Algorix Raises $11.5M Series A for AI Data Infrastructure

South Korean startup Algorix has successfully closed an $11.5 million Series A funding round, propelling its total capital raised to $14 million. The investment was spearheaded by K2 Investment Partners, with significant participation from new backers A Ventures and GU Equity Partners. Existing investors, including Quad Ventures, Kiwoom Investment, and We Ventures, also demonstrated continued confidence through follow-on investments, underscoring the company's promising trajectory since its pre-Series A funding in September 2024.

Founded in 2022 by computer science professor Minsoo Kim, Algorix is developing the Akasic platform, a comprehensive AI data infrastructure designed to address the complexities of enterprise data. The platform integrates fragmented data connectivity, collection, transformation, AI inference, and agentic AI execution. Its core innovation, AkasicDB, functions as an AI-native database engine, uniquely unifying graph, vector, and relational database functionalities within a single, cohesive system. This approach is critical in an era where enterprises grapple with increasingly diverse and siloed data sources, a challenge amplified by the rapid adoption of AI technologies across industries.

Algorix's technological prowess is validated by impressive performance benchmarks. Internal evaluations show AkasicDB achieving processing speeds up to 142 times faster than established graph databases in the LDBC SNB benchmark. Furthermore, it demonstrated over four times the query throughput of Milvus, a leading vector database, while maintaining equivalent accuracy levels. The company's proprietary hybrid RAG (Retrieval-Augmented Generation) technology, capable of executing graph, vector, and relational searches within a single query, has also shown remarkable results. Joint research with KAIST presented at the prestigious ACM SIGMOD 2026 conference revealed up to a 78 percent improvement in answer accuracy compared to conventional RAG methods, highlighting its potential to significantly enhance AI-driven decision-making.

The company's innovative solutions are already gaining traction with major clients across sensitive sectors such as defense, manufacturing, finance, and telecommunications. Notable clients include the Agency for Defense Development, Hanwha Ocean, Hyundai Motor Company, Hankook Tire, KB Securities, Kiwoom Securities, LG Uplus, and KT. Algorix's on-premise deployment model is particularly attractive for data-sensitive organizations, including those in defense and finance, where strict regulations limit external data transfers. This capability positions Algorix as a key enabler for secure AI adoption in highly regulated environments.

The newly acquired capital will be strategically deployed to further enhance the Akasic platform, accelerate the development of new product offerings slated for release in the latter half of the year, and fuel international market expansion. A significant portion will also be dedicated to bolstering the company's R&D talent pool. Algorix aims to convert its ongoing pilot projects into full-scale production contracts and establish a global footprint with field-proven technology, building on its early successes in diverse operational settings.

Hyeokryul Kwon, executive director at K2 Investment Partners, commented on the investment, noting the strategic importance of securing domestic core technology for national security innovation initiatives, often referred to as the 'K-Palantir' strategy. He emphasized Algorix's strong execution capabilities, evidenced by its foundational technology's validation in international academic forums and its successful pilot deployments across various industries and network environments. Minsoo Kim, CEO of Algorix, added that the company's focus on a hybrid RAG database engine stems from the belief that enterprise AI success hinges on data understanding and business context, rather than solely on models. This funding will enable Algorix to elevate the Akasic platform to global standards and set new benchmarks for AI data infrastructure, ensuring the autonomy and security of AI agents.