Fasoo Finalist in ‘Best AI Integration’ at 2025 A.I. Awards

Fasoo announced on the 23rd that it has been selected as a finalist in the “Best AI Integration” category of the 2025 A.I. Awards, a global artificial intelligence (AI) award.

The 2025 AI Awards are a separate award established last year by “The Cloud Awards,” which have been held since 2011. Finalists are selected through evaluations categorized by industry, including platforms, startups, finance, healthcare, and others. The AI Convergence category, in which Fasoo was selected as a finalist, evaluates integration capabilities between existing systems and AI. It includes global technology leaders such as Illumina, Ivanti, Gong, and WalkMe.

Fasoo was recognized for its AI governance and data curation capabilities provided by an AI environment combining its enterprise AI “Ellm” and AI document management platform “Wrapsody.” These two solutions, when interconnected, maintain access permissions and policies for data itself while providing all historical records, enabling maximized quality and efficient management of AI training data.

Elm is a secure and practical small large language model (sLLM) that is fine-tuned with internal data according to an organization’s characteristics and requirements and is built as an on-premises or private cloud solution. Its key feature is the ability to apply access permissions and policies set for each data based on Fasoo’s data management and security insights. This prevents critical data, such as personal information and intellectual property, from being used in AI training or 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 centrally manages them without duplication as a single document, even when stored in a distributed manner based on document virtualization technology. It minimizes ROT (redundant, obsolete, trivial) data that hinders AI training and utilization, allowing data to be managed optimally for AI training in terms of efficiency, cost-effectiveness, and security.

Son Jong-gon, Fasoo Executive Managing Director, stated, “Many organizations struggle to even begin due to a lack of in-house AI experience and resources, or they halt at the pilot stage and fail to apply AI to actual tasks.” He added, “Organizations must initially consider which tasks to apply AI to, how to prepare data, and how to minimize costs and side effects of AI utilization. This requires implementing agent AI that can be practically utilized through analysis and customized design tailored to specific tasks.”