Corporate Knowledge Innovation: The Convergence of AI and Tacit Knowledge Munich, Germany-based AI startup Interloom has secured $16.5 million (approximately 23.1 billion KRW, 14.2 million EUR) in seed funding for its innovative technology that captures tacit knowledge within enterprises to enhance the capabilities of AI agents. The investment round was led by DN Capital, a prominent European venture capital firm, with participation from Bek Ventures and existing investor Air Street Capital. Interloom's technology differentiates itself from existing AI automation solutions by enabling AI to systematically learn from the tacit knowledge held by companies. Knowledge is not limited to tangible information that can be simply documented or stored in databases. Decades of accumulated experience, non-verbal communication, and know-how gained through repetitive tasks also constitute valuable assets. However, because this tacit knowledge is typically inherent in individuals, it is challenging for companies to manage it systematically. Interloom is gaining attention by introducing groundbreaking technology designed to address precisely these challenges. Interloom's core technology lies in capturing tacit knowledge from corporate operational data and applying it to AI agents. Specifically, Interloom analyzes not only documented data such as work instructions, customer service emails, and call records, but also the underlying context and patterns to generate a 'context graph.' This context graph captures undocumented tacit business knowledge and provides it as a reference for decision-making by AI agents and new employees. This technology supports the activities of AI agents and new employees based on a company's past success stories and decision-making patterns. In particular, it is regarded as having introduced a new layer of knowledge management by enabling the systematic management of tacit knowledge within enterprises. Fabian Jakobi, co-founder and CEO of Interloom, pointed out, "While AI agents are rapidly being deployed in frontline operations, they cannot provide answers or perform automated tasks without specific corporate memory." He explained, "By supporting AI agents' decision-making based on past successful resolutions and managing tasks through expert supervision, we create a permanent 'memory layer' of knowledge for the enterprise." The secured investment will be used to expand Interloom's engineering team and launch its first enterprise solution. Interloom expects this to significantly enhance the role and efficiency of AI agents. If AI can effectively learn and utilize the tacit knowledge held by companies, it can shorten the onboarding period for new employees, increase the accuracy of AI agents' decision-making, and prevent knowledge loss across the entire organization. Growth and Investment Trends in the European AI Startup Ecosystem The combination of AI agents and tacit knowledge represents a significant turning point not only for the present but also for the future of the enterprise automation market. This is regarded as a case where the potential of AI technology to effectively utilize tacit knowledge has been recognized, amidst the growing importance of AI's role in the enterprise automation market. Similar innovations are continuously emerging in the European AI startup ecosystem. The European startup ecosystem is seeing a steady inflow of capital into AI agents and enterprise AI infrastructure. Happyhotel, which developed an AI agent for hotel revenue management, secured €6.5 million in investment. Additionally, Equixly, focused on AI-based API security testing, raised €10 million, and Blockbrain, researching enterprise AI agents, recently announced a €17.5 million investment, accelerating the development of enterprise AI platforms. These developments demonstrate that AI technology is evolving beyond a mere automation tool to become a strategic partner for businesses. Conversely, discussions are also underway regarding the risks and limitations that AI adoption may entail. While AI is said to enhance operational efficiency by learning tacit knowledge, questions are also being raised about the accuracy and reliability of this process. Specifically, if the data AI learns from contains biases or is incomplete, there is always a possibility of it leading to incorrect decision-making. Furthermore, concerns about the potential replacement of existing jobs and issues of technology acceptance among employees cannot be overlooked. However, Interloom stated that it rigorously manages AI through expert supervision and collaboration to prevent it from learning in the wrong direction. CEO Jakobi emphasized task management through expert supervision, explaining that they are building a system where AI agents collaborate with human experts rather than operating autonomously. Such advancements in AI technology and increased investment also hold significant implications for the Korean market. Many Korean comp
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