Lomin Supports Woori Bank with Document AI and Launches SaaS Based on Its Integrated Platform

Lomin is supporting Woori Bank's AX (AI transformation) with Document AI technologies such as optical character recognition (OCR) and parsing. According to the industry on May 17, Lomin is participating in Woori Bank's AI agent development project through the Samsung SDS consortium. Samsung SDS was named the preferred bidder for Woori Bank's "AI Agent Banking" project, which involves building more than 175 AI agents, and went on to win the contract.
Lomin will refine data and help build datasets that AI can learn from, using its own Document AI core technology, which recognizes and preprocesses not only the text in Woori Bank's extensive documents but also tables, charts, and forms.
Lomin plans to build on this reference to win more projects in the financial and public sectors. During vendor selection for Woori Bank's AX project, Lomin proved its competitiveness by being chosen as the Document AI partner by three consortia: Samsung SDS and two other major IT services companies.
Lomin recently launched Lomin, a Document AI Agent platform that brings together Document AI capabilities previously offered as separate solutions, including OCR, personal data de-identification, document parsing, and contract comparison and verification. The capabilities were combined into a single platform for service efficiency and scalability.
Lomin has significantly strengthened the platform's agent capabilities so that, beyond document automation, it can connect with core enterprise systems such as enterprise resource planning (ERP) and customer relationship management (CRM) to check data in real time and organize and complete documents.
In particular, Lomin recently shifted its core AI engine from a large language model (LLM) focus to a vision language model (VLM) that can read visual information such as charts, making it possible to classify documents and extract data with the base model alone, without extensive training. The company also plans to strengthen data labeling so that anyone can train models easily.