Deep.Fine, a South Korean industrial AI platform company built on spatial AI technology, has closed a Series B round of KRW 10 billion, bringing its cumulative capital raised to about KRW 18 billion.
The round drew participation from Hyosung Ventures, POSCO Technology Investment, and a consortium of LIG Defense & Aerospace and IBK Capital. Investors cited DeepFine’s track record of solution deployments across multiple industrial sites, its technology for integrating with existing enterprise systems, and its platform architecture’s ability to scale across different industries as key reasons behind the investment.
Strategic investors with direct ties to DeepFine’s core industries — manufacturing, heavy industry, and defense — were a notable feature of this round, following earlier backing from the Korea Credit Guarantee Fund, IBK (Industrial Bank of Korea), Hyundai Motor Group, and LS Group.
Deep.Fine develops an industrial AI agent platform that combines smart glasses, vision AI, spatial computing, and on-site data analytics into a single system connecting the full arc of industrial fieldwork — from issuing work instructions to guiding task execution, verification, record-keeping, and analysis. The company’s technology is designed to digitize complex procedures on industrial worksites and use AI to support workers as they carry out their tasks, aiming to simultaneously improve productivity, accuracy, and safety for enterprise clients. DeepFine currently supplies its solutions to major Korean logistics companies, global manufacturers, and firms in shipbuilding, defense, and maintenance-repair-and-overhaul (MRO). The company has also been evolving its offering into an enterprise-grade SaaS platform that integrates with clients’ internal systems, including warehouse management systems (WMS), enterprise resource planning (ERP), and manufacturing execution systems (MES).
DeepFine said it will use the new capital to advance its industrial AI agent technology, expand its SaaS business into logistics and MRO, build industry-standard models based on its large enterprise client base, strengthen field-data-driven operational analytics, prepare for global market entry, and hire core R&D talent.
