Fasoo said on the 23rd that it was named a finalist in the "best AI convergence" category of the global artificial intelligence (AI) awards, the "2025 AI Awards."
The 2025 AI Awards is a prize separately established last year by The Cloud Awards, which has been held since 2011. In addition to the AI convergence category, it evaluates entries by industry such as platforms, startups, finance, and healthcare, and selects the final shortlist. The AI convergence category, for which Fasoo was named a finalist, is judged based on the integration capabilities of existing systems and AI, and includes technology-leading companies around the world such as Illumina, Ivanti, Gong, and WalkMe.
Fasoo was selected as a finalist for the AI governance and data curation capabilities provided by an AI environment that combines the enterprise AI "Elm" and the AI document management platform "RhapsoDy." The two solutions are linked to maintain access permissions and policies inherent to the data while providing all histories, maximizing the quality of AI training data and enabling efficient management.
Elm is a safe and practical small large language model (sLLM) that is fine-tuned with internal data to fit an organization's characteristics and needs and is deployed on-premises or as a private cloud. Based on Fasoo's data management and security insights, it can apply access permissions and policies set for each dataset. This prevents important data such as personal information and intellectual property from being used for AI training or being inappropriately exposed through AI.
RhapsoDy, which maximizes the quality and availability of internal data for AI training, enables document assetization, version control, and file-level permission management. It encrypts all documents and, based on document virtualization technology, centrally manages them as a single document without duplication even when stored in a distributed manner. It minimizes ROT (redundant, obsolete, trivial) data that blocks AI training and use, and allows management as data optimized for AI training in terms of efficiency, cost-effectiveness, and security.
Executive Director Son Jong-gon of Fasoo said, "Many organizations cannot even get started due to a lack of in-house AI experience and resources, or they stop at the pilot stage and fail to apply it to actual work," and noted, "From the beginning, they must consider which tasks to apply it to, how to prepare the data, and how to minimize the cost and side effects of AI use. To that end, it is necessary to implement an agent AI that is practically usable through analysis and customized design tailored to the characteristics of the work."