, and , three close friends from California who have known each other for more than a decade.

The idea for Miravoice came from firsthand experience with the pains of scaling quantitative survey research in their roles as product managers and consultants. They realized that voice agent technology would be the way these calls would be handled in the future, 鈥渋f agents were appropriately crafted for the unique needs of this market use case.鈥�

Miravoice has between 10 and 20 customers at varying stages 鈥� from paid pilot to production use cases 鈥� according to the company. Those customers include a variety of public-opinion survey organizations, market research firms, university departments and private companies across retail, entertainment and logistics.

Its revenue model is usage-based billing: Customers pay for the time its AI agents are actually on the phone with respondents.

Miravoice surpassed 100,000 calls made in 2025, per the company, and expects that number to be significantly higher this year.

鈥淲hat鈥檚 exciting about the space we鈥檙e operating in is that the scale of the number of calls our platform has to handle dwarfs most other voice agent use cases,鈥� Jain said. 鈥淥ur pilot projects alone are on the order of tens of thousands of calls: more than some voice agent companies鈥� monthly production workloads. In production, some of our customers expect to perform millions to tens of millions of calls each year, after full deployment and implementation.鈥�

Voice AI on the rise

, general partner at Unusual Ventures, said his firm was impressed by the founding team鈥檚 technical acumen and product vision.

In Albright鈥檚 view, Miravoice鈥檚 focus on precision data collection sets it apart from most other entrants in the voice agent market research space.

鈥淭hey鈥檝e correctly identified that voice AI can streamline operations and time-to-insight for large-scale quantitative research studies,鈥� he wrote via email.

Another area where Miravoice distinguishes itself is its ease of use, he said.

鈥淢any voice agent platforms are geared towards technical audiences and software developers,鈥� Albright said. 鈥淢iravoice was built from the ground up with simplicity in mind so that truly any team can use it. This is a step-function change in making AI voice agents for surveys as ubiquitous as web forms are today.鈥�

Indeed, voice AI startups have emerged as standouts in the vast AI space, attracting the attention of investors globally, according to 附近上门 data. Over the past two years, several voice AI companies have seen their valuations triple 鈥� a signal of accelerating market demand and perceived long-term worth.

One example of a voice AI company that has seen a massive valuation jump is , which allows creators, enterprises and others to use AI software to replicate voices in dozens of languages. The Brooklyn, New York-based startup went from achieving unicorn status with an $80 million Series B raise in January 2024 to being valued at about $3.3 billion one year later with a $180 million Series C co-led by and . Then, in February of this year, it raised a $500 million Series D round led by at an $11 billion valuation.

Related reading:

• Why Big Investors Are All Ears For Voice AI Startups
• ElevenLabs Latest AI Unicorn After $80M Raise

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The round marks a significant step-up in valuation from the $3.6 billion that Boston-based Whoop achieved in August 2021 when it raised a $200 million Series F round. In total, it has raised over $900 million since it was founded by in 2012.

led its latest financing, which included participation from a slew of institutional investors, athletes and angels, including , , , and .

Individual investors in the round include soccer star , players and , and musician .

Whoop says it is powered by more than 24 billion hours of physiological data and purpose-built AI models to provide predictive, personalized health insights. It claims to help users understand how they slept, whether they have recovered, how hard to push or pull back, and how daily behaviors like training, nutrition and stress are impacting their performance and long-term health. It further ambitiously claims that it helps users 鈥渋dentify early warning signs, reduce risk, and take action that can prevent serious health events.鈥�

Subscription-based insights

Its model is different from that of many wearables companies. The actual wearable doesn鈥檛 cost anything, but 鈥渕embers鈥� pay a subscription to access the insights it offers. There are different tiers based on style and performance level.

Whoop has historically been more popular among athletes and die-hard workout enthusiasts, although it appears to be becoming more mainstream. The company says it now has over 2.5 million members globally, and that in 2025 bookings grew 103% year over year. It听 operated cash flow positive and ended the year at a $1.1 billion run rate.

The company is actively hiring for over 600 roles as it plans to double down on R&D and global expansion across Europe, the Middle East, Latin America and Asia.

Whoop鈥檚 round is a bright spot in a sector that hit a cyclical low last year after peaking about four years ago. Just over $5 billion in global venture funding went to fitness and wellness-related startups in 2025, 附近上门 data shows.

That said, it鈥檚 not as if investors have abandoned the space, and there are clearly still companies securing big rounds.

Last year, the standout was , maker of a smart ring that collects data on dozens of personal health and wellness metrics. Last October, the 12-year-old Finnish company it had closed on more than $900 million in funding at an impressive $11 billion valuation.

Related 附近上门 queries:

Related reading:

• Venture Capitalists Tap Out On Funding Our Fitness Goals

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

It was going to be a fairly business as usual top 10 list this week until decided to disrupt our Friday with news that it raised $110 billion in new funding. Yes, $110 billion. That is so much money, and so record-setting as a private company funding round, that it makes all those other $100 million and $200 million rounds we usually write about look very paltry by comparison.

That said, we did nonetheless see a number of these kinds of rounds, in sectors including semiconductors, AI, healthcare and biotech.

1. , $110B, artificial intelligence: Generative AI giant OpenAI that it has raised $110 billion in new investment at a valuation of $730 billion pre-money, or $840 billion post-money. The deal includes $50 billion from , $30 billion from , and $30 billion from . San Francisco-based OpenAI says more investors are expected to join as the round progresses.

2. (tied) , $500M, semiconductors: MatX, a startup that designs custom chips and hardware architectures to support large language models, secured $500 million in Series B funding as it prepares to scale manufacturing. and led the financing for the Mountain View, California-based company.

2. (tied) , $500M, broadband: Boulder, Colorado-based Vero Networks, a fiber infrastructure and broadband internet provider, picked up $500 million in a growth funding round backed by , and .

4. , $240M, fusion: Janesville, Wisconsin-based Shine Technologies, a developer of fusion technologies with applications in the medicine and energy sectors, raised $240 million in equity funding led by .

5. , $150M, hardware testing tools: Revel, developer of a software platform for hardware test and control, closed on $150 million in Series B funding. led the financing for the Los Angeles-based company, which plans to expand its offerings across aerospace, defense, robotics and industrial sectors.

6. , $140M, healthcare: Nashville, Tennessee-based Honest Health, a provider of tech-enabled tools for primary care providers, secured $140 million in a new financing led by .

7. , $130M, biotech: Slate Medicines, a startup working on therapeutics for headache disorders, announced its launch alongside $130 million in Series A financing. , and led the investment for the Raleigh, North Carolina-based company.

8. , $106M, smart infrastructure: Fort Lauderdale, Florida-based Ubicquia, provider of an analytics platform for smart lighting, grid monitoring and public safety applications, raised $106 million in Series D funding. and led the financing for the 12-year-old company.

9. (tied) , $100M, AI-enabled accounting: Basis, an AI agent platform for accountants, closed on $100 million in Series B funding at a $1.15 billion valuation. led the round for the New York-based startup, along with , and .

9. (tied) , $100M, satellite and network communication: spinout Aalyria, a developer of software that configures communications satellites to meet demand, secured $100 million in Series B funding. and led the financing for the Livermore, California-based company.

9. (tied) , $100M, smart glasses: Viture, a San Francisco-based maker of extended reality (XR) smart glasses and accessories, says it $100 million in a financing led by .

Methodology

We tracked the largest announced rounds in the 附近上门 database that were raised by U.S.-based companies for the period of Feb. 21-27. Although most announced rounds are represented in the database, there could be a small time lag as some rounds are reported late in the week.

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While Europe鈥檚 venture investment did not grow significantly year over year, the region saw a shift to deep tech funding in 2025. Startup investment has also now maintained well above pre-COVID levels for the past three years.

Still, Europe notably has not seen the same AI-driven boost that North America has. Venture investment in North America-based companies last year soared 46% year over year, with mega rounds into AI-related companies leading the way.

Table of contents

• Quarterly uptick
• AI led for the first time
• UK leads but other countries gain
• Late stage grew in Q4
• Leading investors
• Above pre-COVID funding
• Methodology
• Glossary of funding terms

Quarterly uptick

European venture funding did gain steam in Q4, reaching $16.6 billion 鈥� up 20% quarter over quarter and 27% year over year 鈥� per 附近上门 data.

The largest rounds in Q4 were raised by London-based energy software provider , Finland-based smart ring , Paris-based customer engagement platform , Dutch online grocer , and London cloud GPU provider .

AI led for the first time

Last year, artificial intelligence was the leading sector for venture investment in Europe for the first time, with around $17.5 billion in funding to AI in 2025 compared to just over $10 billion in 2024.

Paris-based frontier lab raised the largest round in the year, close to $2 billion led by Dutch chip machine manufacturer . Other large European funding rounds raised last year in AI went to Nscale and Brevo as well as Munich-based defense manufacturer , London-based AI drug discovery , and Freiburg, Germany-based image frontier lab .

The second-largest sector in Europe in 2025 for startup investment was healthcare and biotech, with companies in the space raising around $13.4 billion.

The third-largest sector was hardware with around $10.8 billion invested. The total demonstrates Europe鈥檚 renewed focus on deep tech including investment in data centers, wearables, defense, quantum, aerospace, robotics and energy.

Financial services, once the leading sector in Europe鈥檚 venture scene, was only the fourth-largest sector for funding in 2025, with around $7.4 billion invested.

UK leads but other countries gain

The U.K., the leading country in Europe, raised around $17 billion. That represents about 29% of total European venture funding in 2025, down from a third of all funding in 2024.

Startups based in France raised $8.5 billion and Germany-based companies came in a close third with $8.4 billion. Each nation鈥檚 startups represented about 15% of funding to the continent last year.

Switzerland was the fourth-largest European country for venture investment in 2025, with $3.6 billion invested in its startups last year. The Netherlands was the fifth largest at $3.4 billion, and was followed by Spain ($2.9 billion) and Finland ($2.2 billion).

With the exception of the U.K., each of those countries raised more venture funding in 2025 than in 2024.

Late stage grew in Q4

Late-stage funding in Q4 reached the highest amount in two years. A total of $9.2 billion was invested across 87 deals, up 65% by amounts year over year.

Early-stage funding reached $5.3 billion in Q4 across more than 250 funding rounds, down 4% year over year.

Seed funding reached $2 billion in Q4 across more than 750 deals, inline with totals year over year.

Leading investors

Investors that led or co-led the largest fundings into the region鈥檚 startups last year were dominated by Europe-based venture and private equity firms. Firms that led or co-led from outside of Europe included a mix of venture or private equity firms from the U.S. or Asia.

Above pre-COVID funding

Funding in Europe did not grow significantly year over year in 2025, but was well above pre-COVID funding levels and growing in deep tech and AI. With a renewed focus on science, funding has also shifted toward cities across Europe with leading research institutes.

Methodology

The data contained in this report comes directly from 附近上门, and is based on reported data. Data is as of Jan. 4, 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. 附近上门 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 附近上门 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. 附近上门 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. 附近上门 includes venture rounds of unknown series, corporate venture and other rounds above $3 million, and those less than or equal to $15 million.

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

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

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CEO and CRO met a decade ago in college and began building different ventures together. After a few pivots, they raised funding for New York-based Flip in 2018 with the goal of building AI that 鈥渁nswers and automatically resolves routine requests鈥� for customers calling into a variety of businesses. They started with a focus on transportation companies and moved into retail in 2021 and healthcare in 2024.

AI-based customer service is a saturated space, but Schiff claims Flip鈥檚 approach is differentiated because it鈥檚 a vertical one that is very focused on just three industries.

Among vertical players, Schiff claims that Flip has an advantage because its AI 鈥渋s battle-tested on more than 300 million phone calls.鈥�

and co-led the round for Flip, which says it has raised a total of $31 million in funding. also participated in the round, alongside , , and a group of angel investors. Flip declined to reveal valuation, saying only that it was up 3x compared to its seed raise.

Year-over-year growth

Today, Flip has hundreds of enterprise customers, including , , and global transportation companies. The company has reached an eight-figure ARR, growing 3x year over year, according to Schiff.

Interestingly, the idea for Flip came when Schiff and Krut were students at . They had built a ride-hailing app called Red Route for calling taxis at Cornell, at a time when was still banned in upstate New York. It was during that experience they came up with the idea for what is today Flip.

鈥淐ustomer service is one of the obvious AI categories for business, and we’re talking on a daily and weekly basis with the largest brands on the planet,鈥� Schiff said. 鈥淓ven for them, it’s not a question of 鈥榠f.鈥� It’s a question of 鈥榳hen鈥� and 鈥榳ith whom.鈥欌��

That, he said, has created 鈥渁 huge amount of noise鈥� in the market.

Over the past year or so, a number of what Schiff described as 鈥済eneric AI providers鈥� popped up.

鈥淭he great irony of this space right now is that while all of the headlines and much of the funding has gone into these generic platforms that are trying to be the AI everything for everyone, across every industry, every channel, every use case. In reality, most of the actual traction, most of the successful customer stories, are working with vendors like Flip that are going very deep into one or a couple of specific industries,鈥� Schiff told 附近上门 News in an interview.

Another differentiator, in his view, is that few companies have developed deep expertise with AI telephone customer service.

鈥淢ost people are doing it inside of chatbots or auto email responders,鈥� he said. 鈥淲e really look at the quality of the experience. It doesn’t matter how nice it is to talk to 鈥� it’s still just another bot that’s in the way of a customer trying to solve their problem.鈥�

When it comes to the revenue model, Flip doesn鈥檛 charge an upfront cost or require a long-term commitment. Rather, it charges per automated call 鈥� a usage model it has implemented since its early days.

鈥楢 vertical approach yields the best results鈥�

, managing partner at , believes that customer service is one of the few huge markets where generative AI has produced tangible results for enterprise customers and a better experience for users.

鈥淏ased on our 30+ years of investing in software, we believe a vertical approach yields the best results,鈥� he wrote via email. 鈥淔lip has taken a different approach than many others by focusing on a couple of verticals and going really deep 鈥� While there are plenty of competitors making noise, some are going after different parts of the market, and Flip has quietly, up to now, launched more live customer deployments, at scale, than anyone.”

, co-founder and managing director at , said he has spent nearly two decades in and around call centers and voice technologies and has 鈥渘ever seen a more compelling ROI for customers鈥� than what Flip offers.

He added: 鈥淭he founding team is exceptional, customer feedback has been tremendous, and the potential for Flip to become a $1 billion business is clear.鈥�

Smerklo said he is also impressed with the company鈥檚 capital-efficient approach to growth.

鈥淪everal other companies that have raised tremendously more money have to rely on ‘forward engineering’ to get their product to work for customers,鈥� he said. 鈥淔lip’s solution works, doesn’t require a massive investment from customers, and solves real, salient business issues.鈥�

Related 附近上门 query:

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I鈥檝e been building products and companies my entire career 鈥� , , , and now, 鈥� and I鈥檝e had the privilege of speaking with some of the sharpest minds in venture and entrepreneurship along the way.

One recent conversation with a legendary investor really crystallized for me a set of truths about startups: what success really is, why some founders thrive while others burn out, and how to navigate the inevitable chaos of building something from nothing.

Here are some of the lessons I鈥檝e internalized from years of building, observing and learning.

Success has no finish line

In the startup world, we talk a lot about IPOs, acquisitions and valuations. But those are milestones, not destinations.

The companies that endure don鈥檛 鈥渨in鈥� and stop 鈥� they keep creating, adapting and pushing forward. They鈥檙e playing an infinite game, where the only goal is to remain in the game.

When you鈥檙e building something truly generative 鈥� driven by a purpose greater than yourself 鈥� there鈥檚 no point at which you can say 鈥渄one.鈥� If your company has a natural stopping point, you may be building the wrong thing.

You don鈥檛 choose the work 鈥� the work chooses you

The best founders I鈥檝e met 鈥� and the best moments I鈥檝e had as a founder 鈥� come from an almost irrational pull toward solving a specific problem I myself experienced.

You may want to start a company, but if you have to talk yourself into your idea, it probably won鈥檛 survive contact with reality. The founders who succeed are often the ones who can鈥檛 not work on their thing.

Starting a company shouldn鈥檛 be a career move 鈥� it should be the last possible option after every other path fails to scratch the itch.

The real killer: founder fatigue

Most companies don鈥檛 die because of one bad decision or one tough competitor. They die because the founders run out of energy.

Fatigue erodes vision, motivation and creativity. Protecting your own drive 鈥� keeping it clean and focused 鈥� may be the single most important survival skill you have.

That means staying close to the product, protecting time for customer work, and avoiding the slow drift into managing around problems instead of solving them.

Customer > competitor

It鈥檚 easy to get caught up in competitor moves, investor chatter or market gossip. But the most important question is always: Are we delivering joy to the customer?

If you鈥檙e losing focus, sign up for your own product as a brand-new user. Feel the friction. Fix it. Repeat.

At Digits, we run our own signup and core flows every week. It鈥檚 uncomfortable 鈥� it surfaces flaws we鈥檇 rather not see 鈥� but it keeps us anchored to the only metric that matters: customer delight.

Boards should ask questions, not give answers

Over the years, I鈥檝e learned the most effective boards aren鈥檛 presentation theaters 鈥� they鈥檙e discussion rooms.

The best structure I鈥檝e seen:

• No slides;
• A narrative pre-read sent in advance; and
• A deep dive into one essential question.

Good directors help you widen your perspective. They don鈥檛 hand you a to-do list. Rather, they help you see the problem in a way that makes the answer obvious.

Twitter: lessons from a phenomenon

When I think back to my time at Twitter, the most enduring lesson is that not all companies are built top-down. Some 鈥� like Twitter 鈥� are shaped more by their users than their executives.

Features like @mentions, hashtags and retweets didn鈥檛 come from a product roadmap 鈥� they came from the community.

That鈥檚 messy, but it鈥檚 also powerful. Sometimes your job isn鈥檛 to control the phenomenon, rather it鈥檚 to keep it healthy without smothering what made it magical in the first place.

Why now is a great time to start

If you鈥檙e building today, you have an advantage over the so-called 鈥渦nicorn zombies鈥� that raised massive rounds pre-AI and are now locked into defending old business models.

Fresh founders can design from scratch for the new reality; there鈥檚 no legacy to protect, no sacred cows to defend.

The macro environment? Irrelevant. The only timing that matters is when the problem calls you so strongly that not working on it feels impossible.

If there鈥檚 one takeaway from all of this, it鈥檚 that success is continuing. The real prize is the ability to keep playing, keep serving and keep creating.

If you鈥檙e standing at the edge, wondering if you should start 鈥� start. Take one step. See if it grows. And if it does, welcome to the infinite game.

听 is the founder and CEO of , the world’s first AI-native accounting platform. He previously served as ‘s head of consumer product and starred in the Emmy Award-winning documentary 鈥淭he Social Dilemma.鈥�

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The old clich茅 says startups are born in garages and dorm rooms. That鈥檚 still true, but there鈥檚 a newer path: founding a startup inside a scale-up.

When you do that, you get the speed of a seed-stage team with the leverage of an established company. Executives and investors should care because this model can unlock new product lines, revenue and talent retention without recreating the wheel.

That鈥檚 how we built , a travel eSIM service launched from inside (the company behind ). In 19 weeks, a seven-person team went from a blank page to a live product. A little over a year later, we had scaled to millions of users with plans offered in more than 200 destinations. We did not invent everything from scratch. We reused what worked and validated everything else fast.

Incubation lowers two risks most founders underestimate

Every new product faces two existential risks: market and execution.

Inside Nord, I鈥檇 helped launch at least half a dozen new products before Saily. The pattern was consistent: Great ideas die when they target the wrong market or underestimate execution. With Saily, timing and infrastructure lined up: eSIM demand was accelerating, pain points were clear, and we could tap Nord鈥檚 backend, payments, app teams and distribution.

That allowed us to move at startup speed without startup fragility.

鈥楶roduct organization fit鈥� beats a great idea

Founders obsess over product-market fit. Inside a scale-up, you also need what I call 鈥減roduct organization fit鈥� or the overlap between a new product and what your company already does well.

When that overlap is high, you ship faster, hire smarter and avoid costly relearning. For Saily, the overlap was obvious: Security tech we knew (virtual location, web protection and ad-blocking), and app development know-how we could bring to travel connectivity.

Competition helped more than it hurt. 鈥淣o competition鈥� usually means 鈥渘o demand.鈥� We treated competitors as free market research, reading hiring signals, product moves and funding announcements to understand where the market was headed.

And we made security the product, not a feature. Travelers don鈥檛 want another app 鈥� they want reliable connectivity that isn鈥檛 risky on unknown networks. Building privacy and protection at the network layer means safety works phone-wide with no tinkering.

Autonomy inside structure

The hard part is not technical, but cultural. Large companies run on process. Startups run on autonomy. We set up Saily as a company within the company: A dedicated product and marketing team with decision speed, plus shared services (legal, finance and design) when needed. Think of it as an internal accelerator, where the platform handles overheads so the team can focus on products.

We kept one rhythm: ship, learn, repeat. Those 19 weeks weren鈥檛 about perfection, but about getting a usable product into the world and compounding feedback.

Experimentation only works if you measure what matters: speed, unit economics and retention. For example, independent third-party testing confirmed Saily鈥檚 network-level ad-blocking reduces data usage by 28.6% 鈥� real money saved for travelers. That is a signal you double down on. If a feature or tool adds complexity without value, cut it quickly.

What founders (and operators) can steal

• Derisk in two tracks: Validate market pull and execution feasibility before you scale spend. If the market isn鈥檛 growing and your organization doesn鈥檛 have overlap, think twice.
• Reuse before you reinvent: Borrow talent, systems and channels where you can. Every overlap removes weeks of risk.
• Measure what matters: Do a simple before/after on ship speed, customer acquisition cost and retention. If the needle doesn鈥檛 move, remove it.
• Build momentum in full sight: Share milestones and learning. It sharpens the team and attracts partners.

Saily is still early, and the market is just getting started, but the model matters as much as the product. Many future founders already work inside growth companies. Give them startup autonomy and scale-up leverage and remarkable things can happen 鈥� in months, not years.

听 is CEO of , a global eSIM app from . A former head of product strategy at , where he helped launch a series of new product lines, Maknickas has turned Saily into a globally successful brand with millions of users and serving more than 200 destinations. An entrepreneur since age 15, Maknickas brings a hands-on, execution-driven approach to building secure, scalable consumer tech.

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To shed some light on this question, we analyzed a dataset of AI-focused startups that raised at least a few million dollars in seed- or early-stage funding this year.

While it was a varied crew, a few areas stood out as particularly popular. These include: back-office tools, robotics, drug development and healthcare automation.

Stepped-up early-stage funding to these areas comes as the most prominent generative AI startups have largely matured to later stage.

Much of the current early-stage generation of startups, by contrast, is focused less on broad, general purpose AI models and more on solving problems and automating tasks within specific industries.

Without further ado, here are the four areas that caught our eye.

No. 1: Back-office automation

Back-office automation was one of the more popular themes for AI-related seed- and early-stage investment, per 附近上门 data, and seemingly for good reason. Tasks related to accounting, payroll, compliance and other back-office functions pose a significant cost to all businesses.

But back-office burdens can be particularly daunting for smaller businesses, which lack the economies of scale of larger rivals. As such, that鈥檚 where a number of startups are focusing their endeavors.

For a sense of where funding is going, we put together a sample list of 10 companies that raised seed- or early-stage rounds this year with a back-office automation focus.

No. 2: Robotics

Anyone who鈥檚 ever performed a dull, dirty or difficult physical task has probably fantasized about having a robot take over. In recent quarters, a surge of funding to startups at the intersection of AI and robotics means that fantasy is now poised to move at least closer to reality.

Per 附近上门 data, we鈥檙e seeing a particularly strong wave of investment activity at seed and early stage. To illustrate, we put together a sample list of 14 companies funded so far this year.

No. 3: AI tools for healthcare

High on the wish list of many health providers is the ability to spend more time providing care and less on recordkeeping and compliance-related tasks. A slew of recently funded startups at the intersection of healthcare and AI are looking to assist in this goal with tools to automate some of the more tedious and repetitive tasks.

To illustrate, we used 附近上门 to assemble a representative sample list of 10 companies in this area that raised seed- or early-stage funding.

That list, however, is only a small portion of the full population of startups in the space funded this year, for which we also provide a sample .

No. 4: Drug development and medical research

The intersection of AI and biotech is also a vibrant area for seed- and early-stage funding.

So far in 2025, this has manifested most noticeably in a series of megarounds for , a Cambridge, Massachusetts, startup working on what it calls a 鈥渟cientific superintelligence platform鈥� for life sciences, chemistry and materials science.

Beyond Lila, however, a raft of other startups in AI and biotech have also raised good-sized seed- and early-stage rounds this year. Below, we aggregated a sample of 10 companies that stood out.

But wait, there鈥檚 more

While this article focused on four investment themes, there were quite a few more that stood out in our query. These included legal tech, go-to-market offerings, chip design, and innovations around AI-enabled voice and audio.

As is typical at seed and early stage, the promise of all these areas sounds quite enticing. We鈥檒l see in a few years, however, if visions of a less tedious back-office, more robot-enabled workforce, more streamlined healthcare system, and faster and more effective medical research come to fruition.

Related 附近上门 lists and queries:

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Overall, investors put $16.8 billion into reported seed- through growth-stage rounds for companies across Asia, per 附近上门 data. That鈥檚 a 20% increase from the prior quarter and a 16% rise from the year-ago period.

But while funding is up in the short-term, investment remains well below the levels typical a few years ago. In multiple quarters in 2021 and 2022, funding was more than twice current levels.

Still, sequential improvement is a positive indicator. And for Q3, it鈥檚 also encouraging that reported round counts were up along with total funding, rising by around 10% from Q2.

Table of contents

• China leads, India lags
• Singapore, Israel and other top funding destinations
• Late stage, early stage and seed
• AI Funding Rises
• Better, but still room for improvement
• Methodology
• Glossary of funding terms

China leads, India lags

Funding gains were unequally distributed among countries in the region, with some posting sharp gains and others seeing investment fall.

China: China, the region鈥檚 largest recipient of venture investment, was among those in the plus column. Funding to China鈥檚 startups hit $6.2 billion in Q3, up 13% from an unusually weak Q2. Even with those gains, however, China funding is down from a year ago and far below 2022 and 2023 levels.

The largest financing went to , a developer of commercial launch vehicles, that $337 million in a late-September financing. Two robotics-focused companies, and , also secured $140 million each.

India: India, the second-largest venture funding destination in Asia, saw investment contract in the third quarter. Per 附近上门 data, a total of $2.7 billion went to reported rounds for India-based startups in Q3, down 22% quarter over quarter and the lowest tally in two years.

Even so, there were some larger rounds in the mix. , an online pharmacy and telemedicine app, picked up $65 million in Series C funding. And , a design tech brand, closed on $50 million.

Singapore, Israel and other top funding destinations

While China and India, with roughly 60% of Asia鈥檚 population, are predictably the continent鈥檚 largest venture markets, several smaller countries also proved popular with investors.

Singapore: Startups in the Southeast Asian financial capital landed a combined $2.4 billion in Q3, nearly triple year-ago levels. The quarter included a $220 million Series C for , an eSIM provider for mobile devices enabling data connectivity for travelers.

Israel: Funding to Israeli startups was estimated at $1.4 billion in Q3 鈥� down from the prior quarter, but still up significantly from a year earlier.

, a cybersecurity platform for AI and autonomous agents, closed on the largest venture fund, a $100 million Series B. The next-biggest was a $96 million Series B for , based in Silicon Valley and Tel Aviv, focused on underground mapping.

UAE, South Korea, Japan and Saudi Arabia: For other Asian nations, fluctuation was the only consistent attribute for funding levels.

United Arab Emirates was one of the gainers, largely due to big rounds for Dubai-based companies. One standout was , a developer of connected smart contact lenses that pulled in $250 million in a July Series A.

South Korea funding also ticked up in Q3. The largest round for the quarter was a $250 million financing for AI semiconductor startup .

Saudi Arabia, meanwhile, clinched a big round with payments platform closing on $157 million for its Series B. And in Japan, overall funding was down, but we did see some jumbo-sized rounds, including a $100 million Series B for back-office automation provider .

Late stage, early stage and seed

Overall, late-stage and technology-growth deals captured the largest share of funding across Asia.

For Q3, investors put $8.3 billion into 151 reported rounds at these stages. In dollar terms, it was the highest quarterly total for the year.

Early-stage dealmaking also saw a pickup in Q3, with reported investment hitting $6.7 billion, also a quarterly high for the year.

At seed, meanwhile, it appears investment declined in Q3 based on reported totals. However, we expect these numbers to rise some over time, as deals at this stage are often recorded in the dataset weeks or months after they close.

AI funding rises

We also broke out the share of Asian funding going to AI-focused companies, given the popularity of this investment theme in recent quarters. For Q3, AI-related investment rose significantly, hitting the highest total on record.

Better, but still room for improvement

Overall, Asia startup funding tallies for the third quarter indicate some improvement in the flow of investment. Given that the region is home to most of the world鈥檚 population and still pulls in a disproportionately small share of total funding, clearly there鈥檚 room for growth.

Perhaps we鈥檒l see some more progress in that direction next quarter.

Methodology

The data contained in this report comes directly from 附近上门, and is based on reported data. Data is as of Oct. 6, 2025.

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.

附近上门 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 附近上门 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. 附近上门 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. 附近上门 includes venture rounds of unknown series, corporate venture and other rounds above $3 million, and those less than or equal to $15 million.

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

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

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This is a weekly feature that runs down the week鈥檚 top 10 announced funding rounds in the U.S. Check out last week鈥檚 biggest funding rounds here.

This week was a fairly busy one for large financings, with eight of the top 10 exceeding the $100 million mark. Leading the way were two software providers: , focused on health benefits software, and , used for legal practice management.

1. (tied) , $400M, health benefits: Judi Health, formerly known as Capital RX, a New York-based provider of software for employers and health plans to manage benefits, announced $400 million in new investment. The financing included a $252 million Series F round along with what the company described as additional investments into its securities, led by and .

1. (tied) , $400M, legal tech: Salt Lake City-based Filevine, a provider of legal practice management software, that it closed on two previously undisclosed rounds totaling $400 million. led the first round and joined and to co-lead the second.

3. , $250M, AI infrastructure: Modular, developer of an enterprise AI inference stack, raised $250 million in a Series C financing led by at a $1.6 billion valuation. Founded in 2022, the Palo Alto, California-based company has raised $380 million in known funding to date.

4. , $180M, fintech: San Jose, California-based AppZen, an agentic AI platform for finance teams, picked up $180 million in Series D funding led by . The company said it wants its software to enable CFOs and controllers to replace over 50% of manual work.

5. , $175M, enterprise software: Distyl AI, a developer of AI tools for enterprise customers, scooped up a $175 million funding round backed by , , , and . The financing sets a $1.8 billion valuation for the San Francisco-based company.

6. , $140M, AI processors: Empower Semiconductor, a developer of power-efficient AI processors, closed on more than $140 million in Series D financing led by . The San Jose, California-based company says its technology can enable energy savings and higher throughput of AI platforms across data centers.

7. , $105M, business communications: San Francisco-based Quo (formerly OpenPhone), raised $105 million in fresh financing led by . The company offers an AI-powered phone system marketed to small businesses.

8. , $104M, cryptocurrency: Crypto and stablecoin infrastructure startup Zerohash raised $104 million in a funding round led by . Founded in 2015, the Chicago-based company has raised $277 million in known funding to date, per .

9. , $100M, healthcare AI: New York-based Inspiren, developer of an AI-powered platform and connected-device system for senior living communities, secured $100 million in a Series B round led by .

10. , $97M, oncology care: Thyme Care, a Nashville, Tennessee-based听 startup that describes itself as a provider of 鈥渧alue-based care鈥� for oncology patients, picked up $97 million in Series D financing from a long list of venture and strategic backers.

Methodology

We tracked the largest announced rounds in the 附近上门 database that were raised by U.S.-based companies for the period of Sept. 20-26. Although most announced rounds are represented in the database, there could be a small time lag as some rounds are reported late in the week.

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