[For more diverse company information on the startups mentioned in this article, visit Unicorn Factory's big data platform 'Data Lab'.]
As investment enthusiasm for AI (artificial intelligence) continues in the venture capital market, vertical AI, which focuses on solving problems in specific industries rather than general-purpose AI, is emerging as a key investment target for venture capital. This trend is attributed to growing expectations that vertical AI can quickly demonstrate profitability at industrial sites, unlike general-purpose AI, which requires massive capital.
This trend is also confirmed in the global investment market. Global venture capital firm Bessemer Venture Partners forecasts that the market size of specialized vertical AI will reach 10 times that of the existing SaaS (software-as-a-service) market. These expectations are also reflected in corporate valuations. In late last year, U.S. legal tech startup Harvey was recognized with a corporate valuation of $8 billion (approximately 11.4 billion won). Domestically, startups are increasingly securing large-scale investments or preparing for listings by leveraging domain data as their weapon.
From video search to editing with AI, 150 billion won in funding
One of the vertical AI companies recently highlighted by venture capital is Twelve Labs. The company develops multimodal AI technology that understands the context of video data to perform search, analysis, and reasoning. In its recently concluded Series B investment round, it secured 150 billion won, achieving cumulative investments of $200 million (approximately 308.7 billion won). Participants in this round included Naver Ventures, U.S. venture capital firm NEA, Amazon's venture investment organization, Radical Ventures, Index Ventures, Quadrille Capital, and Red Bull Ventures. In Korea, Korea Investment Partners was listed as an investor.
Twelve Labs is a startup founded by Lee Jae-seong (CEO), a former officer from the Republic of Korea Army Cyber Operations Command, in March 2021. Headquartered in San Francisco, the company targets the global market. It has expanded its business by securing global enterprise clients with large-scale video data, including broadcasting and media companies as well as NFL organizations. Its competitive edge lies in accumulating relevant domain data by leveraging video understanding AI technology that connects visual and audio information within videos to natural language while comprehending context.
Equipped with its own developed video-native foundation models 'Marengo' and 'Pegasus', the company possesses technology for recognizing, searching, analyzing, and reasoning about videos. Unlike general-purpose multimodal AI, it is evaluated for its strength in precisely understanding the context and temporal flow of video data.
MachinaLabs diving into manufacturing and defense, successful entry into KOSDAQ
Vertical AI company MachinaLabs, targeting the manufacturing and defense sectors, successfully listed on KOSDAQ in May this year based on improved performance. Revenue grew from 49.1 billion won in 2023 to 82.9 billion won in 2024, and is projected to reach 11.4 billion won in 2025. Over the same period, operating losses decreased from 11.2 billion won to around 8 billion won, indicating improved profitability.
MachinaLabs lowered barriers to AI adoption at manufacturing sites by leveraging its platform 'Runway', which enables AI development, deployment, and operation even in closed network (air-gapped) environments disconnected from external networks. It operates over 6,000 AI models across 12 industries where security and precision are critical, including automotive, semiconductors, secondary batteries, and defense, accumulating more than 25 terabytes of industry-specific data.
An industry expert stated, "Industrial sites such as manufacturing and defense are areas where AI adoption is extremely difficult due to concerns about information leaks, security issues, and data fragmentation." They added, "To achieve successful AX (AI transformation), it is essential to build dedicated data infrastructure that can secure and analyze high-quality domain data while maintaining security."
Elbox builds exclusive data… First IPO challenge in legal tech
The legal field is a representative data-intensive area where precedents, annotations, and official interpretations are intricately intertwined. Applying general-purpose AI directly has limitations due to hallucination phenomena where non-existent laws or precedents are fabricated.
Legal tech startup Elbox solved this problem based on its domestic high- and low-court judgment document database (DB). Developing agentic AI that actively performs legal tasks beyond precedent search based on judgment documents, it supplies solutions to major law firms, large corporations, and government institutional investors. Currently, it has secured over 16,000 clients including the top 10 domestic law firms, judicial institutional investors, and major companies, along with more than 15,000 registered lawyers. Based on these achievements, it secured a Series C investment of 30 billion won last year. Recently, it has begun preparing for an initial public offering (IPO) by selecting its lead underwriter.
An industry expert remarked, "While general-purpose AI models can be quickly replaced when superior competing models emerge, vertical AI that organically integrates specialized knowledge and data from industrial sites is difficult to replace easily." They concluded, "Companies that first secure core data for each industry and build solutions will lead long-term AX initiatives."
[MoneyToday startup media platform Unicorn Factory]
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