AI in Education Funding Tracker (88 deals)

Our funding tracker covering the AI in education market

Below is the table listing all the deals. You may find our methodology at the end of this page.

And, if you want to gain a deeper understanding of the market and its current dynamics, get our report covering the AI In Education Market.

Is AI in education funding actually big right now?

AI in education funding is real and active today, but $534.4 million across 87 financings still puts this market in the early stages of becoming a major venture category.

We found 75 companies raising money from the start of 2024 through the end of our research window. The median financing was $4 million and the average quantified round was $6.29 million. The biggest deal was MagicSchool's $45 million Series B, and no individual financing crossed $50 million.

That last point changes how we should read the headline total. Some AI markets reach billions of dollars largely because one or two companies raise several hundred million dollars at once. AI education has built its $534.4 million with a much broader collection of small and mid-sized rounds.

Activity is still coming through at the end of the window. Ed.ai, for example, followed its earlier €1.7 million financing with a fresh €5 million equity Seed round and said the money would support expansion in Europe and the United States. Recent activity still looks alive; what we have yet to see is funding at the scale reached by mature software or frontier-AI companies.

Indicator	Result
Distinct financings	87
Funded companies	75
Quantified capital	≥$534.4M
Median financing	$4.0M
Average quantified financing	$6.29M
Largest financing	$45.0M
Financings above $50M	0
Companies raising more than once in the window	11

How many AI education startups are actually getting funded?

The AI education funding market currently comes down to 75 companies, and most of them only appear once during our research window.

We counted 64 companies with a single financing, ten with two and only one with three or more. In other words, 85.3% of the companies we tracked never show up for a second financing between the beginning of 2024 and the end of the period.

That gives the market a different shape from the constant flow of AI education launches might suggest. Plenty of startups can get into the funded population, but only a small group has so far demonstrated repeated access to capital.

The money follows the same pattern. Companies appearing once still account for $384.3 million because that group includes later-stage businesses whose earlier rounds happened before our window. The 11 companies that raised more than once during the period collected another $150.1 million.

So 87 deals sounds fairly broad at first. Once we follow the companies themselves, the investable market looks more compact.

Is AI education funding concentrated in a few winners?

A clear top tier has already formed in AI education funding: ten companies hold 48.9% of the capital we identified, while MagicSchool alone accounts for 11.2%.

MagicSchool raised $60 million across two rounds in our window. Knowunity follows at roughly $31.2 million, then Subject at $28 million, Zhejiang Jingzhunxue at around $27.6 million and SchoolAI at $25 million.

The concentration is meaningful without becoming extreme. The top five companies hold 32.1% of capital, which still leaves roughly two-thirds spread across the rest of the market. Removing MagicSchool would leave close to $475 million of quantified funding. Where a few leaders pull ahead of a long tail is what the market maps in our market report about AI in education lay out.

Where MagicSchool changes the picture much more is inside its own category. Its two rounds represent about 41.8% of all Educator Copilot capital. Gizmo has a similar effect on AI Practice Tools, where its $22 million Series A makes up around 47% of the category's funding.

The broader market therefore has several real scale-up candidates rather than one company surrounded by tiny startups. At category level, though, individual winners can dramatically change how well-funded a segment appears.

What does a normal AI education startup raise today?

A normal AI education financing today is about $4 million, and more than half of all deals stay below $5 million.

We found 49 financings under $5 million, equal to 56.3% of the market. Another 30 landed between $5 million and $20 million. Only six reached the $20 million to $50 million range.

The interesting part is where the dollars sit. Those 49 small rounds collectively contribute only $86.8 million, or 16.2% of known capital. The 30 rounds between $5 million and $20 million contribute $268.9 million, just over half the entire market.

For founders, the gap between a normal round and a genuinely large AI education round is substantial. Raising $2 million to $5 million is common. Getting beyond $10 million puts a company into a far smaller group. A $20 million-plus financing already belongs near the top of this market.

Which parts of AI education are getting the biggest checks?

AI Learning Software is getting the most money today, while AI Tutor Platforms are producing the most financings.

Tutors account for 32 deals, more than any other category, but they attract $152.5 million. AI Learning Software has 26 deals and receives $192.5 million, making it the largest destination for capital.

Educator Copilots form another serious pocket of funding. We counted 14 deals worth $107.7 million. That is one-sixth of all financings but roughly one-fifth of the money.

At the smaller end, AI Grading Tools generated five financings worth $17.2 million. AI Assessment Platforms reached $18 million across only three deals, and one company, The Invigilator, represents most of that amount.

This is why simply counting startups gives an incomplete picture. Tutors are where we find the most funded companies. Broader learning platforms and teacher-facing software are where the larger checks show up more often.

Category	Deals	Companies	Capital	Median financing
AI Learning Software	26	25	$192.5M	$5.0M
AI Tutor Platforms	32	28	$152.5M	$3.32M
Educator Copilots	14	11	$107.7M	$4.0M
AI Practice Tools	7	7	$46.5M	$2.5M
AI Assessment Platforms	3	3	$18.0M	$4.0M
AI Grading Tools	5	4	$17.2M	$2.09M
Total	87	75	≥$534.4M	$4.0M

Why do AI learning platforms and teacher copilots get bigger checks?

The biggest checks in AI education tend to arrive once a product has become expensive to distribute, support and operate inside schools.

MagicSchool makes the pattern easy to see. When the company announced its $45 million Series B, it said millions of people were using the platform monthly and that it was working with more than 10,000 schools. The new money was going into product and engineering, partnerships, customer experience and safety.

Subject gives us another version of the same story. Vistara Growth's announcement for its $28 million investment describes accredited K-12 curriculum, AI-powered teaching products and expansion across school districts. The company said it would use the capital to expand courses, deepen automation and scale go-to-market.

Knowunity reached roughly $31.2 million with a different model. XAnge said the platform had 20 million users across more than 15 countries and around 380,000 student creators when it raised. At that point, the company was funding an international consumer platform rather than an early product experiment.

Nectir's $12.5 million Series A also fits the institutional side of the picture: the company described its product as purpose-built AI infrastructure for higher education.

Across these cases, the larger financing needs come from distribution, curriculum, integrations, safety, customer support and international expansion. The AI model itself is only one part of what investors are paying to scale.

How young are AI education startups when they raise money?

AI education startups are getting funded very early: the median company is only two years old at the time of financing.

Among the 74 companies where we could establish a usable founding year, 41 were founded in 2023 or later. That is 55.4% of the documented cohort. Almost one-third were founded in 2024 or later.

The age also changes by product. AI Tutor Platforms, Educator Copilots and AI Grading Tools all have a median company age of two years when they raise. AI Practice Tools come in at three years and AI Learning Software at four.

There are some very fast examples. MagicSchool was founded in 2023 and reached a $15 million Series A the following year. Sparkli, founded in 2025, raised $5 million soon after launch. Wilgo also raised around $7 million in its first year.

A different group comes from older education businesses adding or pivoting toward AI. ConveGenius, Third Space Learning and SpeakX fall closer to that model. Those companies bring years of operating history into the current AI cycle, which helps explain why age alone does not perfectly track stage.

Still, the center of gravity is clearly young. Investors are often making their first meaningful bet on an AI education company before it has accumulated much operating history. Backing companies with so little history carries risks, and we rate the less obvious ones in our report covering the AI in education market.

Where does AI education funding start to break down?

AI education funding narrows sharply after Seed: we found 60 Seed financings, 13 Series A rounds and only four Series B rounds.

The check size jumps at the same time. A Seed financing has a median size of $1.93 million. Series A moves to $11.5 million, and Series B reaches $29.39 million.

For every Series A in the market, there are roughly 4.6 Seed financings. The ratio from Series A to Series B is another 3.25 to one.

That tells us where the difficult part begins. Starting an AI tutor, teaching assistant or learning product and raising an initial round has become relatively common. Turning one of those products into a company investors will back with $10 million, $20 million or $30 million is much rarer.

The latest rounds show that companies can make the jump. Flint raised $15 million at Series A, Gizmo raised $22 million and Subject reached $28 million in growth capital. There are simply far fewer companies operating at that level than the Seed activity might lead someone to expect.

Stage	Deals	Share of all deals	Capital	Median financing
Seed	60	69.0%	$180.7M	$1.93M
Series A	13	14.9%	$158.0M	$11.5M
Series B	4	4.6%	$108.8M	$29.39M
Series C	0	0%	$0	-
Series D+	0	0%	$0	-
Growth Equity	3	3.4%	$40.9M	$7.0M
Unknown	7	8.0%	$46.1M	≈$4.0M

Why is there almost no Series C money in AI education?

Series C money is basically absent from AI education today: after only four Series B financings, our entire window contains no Series C or Series D+ rounds.

The age of the cohort explains part of it. More than half of the companies with known founding dates started in 2023 or later. Many simply have not had enough time to go from Seed through A, B and C.

Age does not explain the whole gap, though. The ladder is already thinning long before Series C. As seen above, only 13 Series A financings emerge from 60 Seed deals, and just four Series Bs appear after that.

That points to a commercial test as much as a chronological one. A young AI education product can attract early capital on product quality, founder credibility and early adoption. The next rounds require something harder: sustained usage, distribution, school or district adoption, convincing economics and enough growth to support much larger checks.

For now, AI education has a large early-stage funnel and only the beginnings of a late-stage class. We still do not really know how many of today's Seed and Series A companies will grow into businesses large enough to build a proper Series C market.

Are investors still funding new AI education startups, or mostly doubling down on existing ones?

Investors are still backing new AI education startups, but the larger checks overwhelmingly go to companies that have raised before.

We classified 36 financings as first financings, equal to 41.4% of all deals. Their median size was just $1.27 million, and together they contributed about $95 million.

Follow-on financings look very different. We counted 50 of them, with a median of $5.55 million and roughly $436 million of capital. More than four-fifths of the quantified money in the market therefore sits in follow-ons.

There is plenty of fresh company creation underneath that. Vimi entered with a $12 million first financing, SigIQ.ai with $9.5 million, Wilgo with roughly $7 million and Sparkli with $5 million. Smaller first checks appear constantly throughout the dataset as well.

The pattern becomes much more selective once companies return for more money. Brisk Teaching moved from a $5 million Seed financing in our window to a $15 million Series A. Ed.ai went from around $1.9 million to roughly $5.8 million. Wild Zebra returned with $5 million of fresh cash after its earlier financing.

So new entrants are still getting a shot. Investors reserve most of the serious capital for companies that have already passed an earlier funding test. Companies that fail the next funding test are worth studying, and we ask what stalled startups share in our report on AI in education.

Does AI education funding come steadily, or in bursts?

AI education deal flow is fairly steady, while the dollars still jump around whenever a large round lands.

Across completed months in our research period, the average was 2.63 deals and the median was three. The busiest month had five. We are dealing with a low-volume market, but one where financing announcements arrive relatively regularly.

Monthly capital is much less smooth. The median complete month produced about $14.3 million. One of the biggest months reached roughly $49.7 million because Knowunity, StudyFetch and Wilgo all raised meaningful rounds around the same period.

Another month reached roughly $48.2 million almost entirely because MagicSchool raised $45 million.

Deal count and capital tell different stories. Three small financings can make a month look active without adding much money, while one major Series B can make an otherwise quiet month look enormous.

For anyone following this market through headlines, that distinction is useful. A sudden jump in dollars can be one company. A genuine widening of the market would show up in the number of companies getting funded as well.

Does North America really dominate AI education funding?

North America currently dominates the money side of AI education, even though Europe is almost as active by deal count.

North America produced 34 financings versus 29 in Europe. That is a modest difference in activity. Capital is much further apart: North America captured $296.7 million, compared with $126.1 million in Europe.

The median financing makes the gap even clearer. North America's median is $5.15 million, while Europe sits at $1.71 million and Asia-Pacific at $1.80 million.

European companies can still reach serious scale. Knowunity raised roughly $31.2 million, Gizmo $22 million and Nectir $12.5 million. The issue is frequency: Europe generates plenty of funded AI education startups but fewer large checks across the cohort.

Asia-Pacific shows a similar pattern. It produced 18 deals, including Alibaba-backed Zhejiang Jingzhunxue, yet captured only 14.3% of total capital.

So the geographic imbalance currently sits more in financing size than startup creation.

Region	Deals	Companies	Capital	Median financing
North America	34	30	$296.7M	$5.15M
Europe	29	24	$126.1M	$1.71M
Asia-Pacific	18	16	$76.5M	$1.80M
Middle East	3	2	$16.2M	$3.0M
Latin America	2	2	$8.0M	$3.98M
Africa	1	1	$11.0M	$11.0M
Total	87	75	≥$534.4M	$4.0M

Which investors keep coming back to AI education?

Very few lead investors keep coming back to AI education: only three appear on more than one financing in our window.

We could identify a lead on 66 of the 87 deals, and those financings involve 78 different disclosed leads because several were co-led. Owl Ventures, Triple Point Ventures and Eka Ventures are the only names that lead more than one deal.

Even those repeat appearances are limited. Owl Ventures shows up on Brisk Teaching and StudyFetch. Triple Point Ventures backed two Chalkie financings. Eka Ventures appears across two Medly AI tranches.

Together, recurring leads cover only six of the 66 deals where we know the lead investor.

Compare that with the larger financings. Valor Equity Partners led MagicSchool's $45 million Series B. XAnge led Knowunity. Insight Partners led SchoolAI. Shine Capital led Gizmo. Vistara Growth led Subject. Bessemer led Brisk Teaching's Series A.

There is no obvious small club controlling access to AI education capital right now. Investors are coming into the category from many different directions, and most only appear once. With no small club of specialist funds yet, we follow what investors back and avoid in our AI in education market report.

Do strategic investors actually matter in AI education?

Strategic investors matter around specific distribution and infrastructure deals, but they appear in only 14.9% of AI education financings.

We found 13 deals with at least one strategic investor. Their median financing was $5.4 million, compared with $3.9 million for deals without a strategic.

More revealing is who those investors are. College Board participated in StudyFetch. Alibaba backed Zhejiang Jingzhunxue. Klett invested in Teachino. Educational Records Bureau backed Wild Zebra. Searce participated in ConveGenius. La Poste Ventures joined Ed.ai.

Adobe Ventures is the clearest repeat strategic investor, taking part in both MagicSchool financings in our window.

These deals tend to have an understandable commercial connection. Assessment groups can help an assessment or learning company. Education publishers bring content and distribution. Infrastructure businesses can support deployment. Large technology groups bring AI ecosystems and market reach.

Still, 74 of the 87 deals happened without a strategic investor. AI education venture funding works perfectly well without corporate capital, even if the right corporate partner can become useful once a startup needs distribution, integration or industry credibility.

What do the biggest AI education rounds have in common?

The biggest AI education rounds are going to companies that already have meaningful distribution and now need money for school deployment, curriculum, support, safety or international growth.

MagicSchool had millions of monthly users and partnerships with more than 10,000 schools when it announced its $45 million round. Knowunity had 20 million users in more than 15 countries when it raised €27 million. Gizmo said it served more than 13 million learners across more than 120 countries when it announced its $22 million Series A.

Institutional businesses show the same pattern through a different route. Subject's $28 million financing supports accredited curriculum and district expansion. SchoolAI's $25 million Series A went into a platform built around teachers, students and school systems. Nectir raised $12.5 million to scale AI infrastructure for higher education.

Once a company reaches that point, the expensive part is no longer just building the product. It has to win distribution, support users, integrate into institutions, satisfy schools on safety and reliability, and keep improving the software while the organization grows.

That is currently the clearest dividing line between an ordinary AI education funding round and one of the market's biggest checks.

What should we actually take away from the funding data?

AI education is currently a genuine venture market, but it is still young. We found 75 funded companies and more than half a billion dollars of quantified capital, with very little evidence yet of the late-stage financing layer we would expect from a mature category.

The typical company is operating with much less money than the biggest announcements suggest. Small rounds dominate deal count, while $5 million to $20 million financings supply most of the actual capital.

There is also a clear difference between where startups are being created and where large checks go. AI Tutors generate the most deals, while broader learning software and educator-focused platforms attract more capital relative to their numbers.

The funding ladder is probably the most important thing to watch now. Seed capital is plentiful compared with Series A, Series B is already rare, and Series C has yet to appear in our cohort. The next few years will show how much of today's early-stage activity can survive that progression.

Geography matters mostly once companies begin raising larger rounds. Europe produces almost as many financings as North America, yet North American companies raise much larger checks across the market.

Investor concentration remains surprisingly low. The companies are beginning to separate into winners, but the funds backing them are still highly fragmented. There is no dominant group of AI education venture firms repeatedly underwriting the category.

Finally, the largest rounds tell us what investors are willing to pay for these days. Serious money tends to arrive when an AI education company has already built distribution and needs to operate at scale. The companies that can turn product adoption into durable school, consumer or institutional distribution are the ones most likely to define the next stage of this market.