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 鈥済ame-changing.鈥�

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.

小蓝视频色情网页版 News spoke with Kim about how Reach鈥檚 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 firm鈥檚 approach to returning capital.

This interview has been edited for length and clarity.

小蓝视频色情网页版 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 firm鈥檚 focus evolve into learning, health and work?

Kim: Reach started in 2015, and our original focus was exclusively on learning and education technology 鈥� 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 learner鈥檚 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 you鈥檙e 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 鈥渆levating human potential.鈥� 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.

It鈥檚 not good enough to be pitched a SaaS or AI product and have the founders say, 鈥淭his will make people more productive at work, and therefore maybe they will earn more or enjoy their jobs more.鈥� That鈥檚 plausible, but it isn鈥檛 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: , Stepful鈥檚 allied healthcare training, and Replit for what its founder calls 鈥渃itizen developers.鈥�

On the supply side, it鈥檚 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 wasn鈥檛 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 shouldn鈥檛 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.

That鈥檚 why I liked it. I don鈥檛 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 GPTZero鈥檚 sale tell you about which AI products can become durable standalone companies and which belong within larger platforms?

Kim: I don鈥檛 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 that鈥檚 quite good and is still a standalone, venture-backed company.

It鈥檚 not clear to me that this category can鈥檛 exist on its own. We have to be very case-by-case. We don鈥檛 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, it鈥檚 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 鈥� a former educator, for example.

Third is a defensible and scalable business model.

The nonconsensus insight is funny because it鈥檚 what makes these companies look weird and maybe uninvestable in the beginning. Even within our team, they鈥檙e 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, it鈥檚 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 investors鈥� capital. What produced those returns?

Kim: We鈥檙e 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, there鈥檚 still remaining value, so we鈥檒l see how high that number gets. One fund-returning exit would be great; two or three would be amazing. That鈥檚 what we鈥檙e striving for.

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

Kim: We鈥檝e had some great exits where, given how prominent the company is, you might be surprised that our share of the returns wasn鈥檛 that large. That鈥檚 purely an ownership calculation.

From our first fund to today, we鈥檝e 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. It鈥檚 important for the exit math and distribution math.

What role do secondary transactions play in getting liquidity?

We鈥檝e become very proactive and conscientious about liquidity opportunities. Much of our distributions to investors come from secondary sales 鈥� selling our shares in a subsequent round, before an actual exit.

Whenever there鈥檚 an opportunity, we evaluate it. We consider how long we鈥檝e 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 it鈥檚 certainly mainstream now.

Sometimes, when we see enough upside, we鈥檒l buy secondary shares. GPTZero was an example: After our Series A investment, we bought secondary shares, and I鈥檓 really glad we did because it worked out well. For us, we sell more often, but occasionally we buy.

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How would you handle a junior employee questioning the way you鈥檝e always done something? Might you roll your eyes and dismiss their comments as naivety? Or would you indulge their curiosity?

As AI has made knowledge accessible on a scale never seen before, companies are becoming leaner and operating faster. What once took a large team months to do can now be done by a handful of people in a few days.

It is undeniable that autonomous systems are changing the way we work. In the small and dynamic teams of the future, choosing the right humans to direct your AI systems will become make or break for a company.

As a six-time founder, I鈥檝e learned the best workplaces are the ones where questioning things is the norm. Here鈥檚 how to build a team that questions orders as much as it obeys them.

AI by design

鈥淎I by design鈥� doesn鈥檛 only mean building the right autonomous systems. It鈥檚 also about creating autonomous humans. You need to trust the human in the loop as much as you do the technology. The team around you ultimately shapes the company in ways you can鈥檛 control. So surrounding yourself with people you trust to make decisions when you鈥檙e not in the room is critical to success.

The nature of job roles is changing. A job description can be totally different from the one advertised by the time you鈥檝e found a candidate, and a six-month roadmap is outdated by the time you鈥檝e finished drawing it up.

The has stated that as AI reshapes the workplace. Hiring for a fixed set of skills won鈥檛 move the needle. The people worth investing in are those who are able to learn what comes next.

Hire for curiosity

Curiosity is the best trait you can hire for. When I look at a CV, it鈥檚 not just experience or academic credentials that draw me in. I look for what people have built on the side. What have they made on their own initiative?

Hire for curiosity, and you鈥檒l create an environment where people are willing to throw new ideas around and challenge outdated ways of doing things. If your team is worried about saying the wrong thing, they won鈥檛 end up saying the right thing either.

In a world where technology is turning everything on its head, the companies that will thrive are the ones with curious people who are able to adapt to change quickly.

Hand over real responsibility

Employees with autonomy operate faster. They make better decisions because company vision is not abstract to people who are given real responsibility to drive it. Being involved in strategic direction stitches an employee into the fabric of the company and keeps them engaged.

Trust your employees to know what isn鈥檛 working. Allow people to pursue new ideas and reinvent things. Your employees are likely to spot potential problems before you do when they鈥檙e closer to the product. Make sure your team has the autonomy to try to fix them before they take hold.

Boredom is a big business risk

As companies become smaller, employee retention is more important than ever. Losing your best people is costlier when you have fewer of them to begin with.

The effects of a bored employee surface quickly in a small team. Boredom makes talented people a little bit slower, and a lot less likely to try the difficult thing.

The challenge for modern leaders is keeping your team engaged and interested. A bored employee is more likely to be swayed by a flattering recruiter.

Make sure to invest in development, keep your team learning, and always encourage curiosity. Give people autonomy and responsibility from the beginning, and boredom has nowhere to take hold. The mentality of risk and the drive to challenge something outdated is what you need to succeed in the changing work environment.

Dare to be a beginner, and teach your team to do the same. That junior employee questioning how you’ve always done things could be the most valuable person in the room.

is co-founder and CEO of Stockholm-based , an agent-driven, game-based learning platform. He has experience building, exiting and scaling digital companies across 70 countries. Uniplay is his sixth company to date.

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In November 2022, was doing something rare for a longtime educator: taking time off. Having launched his career as a teacher in Atlanta Public Schools, Khan became an assistant principal before founding his own public high school in Denver. After a year spent coaching principals at the district office, he decided to take a 鈥減ersonal sabbatical.鈥�

Then, ChatGPT came out.

Khan began tinkering with the new technology, fascinated by its potential.

鈥淚 actually went out to my old school building, the one that I founded, and started using it with teachers,鈥� Khan recalls. He ran workshops and asked the educators to use the tool in as many scenarios as possible.

The responses were varied. Most teachers barely touched it. A few tried, but felt doing the work manually was faster. However, some had a lightbulb moment.

鈥淭here were one or two teachers who told me, 鈥楾his has completely revolutionized the way I teach,鈥� 鈥� Khan said in an interview with 小蓝视频色情网页版 News.

Seeing that divide sparked something in him.

鈥淚 thought this technology could impact every teacher, not just teachers who are really enthusiastic about using new technologies,鈥� Khan said. 鈥淪o the task then was, 鈥楬ow can we take all the power of this new technology and make it really accessible to teachers?鈥� 鈥�

Building the 鈥榲ertical AI鈥� for K-12

That experiment set the groundwork for , a platform designed as an all-in-one AI operating system for K-12 educators and students. For teachers, the tool acts as a daily assistant. It performs tasks like building rubrics, differentiating assignments for varied learning levels, and generating practice worksheets and reading materials.

The platform also helps educators offer monitored AI experiences directly to students. Those experiences range from algebra tutors to writing assistants customized with state exam rubrics that deliver tailored feedback to help students revise their essays.

鈥淵ou can think of MagicSchool as the vertical AI solution for K-12 schools,鈥� Khan said. “Enterprises are adopting generative AI in other fields 鈥� Like in law, there鈥檚 and that are vertical AI for legal firms. We鈥檙e kind of that, but for K-12 schools.鈥�

Today, the company鈥檚 primary customers are school districts that want to provide a safe, governed environment for generative AI that aligns with data privacy rules and local curriculum priorities. MagicSchool now partners with large school systems, including Denver Public Schools, and Florida鈥檚 Broward County Schools and Hillsborough County Schools, as well as private institutions.

“One in five children in America go to a school that is in partnership with MagicSchool,” Khan noted. Additionally, roughly 8 million educators worldwide have signed up for the platform, he said.

The uphill battle to raise capital

Despite the platform鈥檚 rapid adoption, Khan’s path to raising capital for MagicSchool was a challenge. In the beginning, he worked with hourly contractors and lacked a formal business model.

鈥淚 had no real business plan,鈥� Khan said. “The most successful tech companies from my perspective as a consumer were the ones that just got a lot of users, and that was my goal 鈥� I was like 鈥榣et’s just get a lot of people using this, and we’ll figure it out from there.鈥� 鈥�

Once MagicSchool鈥檚 user base neared 1 million, Khan began pitching venture capitalists. However, when compared to standard Silicon Valley profiles, his background as an educator initially proved to be a hurdle rather than a selling point.

鈥淣obody wanted to give a former principal money,” Khan said, recalling 鈥渜uite literally hundreds of meetings鈥� before securing an institutional investor.

鈥淚 think that investors are taught to pattern match,鈥� he noted. 鈥淭hey’re saying, ‘Hey, well, did you go to ? Are you a tech person? Did you work at ? ‘… I have none of those things on my resume.鈥�

Even edtech-focused investors were hesitant, leaving Khan frustrated as he watched other founders secure millions based purely on tech-heavy resumes.

鈥淚 remember seeing other edtech companies right around our size raise seed rounds 鈥� with no product, no sales, no nothing,鈥澨� he recalled. 鈥� I would think, 鈥楶eople know what our product is. Millions of teachers know what our product is, and nobody’s heard of that one.鈥� 鈥�

To overcome the skepticism, Khan relied strictly on impressive growth metrics, convincing investors during every fundraising stage that the business鈥� 鈥渢raction was undeniable.鈥�

The strategy paid off. Following early angel investor checks, MagicSchool went on to raise a $2.4 million seed round led by Colorado-based . To date, the company has raised nearly $63 million in total funding, driven by strong financial growth, including 3x year-over-year revenue growth at the end of last year, according to Khan. The startup鈥檚 other backers include , , and.

Expertise as the next wave of innovation

Although Khan no longer manages the high school he founded, he stays connected to the classroom through district visits. The school remains a top-performing public school in Denver under a former founding team member, he noted.

鈥淥f course, I miss that,鈥� Khan admits. 鈥淭here’s nothing that can replace the relationship you build over a long period of time with students.鈥�

Yet, his deep-rooted experience in education ultimately became MagicSchool’s greatest asset 鈥� a trend Khan sees taking hold across the broader AI landscape as domain experts step up to build industry-specific tools.

鈥淚 think that what we’ve learned over time is that the model is no longer the differentiator,鈥� Khan says. 鈥淗ow you contextualize the model with the real problems that people have in the work that they’re doing, and specific expertise, is the thing that’s going to unlock the next wave of innovation and impact for generative AI.鈥�

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Smith spent eight years on active duty, serving as a technical product manager building satellites and software for national defense for the and . When he returned home from a seven-month deployment, Smith looked at the data surrounding community college transfers to four-year universities and realized how low the success rates were.

鈥淵ou have a higher chance of success [of attaining a bachelor鈥檚 degree] by pursuing a military academy 鈥� than if you go to any community college 鈥�,鈥� Smith said in an interview with 小蓝视频色情网页版 News. “That didn’t really make sense to me.鈥�

He then entered graduate school and launched in 2019 while working on his MBA听at .

Now, the Los Angeles-based startup tells 小蓝视频色情网页版 News exclusively that it has secured a $13.3 million Series A funding round to scale its AI-native platform, which automates the manual back-office workflows that can slow down university admissions.

led the financing, which included participation from , , , , , , 听and others.

The new capital brings EdVisorly鈥檚 total funding to about $22 million and marks a significant valuation step-up from its previous tranches, according to CEO Smith.

The startup鈥檚 funding comes amid an overall downturn in investment in the sector. Venture funding to education-related companies has in recent years come in at a fraction of the sums such startups raised during the pandemic peak, when investment topped out at nearly $20 billion in 2021. Through the first half of 2026, however, edtech and education-related startups have raised just under $1.8 billion globally, . That鈥檚 below the $2.5 billion raised in the first half of last year, but a notch higher than the $1.4 billion raised in the second half of 2025.

Automating the back office

EdVisorly aims to take the slow, manual paperwork out of the college admissions and transfer process.

The software doesn’t decide which students get accepted and does not serve as a gatekeeper, Smith emphasized. Instead, he said, it is designed to handle the tedious, behind-the-scenes administrative tasks that bog down university staff.

The driver behind EdVisorly鈥檚 recent growth is its proprietary platform, EddyAI. The tool works to automate repetitive back-office workflows in the admissions and enrollment process, including tasks such as reading student transcripts and recalculating GPAs based on a university鈥檚 specific criteria.

“We automate a lot of the backend processes,鈥� Smith said.

For the 10.5 million community college students in the U.S. trying to transfer to a four-year university, the process is usually a total guessing game. EdVisorly aims to bridge that gap.

Applicants are able to upload their transcripts into its platform to run an unofficial credit evaluation. The app automatically reads their classes and matches them against university requirements. Even before they ever speak to an admissions counselor, families can learn exactly how their credits stack up, what a degree will cost, and how many semesters a student would have remaining.

On the university side, registrars use the same technology to process official transfer credits and quickly build new credit-matching rules, bypassing a process that historically required a human to review every course.

“The technology actually reads the transcript, it takes that data from the transcript, and it compares it to the equivalencies that the school has,” Smith noted. “There’s kind of an infinite number of 鈥� transferable credits and courses that could exist across the United States.鈥�

The startup鈥檚 next iteration will focus on organizing all of that data, 鈥渟o that there’s no mystery as to whether a student’s credits will transfer,鈥� Smith said.

Both sides of the market

EdVisorly counts more than 100 colleges, universities and higher education systems as customers. Its roster includes institutions such as the , the , and . It has helped over 250,000 students since its inception, per the company.

The startup sells directly to higher education institutions via a B2B subscription model. Smith uses a management framework from his military days to run deployments: People come first, clear policies come second, and technology sits at the bottom as a tool to support them.

“We believe in not the concept of replacement, but truly repurposed,” Smith said. “Technology can best be implemented when you have people who are willing to adopt, and they’re innovative, and they’re excited.”

Its Series A funding will go toward upgrading the platform’s core engineering infrastructure and adding more UX designers to polish the student-facing app. Currently, the company has nearly 50 employees.

, managing partner and founder at Breachway Capital, said he is most excited about EdVisorly鈥檚 鈥渂readth of impact.鈥�

鈥淭his is not a solution that optimizes for one side of the market at the expense of another,鈥� he wrote via email. 鈥淚t drives real efficiency and tangible value for institutions while delivering a meaningfully better experience for students navigating one of the most important decisions of their lives. That is a truly unique value proposition.鈥�

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His career, which spans his time as founder of , DFJ and thehas also included high-profile missteps 鈥� most notably 鈥� underscoring the risk and volatility that goes along with making bold wagers.

A frequent personality on TV and social media, Draper is also known as a relentless champion for decentralized technology and a leading voice for bitcoin and blockchain. In 2024, he launched Draper TV, a media network, where he continues to host a global pitch competition called 鈥淢eet the Drapers.鈥� The series, which is now entering its ninth season, invites viewers at home to invest alongside him in innovative startups.

Draper exudes an almost schoolboy-like enthusiasm and passion when it comes to startups, technology, bitcoin and innovation. I recently spoke with him 鈥� while he was sporting his favorite purple and gold bitcoin tie 鈥� to get his thoughts on everything from his use of digital twins, how the current AI boom compares to previous cycles, and how he wishes policymakers approached tech regulation.

This interview has been edited for clarity and brevity.

小蓝视频色情网页版 News: What have you been up to lately? What’s occupying your time?

Draper: We are doing something interesting with 鈥� we鈥檙e joining them for something called America’s Startup. We’re going to do a business plan competition around the country for college students. It kind of dovetails into 鈥淢eet the Drapers.鈥� is one of our sponsors, so we鈥檙e thinking about doing shows in 鈥渟mall bites鈥� for them.

We鈥檙e also doing a lot with . This is the year we turn our distribution global. We had a reach of 300 million people, with 10 million seeing each episode, but we鈥檙e focusing on building the YouTube audience now because you get more control and understand the audience better.

Then there is . We鈥檙e building relationships with various countries that send their top students or potential entrepreneurs to us. People call it a 鈥減re-accelerator,鈥� but I call it a 鈥渉uman accelerator.鈥� We accelerate the people 鈥斕齮hey have to accelerate their own business. We take them through very difficult challenges: a three-day hackathon and survival training with the Navy SEALs, special forces and the . Then they have a two-minute presentation to VCs.

You鈥檙e using “digital twins.” How are you actually deploying AI in your daily operations?

Yes, they are helping. They answer questions from entrepreneurs. On our site, they can talk with me or my digital twin, or they can send in a deck.

My team has built these in a few different ways. One is a hologram by Proto at Draper University. On our website, we have a twin created by Randy Adams that can talk to entrepreneurs. We even have an AI 鈥� built by an intern 鈥� that evaluates pitch decks and 鈥渟pits out鈥� feedback.

Beyond that, we use a tool called Seer that uses video to detect facial expressions; it can determine if an entrepreneur is passionate, lying or genuinely interesting. We鈥檙e also using a voice analysis tool 鈥� similar to how reportedly hires people based on specific 鈥渧oice models鈥� that match their desired personality types 鈥� to identify the 鈥渆ntrepreneurial voice.鈥�

What do you think feels fundamentally different about the cycle that we鈥檙e in right now compared to previous ones?

Weirdly, I don鈥檛 see a big difference. It鈥檚 as big as the dot-com boom, maybe bigger. I call it the Draper iS curve. Every industry goes through this. There is a little “i” 鈥� that鈥檚 the hype. It comes to a point (the dot on the i), and then it comes down because people are disenchanted. It sits there while engineers are hard at work, and then it grows into a big “S” that goes way bigger than the top of the i.

It happened with the internet: 1999 was the climb, 2000 was the top, and 2001 was the crash. From 2001 to 2008, it grew into a huge boom. It’s happening with bitcoin now. And AI is right at the “dot” on the i or coming down off it. People are disenchanted because of energy issues, but it will eventually be bigger than anyone imagined, especially in robotics.

What鈥檚 the trend that you think right now might be a little bit overhyped? And what鈥檚 something that’s underestimated?

The quick answer is AI is overhyped, but I don’t believe that. Under-noticed is that Big Pharma would have you believe chemotherapies are the most important thing 鈥� that you create a molecule and use it forever, and then need another molecule for the side effects. We鈥檙e moving from chemotherapies to bio-cures: stem cells, cloning and genetic engineering.

Also, companies we used to call 鈥渟pace and transportation鈥� are now called dual-use. The and governments are buying in because they realize they are way behind the commercial sector. And bitcoin is in that period where 鈥渘obody cares,鈥� but it鈥檚 slowly taking over.

Do you see bitcoin actually replacing the dollar for daily use?

For now, nobody wants to spend it because they think it will be worth more. But eventually, retailers will say, 鈥淲e only take bitcoin.鈥� If that happens, there will be a run on the dollar.

People worry about quantum computing hacking bitcoin, but they鈥檒l hack the banks first 鈥� it’s way easier. I鈥檇 be more concerned about money in a bank than on a bitcoin ledger. Bitcoin also keeps perfect records; we wouldn’t need 85,000 agents because the blockchain can just pay whoever needs to be paid.

Where do you think the biggest potential for returns in the AI space are? Tooling, vertical AI, AI-native companies?

One or two general AI companies will win big and become 鈥渉ungry giants,鈥� the way was for software or bitcoin is for tech applications. A lot of people working around the edges might just be acquired by the AGI. We鈥檝e funded companies doing vertical AI: AI for patents, AI for science.

But remember, the big winners at the start of the internet were , and , and none of them ended up being a big part of the internet later. We don’t know who will rise from the ashes yet.

If you could implement one policy to accelerate innovation, what would that policy be?

Don鈥檛 regulate in anticipation of fearful outcomes. Regulate after something bad happens. Otherwise, you put a dark cloud over every innovator. I would also sunset laws. The ’33 and ’40 Acts are just keeping the poor poor and the rich rich. We should create a free market in education, too 鈥� let the best schools thrive and the worst die.

Some would argue in the case of bitcoin, we were slow to regulate. Do you disagree?

The U.S. just decided everything was a security and made it illegal. That鈥檚 why innovators are geofencing the U.S. to protect themselves from the ‘s long arms. Countries like El Salvador, Japan, Dubai and Abu Dhabi are rocking because they say 鈥渄o it.鈥�

I say decentralize everything. The guy at the tiller of the ship knows better than the general in Washington, D.C. You don’t want a president telling you how to raise your kids; you’ll do a better job than they will.

What’s the trait you now prioritize in founders that you didn’t a decade ago?

A love for the customer. It has to be an obsession. That love becomes a viral effect; customers love the product so much they tell everyone. People will naturally follow a leader who is that obsessed with their customer.

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And underlining the pace at which some startups are now sprinting to billion-dollar-plus valuations, four of the new unicorns are less than a year old.

In exit news, 9-year-old fintech unicorn was acquired by for $5.2 billion. That鈥檚 well below its January 2022 valuation of $12.3 billion but still marks a win for earlier investors seeking liquidity.

Of the 31 companies that joined the board, 23 are U.S.-based and two hail from Canada. Germany, France, Belgium, Israel, Japan and India each added one new unicorn to the board last month.

Among sectors, AI and AI infrastructure contributed the most new unicorns, totaling nine from those two areas. The next-leading sectors, with three new unicorns each, were manufacturing and security propelled by AI. AI was also a major contributor to new unicorns in the semiconductor, defense and autonomous driving sectors.

The largest funding last month for a unicorn company was $20 billion to 鈥檚 at an . Within a month of that funding, xAI in early February announced a merger with another Musk-led company, rocketmaker .

11 exits

Brex鈥檚 acquisition by Capital One was the largest of the four M&A deals for unicorn-valued companies in January.

On the IPO side, seven companies went public, the most high-profile of which were and , both foundation AI model companies based in China.

Here are January鈥檚 newly minted unicorns.

AI

• , an AI research lab focused on human collaboration, raised a $480 million seed funding led by and 1. The less than 1-year-old Redwood City, California-based company was valued at $4.5 billion.
• , an AI scientific research lab, raised a $180 million seed round led by , and . The less than 1-year-old San Francisco-based company was valued at $1.5 billion.
• AI evaluation platform raised a $150 million Series A led by 2听and . The less than 1-year-old San Francisco-based company was valued at $1.7 billion.
• Voice AI startup raised a $143 million Series C led by France-based . The 10-year-old San Francisco-based company was valued at $1.3 billion. As part of its announcement, Deepgram disclosed the acquisition of , a voice AI startup for restaurants and drive-thru ordering.
• , an infrastructure company for voice AI, raised a $100 million Series C led by . The 5-year-old San Jose, California-based company was valued at $1 billion.

AI infrastructure

• , an AI networking company, raised a $200 million Series A led by , and . The 1-year-old Santa Clara, California-based company was valued at $1 billion.
• GPU marketplace raised a $150 million Series B led by . The 2-year-old Palo Alto, California-based company was valued at $1 billion.
• , for secure AI run locally on devices, raised a Series A extension funding of an undisclosed sum. The 6-year-old Austin-based company was valued at $2.5 billion.
• , which manages a GPU marketplace, raised a Series C led by . The 6-year-old company was founded in Lithuania and is now headquartered in Miami. It was valued at $1 billion.

Manufacturing

• , a builder of factories for defense and the aerospace industry, raised a $131 million private equity funding led by . The 5-year-old Hawthorne, California-based company was valued at $1.6 billion.
• , a developer of no-code applications for manufacturing, raised a $120 million Series D led by . The 11-year-old Somerville, Massachusetts-based company was valued at $1.3 billion.
• 惭辞苍迟谤茅补濒-产补蝉别诲 , a manufacturing automation company utilizing modular robotics, raised a $90 million Series D led by . The 9-year-old company was valued at $1.2 billion.

Security

• , provider of security for cloud services in real time to protect from hackers, raised a $250 million Series B led by . The 3-year-old San Francisco-based company was valued at $1.5 billion.
• Tel Aviv-based , an AI security platform that integrates with existing security platforms to provide context on incidents, raised a $140 million Series D led by . The 6-year-old company was valued at $1.2 billion.
• Belgium-based , a developer-oriented security platform, raised a $60 million Series B led by . The 3-year-old company was valued at $1 billion.

Semiconductor

• , an AI chip developer to run transformer models, raised a reported $500 million funding led by . The 3-year-old Cupertino, California-based company was valued at $5 billion.
• , an AI chip design company, raised a $300 million Series A led by . The less than 1-year-old Palo Alto, California-based company was valued at $4 billion.

Cryptocurrency

• Stablecoin payments platform raised a $250 million Series C led by . The 4-year-old New York-based company was valued at $2 billion.
• Crypto payments network raised a $75 million Series C led by . The 5-year-old San Francisco-based company was valued at $1 billion.

Healthcare

• Maternity healthcare provider, raised a $92 million Series C led by Stripes. The 4-year-old New York-based company with plans to expand healthcare services to women and children was valued at $1.7 billion.
• , a co-ordination platform for medications across doctors, pharmacies and patients, raised a Series B led by . The 3-year-old New York-based company was valued at $1 billion.

Defense

• Paris-based , an autonomous drone maker, raised a $200 million Series B led by aircraft manufacturer . The 2-year-old company was valued at $1.4 billion.
• , a builder of secure software for the defense industry, raised a $136 million Series B led by . The 4-year-old Colorado-based company was valued at $1 billion.

Fintech

• Tokyo-based brokerage infrastructure provider raised a $150 million Series D led by . The 11-year-old company was valued at $1.2 billion.
• India-based , a payment infrastructure provider, raised a $50 million Series D led by . The 13-year-old company was valued at $1.2 billion.

Fitness

• , an owner of physical fitness brands and the parent of , raised a $785 million private equity financing led by . As part of the transaction it announced a merger with . The San Luis Obispo, California-based company was valued at $7.5 billion.

Autonomous Driving

• Toronto-based , a self-driving technology company, raised a $750 million Series C led by and ,valuing it at $3.8 billion. The 5-year-old company announced a partnership with to support robotaxis.

Social media

• , an AI-powered video generation platform for social media, raised an $80 million Series A extension funding which brings its Series A funding total to $130 million. The 3-year-old San Francisco-based company was valued at $1.3 billion.

Education

• Online tutoring platform raised a $150 million Series D led by at a $1.2 billion valuation. The 14-year-old Brookline, Massachusetts-based company was founded by Ukrainians and maintains a team in Ukraine.

Compliance

• ESG compliance software platform raised a $100 million Series C led by , a joint venture between and . The 7-year-old Baden-Wurttemberg, Germany-based company was valued at $1.1 billion.

Energy

• , a developer of a residential energy storage device for electricity and electric vehicles, raised a $163 million funding. The 7-year-old San Francisco-based company was valued at $1 billion.

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• (1,684)
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• (37)
• (186)
• (115)
• (102)
• (868)
• (494)
• (226)
• (38)
• (470)

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• A Growing Share Of Seed And Series A Funding Is Going To Giant Rounds

Methodology

The 小蓝视频色情网页版 Unicorn Board is a curated list that includes private unicorn companies with post-money valuations of $1 billion or more and is based on 小蓝视频色情网页版 data. New companies are as they reach the $1 billion valuation mark as part of a funding round.

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

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

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

Please note that all funding values are given in U.S. dollars unless otherwise noted. 小蓝视频色情网页版 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 小蓝视频色情网页版 long after the event was announced, foreign currency transactions are converted at the historic spot price.

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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 deal roundup here.

Venture investors’ thirst for AI isn鈥檛 close to quenched yet. That鈥檚 the takeaway from this week鈥檚 lineup of large U.S. funding rounds, which was mostly a mix of AI pure-plays and companies with a heavy focus on the technology.

The week鈥檚 largest round however, a $600 million financing for drone delivery provider Zipline, offered evidence that investors are also keen on platforms and technologies with applications in the physical world. The second-largest round, a $480 million seed deal for upstart AI lab Humans&, meanwhile, showed there鈥檚 also still appetite for ultra-ambitious newcomers.

1. , $600M, drones: Drone delivery unicorn Zipline it closed on over $600 million at a $7.6 billion valuation from investors including , , and . South San Francisco, California-based Zipline also says it expects to expand into at least four new states this year, with initial plans to begin service in Houston and Phoenix.

2. , $480M, AI: Humans&, an AI lab working to apply the technology in ways that are centered 鈥渁round people and their relationships with each other,鈥� secured $480 million in seed funding. The company was founded in September by top researchers from , , , and .

3. , $300M, AI infrastructure: AI infrastructure startup Baseten reportedly $300 million with backing from , and . The financing set a $5 billion valuation for the 7-year-old, San Francisco-based company.

4. , $250M, medical AI: OpenEvidence, an AI platform for doctors, announced that it picked up $250 million in a Series D funding round that doubled its valuation to $12 billion. and co-led the round, which marks the fourth fundraise for the Miami-based startup in less than a year.

5. , $215M, rare earth magnets: San Marcos, Texas-based Noveon Magnetics, a manufacturer of sintered rare earth permanent magnets, it secured $215 million in Series C funding, including $200 million from . The money will go toward expanding the company鈥檚 rare earth magnet manufacturing capacity.

6. , $200M, AI infrastructure: AI networking infrastructure startup Upscale AI $200 million in Series A funding led by , and . The financing set a valuation of more than $1 billion for the Santa Clara, California-based company, which was founded less than two years ago.

7. (tied) , $150M, online tutoring: Language learning marketplace Preply raised $150 million in Series D funding led by . The financing reportedly sets a $1.2 billion valuation for the 14-year-old, Brookline, Massachusetts-based company.

7. (tied) , $150M, AI inference: Inferact, a startup founded by creators and maintainers of open-source LLM inference engine vLLM, announced its launch along with $150 million in initial funding. and led the financing, which set an听 $800 million valuation for the company.

7. (tied) , $150M, cybersecurity: Security provider Claroty picked up $150 million in Series F funding led by . The 11-year-old company, founded in Israel and now headquartered in New York, has raised close to $900 million in equity funding to date, per 小蓝视频色情网页版 data.

10. , $115M, geothermal energy: Salt Lake City-based Zanskar, a startup applying AI to geothermal exploration, raised $115 million in Series C funding led by and joined by a long list of new and existing investors.

Methodology

We tracked the largest announced rounds in the 小蓝视频色情网页版 database that were raised by U.S.-based companies for the period of Jan. 17-23. 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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So far this year, global edtech-focused startups have raised around $2.8 billion in seed- through growth-stage funding, per 小蓝视频色情网页版 . That鈥檚 roughly flat with 2024 levels, pointing to stabilizing investment, albeit at a fraction of the peak a few years ago.

In the U.S., this year鈥檚 funding numbers are a bit stronger relative to 2024, with $1.2 billion invested in edtech startups so far. While still far off of the pandemic-era highs, 2025鈥檚 funding figures puts this year roughly on par with 2023.

What鈥檚 in and what鈥檚 out

Edtech is a vast space, covering everything from preschool lesson-planning to corporate upskilling. Given this, it鈥檚 not uncommon to see a downturn in one subcategory while another remains a funding favorite.

If we were to generalize trends looking at this year鈥檚 larger rounds and exits, it appears investors are particularly keen on opportunities in healthcare education and training. At the K-12 level, VCs are also backing startups deploying AI tools to customize lessons for individuals and free up teachers from routine, repetitive tasks.

As for what鈥檚 not hot, we鈥檝e seen a movement away from coding academies and teaching platforms, with the rise of coding automation tools. We鈥檙e also seeing a paucity of jumbo-sized funding rounds and not a lot of deals that look like pre-IPO financings.

What the biggest rounds tell us

So who is getting funded?

, a Berlin-based startup offering a tool to learn about and research medical information, raised the largest round, securing nearly in a March financing. The company started with a focus on medical students but now also markets to practitioners.

, a provider of content and online learning activities for young children, secured the next-biggest funding, a September round led by .

Other larger rounds this year include an financing for , developer of a chatbot to help students navigate college life and boost retention, and a Series B for , a provider of AI-enabled time-saving and productivity-enhancing tools for educators.

For a slightly broader view, below we put together a list of eight of the larger funding recipients in the education sector this year.

Buyers too

Edtech is also seeing some exit activity. This is coming in the form of M&A, as the IPO market has been quiet this year.

Most recently, , a platform for healthcare workers to learn new skills and obtain certifications, sold to , a software platform for senior living and home care providers, for an undisclosed sum.

Founded in 2013, Cambridge, Massachusetts-based Care Academy previously raised at least . The company, founded and led by -trained educator , carved out a niche offering upskilling opportunities to health workers like home care aides and nursing home staffers, opening a path to advancement for what are typically lower-paid positions.

Also in the health sphere, , an Austin startup focused on online learning tools for medical students and educators, sold this spring to exam prep provider , a portfolio company of private equity firm . Previously, 11-year-old OnlineMedEd had raised at least .

And in the post-secondary education space, , a Toronto-based provider of software tools for colleges to attract and retain students, sold a majority stake to PE firm in August.

The optimist case

Looking ahead, the optimist case is that founders, investors and acquirers alike will find plenty of appealing opportunities in ed tech.

Longtime education startup investor considers the education and training market to be one of the fastest-growing sectors in the global economy. In its 2025 , the firm projects the global education market is on track to surpass $10 trillion by 2030.

In terms of growth, Owl unsurprisingly points to AI as the largest ed tech driver. In recent years, the report notes, AI in the classroom has moved beyond the experimentation stage and is already proving vital in saving educators hours of work, providing personalized tutoring to students, and helping craft compelling lesson plans.

Eventually, it鈥檚 likely we鈥檒l see the impact of AI innovation in edtech also showing in the form of more funding for startups in the space.

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Those were once again the findings of our annual look at which U.S. colleges and universities graduate the highest number of funded startup founders, based on 小蓝视频色情网页版 data.

As usual, four universities 鈥� , , and 鈥� hung on to the top four slots. The remaining names on our list mostly include a mix of large state research universities, Ivy League institutions and private schools known for tech and business.

For a more detailed overview, we posted the full ranking below. It tracks the number of founders affiliated with each school whose startups raised seed through growth-stage funding this past year.

Leading schools are also hard to get into

When we look at the top-ranked schools on our list, all are known for providing a rigorous education. What they also share in common are highly competitive admissions processes.

This is particularly true for undergrads. For the , for example, Stanford admitted just 3.6% of applicants, followed by Harvard at 3.7%, and MIT at 4.6%.

Many of those accepted are likely people well-poised to succeed in entrepreneurship regardless of degree. For evidence, look at the history of prestigious university going on to found valuable companies such as , and . That said, of course, we also see co-founders in areas that rely on their academic expertise, particularly among AI and biotech unicorns.

Public university outperformers

Public universities, which have higher acceptance rates for in-state residents, are harder to measure for admissions competitiveness. But when it comes to funded-founder track records, it鈥檚 clear that a few names stand out.

The far-and-away leader in this category is UC Berkeley, which benefits from its highly regarded STEM programs as well as its location in the San Francisco Bay Area, the global capital of the venture industry.

ranks a distant second, with just over 100 grads going on to launch companies funded in the past year. and are close behind, with 97 and 93 funded founders, respectively, followed by , with 86.

Ivies and hard-to-get-into private schools round out the list

All eight schools in the made our list, which is what we鈥檝e seen in past years as well. After Harvard, the next-biggest Ivies for funded startup founders were , and .

Of course, there are also other private, non-Ivy universities that are notoriously hard to get into or known for particularly demanding STEM curriculum. Not surprisingly, these churn out a lot of funded founders as well. In this category, beyond the aforementioned Stanford and MIT,听 , and also ranked high on our list.

Since size is a consideration here as well, we also ought to give a shout-out to some smaller schools that produce a disproportionately high number of funded founders. For instance, , with only about 2,500 students, outperforms many much larger well-regarded schools.

Business schools play an outsized role

Several of the schools on our list also got there to a large degree as a result of business school grads.

Per 小蓝视频色情网页版 data, standout business schools for funded founders include , , Northwestern鈥檚 and Penn鈥檚 , among others.

Business schools have also factored in favorably in prior research looking at universities that produce the highest numbers of startup CEOs.

No big changes

While it may seem like the world is changing at a faster rate than ever, funded founder and university rankings are one of the more stable indicators. Over the years we鈥檝e been crunching these numbers, the component universities of our list, and their respective rankings, haven鈥檛 budged dramatically.

Bottom line: If your plan is to be a unicorn founder, attending Stanford is still probably not a bad idea.

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Graduates and famous dropouts have launched companies that are collectively valued in the trillions today. And alongside and , Harvard regularly ranks in the top three schools for graduating founders of funded startups.

But how is it measuring up lately?

With graduation season upon us, and Harvard garnering headlines in its with the administration, we thought it would be timely to look at the school鈥檚 recent record in launching funded founders and CEOs. This includes a look at students鈥� roles in founding and leading unicorns, launching new funded startups, and taking companies to exit.

Still going strong

First, we looked at Harvard attendees鈥� role in founding some of today鈥檚 most valuable private, venture-backed companies. To illustrate, we put together a list of 12 of the most heavily funded startups with a Harvard-affiliated founder.

Notably, the company at the top of our list 鈥� 鈥� was co-founded by , who studied at Harvard, but chose building a startup over completing a degree. He joins a famous league of Harvard dropouts-turned-billionaire-founders, including and .

Another heavyweight in the news this week is human resources software provider , which just raised $450 million at a $16.8 billion valuation. Co-founder and CEO is a Harvard grad.

The other mega-funding recipient on our list 鈥� Medicare benefits provider 鈥� counts Harvard grads and brothers and as co-founders. Ed Park also serves as CEO.

$200B+ in funding to Harvard-affiliated startups

Private, venture-backed companies founded by former Harvard students have also raised copious sums over the years.

Per 小蓝视频色情网页版 data, there are currently over 1,900 such companies that have raised over $1 million in equity investment. To date, those companies have collectively in equity funding over the years.1

Much of that funding is rather recent. Per 小蓝视频色情网页版 data, companies with a Harvard-affiliated founder or co-founder have raised over $54 billion in the past year. However, this is only if one includes nearly $47 billion for , which counts 鈥� who attended Harvard but later transferred to MIT 鈥� as co-founder and current CEO.

Harvard is a CEO factory too

Harvard is also pretty good at churning out future CEOs of high-valuation venture-backed companies.

Per 小蓝视频色情网页版 data, there are 158 Harvard alumni of current unicorns, emerging unicorns or exited unicorns. Many of them are also founders or co-founders of the companies they lead.

Many of the best-known names on the list are onetime unicorns that are now public. This includes several that made their market debuts several years ago, such as , , and .

In prior surveys, we鈥檝e found that , in particular, has a strong track record for graduating future CEOs. That鈥檚 the alma mater of many unicorn CEOs as well. (Although it鈥檚 tempting as an aside to note that the success of OpenAI, Stripe, and , gives credence to the notion that perhaps people who matriculate at Harvard but later leave are the most fundable entrepreneurs.)

The path ahead

Whether Harvard continues on its well-worn path of serving as a launchpad for startup founders and leaders, of course, remains to be seen. In coming days, we鈥檒l also be taking a look at how the school compares to other well-regarded institutions for matriculating future funded founders. Stay tuned.

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