July 2026
Unicorns Minted in 2025
Last updated on 31 December 2025
Which unicorns were created in 2025?
Over 140 unicorns were minted in 2025!
5 new unicorns have been added end of July and through August, all coming from the 🇺🇸 US, and all but one (Polymarket) being AI-native.
Nearly 80% of all unicorns minted in 2025 were created in the US.
Visible growth in the Middle East, with three unicorns minted in 2025 - 🇦🇪 Xpanceo (deep tech), 🇦🇪 The Open Platform (crypto), and 🇸🇦 Ninja (e-commerce).
Within Europe, 🇬🇧 the UK is the clear leader, having created unicorns like PhysicsX (AI), Cera (health), Isomorphic Labs (biotech) and MUBI (streaming).
Complete AI domination - 70% that became unicorns are AI-native, and the remaining 30% operates in other sectors.
# | |||||||||
|---|---|---|---|---|---|---|---|---|---|
1 | 🇺🇸 | $12.0B | $3,000M | seed round | Jul-25 | AI | |||
2 | 🇺🇸 | $8.0B | $2,000M | Series B | Nov-25 | AI | |||
3 | 🇺🇸 | $5.0B | $500M | Series A | Oct-25 | Non-AI | |||
4 | 🇺🇸 | $4.5B | $475M | Seed | Dec-25 | AI | |||
5 | 🇺🇸 | $4.0B | $250M | growth round | Aug-25 | AI | |||
6 | 🇺🇸 | $4.0B | $250M | Series C | Oct-25 | AI | |||
7 | 🇺🇸 | $4.0B | $900M | Series C | Nov-25 | AI | |||
8 | 🇺🇸 | $3.5B | $210M | Series B | Jul-25 | AI | |||
9 | 🇺🇸 | $3.1B | $100M | growth round | Aug-25 | AI | |||
10 | 🇺🇸 | $3.0B | $37M | 81.1x | $100M | Series C | Jun-25 | AI | |
11 | 🇺🇸 | $3.0B | $100M | Series B | Jan-25 | Non-AI | |||
12 | 🇺🇸 | $3.0B | $260M | Series E | Sep-25 | Non-AI | |||
13 | 🇺🇸 | $3.0B | $700M | Series B | Dec-25 | Non-AI | |||
14 | 🇺🇸 | $2.8B | $350M | Series B | Jul-25 | Non-AI | |||
15 | 🇺🇸 | $2.8B | $8M | 361.8x | $250M | Series D | Feb-25 | AI | |
16 | 🇺🇸 | $2.7B | $150M | Series D | Jul-25 | AI | |||
17 | 🇺🇸 | $2.6B | $190M | Series C | Mar-25 | AI | |||
18 | 🇺🇸 | $2.5B | $250M | Series C | Mar-25 | AI | |||
19 | 🇺🇸 | $2.5B | $100M | 25.0x | $200M | Series B | May-25 | Non-AI | |
20 | 🇺🇸 | $2.5B | $250M | Series C | Nov-25 | AI | |||
21 | 🇺🇸 | $2.2B | $150M | Series D | Sep-25 | AI | |||
22 | 🇺🇸 | $2.1B | $68M | Series B | Nov-25 | AI | |||
23 | 🇨🇳 | $2.1B | $208M | 9.9x | undisclosed | Series B | Mar-25 | AI | |
24 | ![](data:image/svg+xml,<svg xmlns="http://www.w3.org/2000/svg" width="20" height="20" viewBox="0 0 20 20"><rect fill="%23e5e7eb" width="20" height="20" rx="4"/></svg>) Erebor Bank | 🇺🇸 | $2.0B | $250M | growth round | Jul-25 | Non-AI | ||
25 | 🇬🇧 | $2.0B | $315M | growth round | Aug-25 | AI | |||
26 | 🇺🇸 | $2.0B | $275M | Series C | May-25 | AI | |||
27 | 🇺🇸 | $2.0B | $24M | 83.3x | $185M | Series C | Jun-25 | Non-AI | |
28 | 🇺🇸 | $2.0B | $75M | 26.7x | $100M | Series B | Jan-25 | AI | |
29 | 🇺🇸 | $2.0B | $200M | Series D | Mar-25 | Non-AI | |||
30 | 🇺🇸 | $2.0B | $150M | Series B | Mar-25 | AI | |||
31 | 🇺🇸 | $2.0B | $415M | Series C | Aug-25 | AI | |||
32 | 🇺🇸 | $2.0B | $150M | Series E | Dec-25 | Non-AI | |||
33 | 🇺🇸 | $2.0B | $100M | growth round | Sep-25 | AI | |||
34 | 🇺🇸 | $2.0B | $610M | Series D | Oct-25 | Non-AI | |||
35 | 🇺🇸 | $2.0B | $400M | 4.9x | $138M | Series C | Feb-25 | Non-AI | |
36 | 🇺🇸 | $1.9B | $350M | Series B | Nov-25 | AI | |||
37 | 🇸🇪 | $1.8B | $260M | Series B | Jan-25 | AI | |||
38 | 🇺🇸 | $1.8B | $75M | 24.0x | $200M | Series A | Jul-25 | AI | |
39 | 🇺🇸 | $1.8B | $1,000M | 1.8x | $72M | Series C | Jan-25 | Non-AI | |
40 | 🇺🇸 | $1.8B | $175M | Series B | Sep-25 | AI | |||
41 | 🇺🇸 | $1.8B | $300M | Series D | Dec-25 | Non-AI | |||
42 | 🇺🇸 | $1.8B | $300M | Series D | Sep-25 | Non-AI | |||
43 | 🇬🇧 | $1.8B | $605M | series A | Mar-25 | AI | |||
44 | 🇺🇸 | $1.7B | $165M | Series B | Feb-25 | Non-AI | |||
45 | 🇨🇳 | $1.7B | $140M | 11.9x | $97M | Series C | Jun-25 | Non-AI | |
46 | 🇺🇸 | $1.6B | $141M | Series B | Jan-25 | AI | |||
47 | 🇮🇪 | $1.6B | $185M | Series B | Jun-25 | Non-AI | |||
48 | 🇺🇸 | $1.6B | $44M | 37.0x | $122M | Series D | Jun-25 | AI | |
49 | 🇺🇸 | $1.6B | $365M | Series D | May-25 | AI | |||
50 | 🇺🇸 | $1.6B | $250M | growth round | Sep-25 | AI |
Showing 1 to 50 of 138 rows
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Data and methodology
Underlying data
Public markets data is powered by FactSet (consensus analyst estimates), and Morningstar (historical data). Data points are calendarized to December where relevant: retrieved data on financial year ends (e.g. FY, FY+1 etc.) are mapped to calendar years (2025A, 2026E etc.) before the appropriate month weights are then applied to prior/future fundamentals.
Private transaction data is multi-sourced, aggregated from harvesting public information, 3rd party APIs, and data engineering. All data is verified and provided with an extensive manual process. If data permits, we apply our own logic to get to the EV. For example, for a large M&A deal with available information on the target's net debt, we might adjust a valuation to fully reflect an accurate EV. In all other cases, we take the reported valuation as the numerator. Financials: we source LTM revenue and LTM EBITDA data from company filings, press releases, or other verified sources. If LTM data is unavailable, we take the 'next best-fit' period (run-rate or calendar year), provided it makes sense in a given case. For example, if a deal closed in November 2025, we might take full-year 2025 revenue as a revenue benchmark.
Any raw figures are harmonised to USD for comparison purposes.
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