Sixth Annual Enterprise Tech 30 List released by Wing Venture Capital?Generative AI dominates, enthusiasm strong for early-stage companies
Wing Venture Capital, a venture capital firm investing in early-stage companies driving the AI-first transformation of business, today announced the fifth annual Enterprise Tech 30?a definitive list of the most promising, private enterprise tech private companies across all stages of maturity.
This list and accompanying research are the product of a two-phase process to distill a stack-ranked list of the top venture-backed enterprise tech companies and to uncover key insights and trends driving the market. Of the 15,000+ venture-backed enterprise tech companies in consideration, 40 companies have been selected as the enterprise tech leaders, segmented by "stage" as determined by an institutional research process.
This year, a record 112 venture capitalists across 92 venture capital firms participated in determining the ET30. The assets under management for the venture capital firms ranged from $50 million to $150 billion.
The Enterprise Tech 30 for 2024 are:
Early
Mid
Late
Giga
LangChain
Unstructured
Modal Labs
LlamaIndex
Magic
Baseten
Clay
Chroma
Fixie
Braintrust
Pinecone
Perplexity
ElevenLabs
Together AI
Harvey
MotherDuck
Chainguard
Linear
Hex
Metronome
Figma
Rippling
Canva
Cribl
Hugging Face
Vercel
Scale AI
dbt Labs
Abnormal
Glean
OpenAI
Databricks
Stripe
Anduril
SpaceX
Anthropic
Snyk
Ramp
ServiceTitan
Airtable
The companies are categorized by total capital raised. The Giga stage includes companies that have raised $1 billion or more; early-stage includes companies that have raised $35 million or less; mid-stage from $35 million to $150 million; and late-stage includes $150 million or more.
"In ET30's sixth year, we see the undeniable dominance of generative AI reflected across the entire list, but especially among the youngest companies," said Peter Wagner, founding partner at Wing Venture Capital. "Where later stage companies saw decreases in deal sizes and valuations, early stage companies saw increases. It's a fascinating market divergence, in which those companies excelling in the fast-moving waters of AI hold a lot of interest for investors, while others struggle to garner attention."
The research process for uncovering the Enterprise Tech 30 also uncovered insights about the state of enterprise tech, including:
By category, 30% of the ET30 2024 companies are in AI models and tools. 25% are in SaaS, and 20% are in data platforms, ETL and BI. 10% are in cybersecurity. We describe and define our category framework, which is designed to be MECE (mutually exclusive and collectively exhaustive), in the next section.
By stage, 90% (9 of 10) of the early stage ET30 2024 companies are in AI models and tools and data platforms, ETL and BI. 10% (1 of 10) are in SaaS. There are no cybersecurity, developer and devops tools, fintech, and defense/aero early stage ET30 companies this year.
For mid stage ET30 this year, data platforms, ETL and BI co-leads with 30% of ET30 2024 companies, as compared to 30% in SaaS, 20% in AI models and tools, 10% in dev and DevOps tools, and 10% in cybersecurity.
40% of ET30 2024 companies are generative AI-native, meaning that the companies' origins are rooted in generative AI technology. Further, an additional 13% of ET30 2024 companies are generative AI-launch, meaning that the companies have recently launched significant generative AI features or products. By comparison, 3% of ET30 companies in 2021 were generative AI.
Product-led growth remains prominent in the Enterprise Tech 30. This year, 75% (30 of 40) of ET30 companies employ a significant product-led growth model, as compared to 63% of ET30 companies in 2019.
Early stage companies continue to ascend to the Enterprise Tech 30 rapidly. This year, the median time since founding for early stage companies was 1.8 years, as compared to 2.3 years for last year's early stage cohort and 5.0 years for the 2019 early stage cohort. The pace of ascension is due to both the venture capital financing market and the tech movement in generative AI.
This year, mid and late stage companies saw decreases in last deal sizes and last valuations, while early stage companies saw increases. The median last deal size for mid stage and late stage companies this year decreased to $33 million and $152 million, respectively, from last year's companies. Meanwhile, the early stage companies' median last deal size increased to $18 million.
The median last deal valuation for mid stage and late stage companies this year decreased to $406 million and $4.4 billion, respectively, from last year's companies. The early stage companies' median last deal valuation increased to $66 million.
Late stage companies have also raised capital less frequently than in previous years. Many still have significant cash from the 2020-2022 venture capital markets. This year, the median time since last deal for late stage companies increased to 2.0 years, as compared to 1.3 for last year's late stage companies.
This year, nearly half of ET30 2024 founders (52 of 114) previously worked at Google, Meta, Microsoft, and OpenAI, often in AI research positions. 29% (33 of 114) worked previously at Google. 11% (13 of 114) worked previously at Meta and Microsoft. 6% (7 of 114) worked previously at OpenAI.
In 2024, 43% (17 of 40) of the companies are new to the Enterprise Tech 30, driven by AI and data. 7 of the 17 new companies are in AI models and tools, and 3 are in data platforms, ETL and BI. 4 are in SaaS.
ET30 continues to reflect startup innovation at the early and mid stages. 7 of the 10 early stage companies and 6 of the 10 mid stage companies this year are new.
Two of this year's Enterprise Tech 30 returned in a later stage than their initial appearance. As discussed in previous reports, each subsequent stage is more difficult to stand out in, so the return of these companies is a notable achievement. Linear: returned to mid in 2024 from early in 2021-2023. Abnormal: returned to late in 2024 from mid in 2021-2022.
For more information on the research methodology, additional insights, and to view the results, visit: enterprisetech30.com.
About Wing Venture Capital
Founded in 2013, Wing works with ambitious founders to enable the AI-first transformation of business. We invest early, before it's obvious, leading Seed and Series A financings and engaging deeply with our signature company-building skills and resources. The current Wing portfolio includes some of today's most important enterprise technology companies such as Snowflake, Cohesity, Pinecone, and Gong. For more information, visit: www.wing.vc
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