[Dongguk University Campus Town X IT Donga] Dongguk University has been participating in the Seoul Campus Town project since 2022, creating a startup ecosystem in the northwestern urban area. By supporting deep tech and cultural content startups, it has been selected as an excellent case of startup nurturing for two consecutive years and received an A+ grade in the 2024 Seoul Campus Town performance evaluation. IT Donga introduces promising startups developing alongside Dongguk University Campus Town.

According to the 'Current Status and Implications of Service Industry Data Utilization' report published by the Korea Economic and Industrial Research Institute in 2023, 73% of service industry companies wanted to use data to develop products and services, and 45.3% expressed an intention to purchase data. Many companies responded that there were no visible management performance results from using data, but 60.9% said it was helpful in customer management.

Meanwhile, 33.8% of responding service industry companies plan to expand their data utilization areas, but cited the lack of expertise and absence of data-related personnel as the biggest barriers to data utilization. Many service companies are willing to purchase and use data, but still struggle with how to create and organize it.

To Create Value with Data, a Circulating Ecosystem Must Be Established

Gartner's 2011 report 'How to Plan, Participate, and Prosper in the Data Economy' defines the data economy as an economy that creates industrial value by utilizing data. Fifteen years after the report's release, AI has emerged, leading to AI-based innovation in almost every industry, highlighting the importance of data value. However, for data to have industrial value, a circulating ecosystem that collects, stores, processes, and utilizes data must be established.


The Korea Economic and Industrial Research Institute explains that the data value chain ecosystem goes through a construction and opening process generated by sensors or people, is created in the form of public or private data, stored and distributed in the form of general information or personal information requiring security processes, and is analyzed and utilized for customized services or data-based decision-making after processing. This is a model suitable for Korea, where public big data is being built under government leadership while private sectors separately build AI datasets.

However, many companies face difficulties in the data collection process itself. The fact that 45.3% of domestic service companies expressed their intention to purchase data for product and service development is because it is difficult to build data directly and there is a lack of related personnel. However, there is already a lot of data within companies, existing only in an unorganized form.

The US Data Science Institute (USDSI) analyzed that 60% of data within companies is in an abandoned form. This abandoned portion includes documents, photos, videos, emails, and collaboration tool attachments stored in company clouds or personal computer folders. Such data remains unprocessed unless the company initiates data management, persisting in personal or team drives.

Even effectively processing only the documents among these can greatly aid companies lacking data. Necton's 'YuringPower,' released this month, is a company that provides a foundation for easily datafying remaining and abandoned data within companies, regardless of the field.

'YuringPower' Organizes Scattered Data Within Companies

Necton, a startup established in March this year, recently officially launched 'YuringPower,' a data construction and management solution for AI Transformation (AX).


YuringPower is essentially an intelligent document organization service utilizing AI. It identifies scattered or stored documents within the company, as well as documents related to certifications or regulations, based on AI technology. This includes data that is handwritten or in conditions not properly managed due to being in blind spots. Then, it classifies and organizes each document according to external regulations or internal standards, creating a management system. Furthermore, it automatically extracts data within each document to build a structured dataset that can be used by internal systems or AI models.


In terms of functionality, the core features are ▲ a document classification function that labels documents based on external regulations or internal standards ▲ 'data extraction,' which automatically processes various unstructured document types (such as transaction statements, quotes, contracts) according to necessary conditions like company name, amount, date, and person in charge. The biggest difference from other global company solutions is that it focuses on solutions for organizing dark data. Dark data refers to vast unorganized data that an organization collects and stores but does not analyze or use for other purposes.

Park Hyun-ji, CEO of Necton, stated, "In November, we will conduct education and support for the introduction of Software as a Service (SaaS). In the future, it will also be provided in a built-in form considering the security environment," adding, "The target for introduction is almost all fields. It's too heavy to do organization services with Enterprise Resource Planning (ERP), and the cost is enormous to computerize or build a separate program. In such a situation, the ability to add services with just SaaS and API (Application Programming Interface) is YuringPower's strength."

Institutional Support Follows Due to the Significant Benefits of Data Organization

Meanwhile, Dongguk University, which highly evaluated Necton's business potential, has been supporting its growth from the initial startup stage. Dongguk University provides diverse support based on a startup package, including ▲ office space provision ▲ administrative, labor, and personnel support ▲ regular mentoring ▲ networking days and contest connections.

CEO Park Hyun-ji explained, "Through Dongguk University's scale-up mentoring process, we were able to specifically review AI adoption cases by industry, SaaS expansion strategies, and overseas market entry strategies," adding, "In particular, we clearly organized the business structure and utilized it for investment pitching." The background for YuringPower's emergence included Dongguk University's generous support, laying the foundation for domestic technology companies to advance into larger markets in the long term.

Necton's Customers Include Companies Both Domestically and Internationally, Aiming for Overseas Markets

Necton's YuringPower targets almost all fields for data organization and processing, applying equally domestically and internationally. CEO Park Hyun-ji stated, "This year, the priority is to increase the satisfaction of companies introducing the service. We are currently continuously building networks with overseas markets such as Europe and the United States and plan to globalize the service in various ways."

Grand View Research predicts that the big data market size will reach USD 862.31 billion (approximately KRW 1,235.86 trillion) by 2030, with a growth rate of 14.9% annually. Even by organizing only the data accumulated in the company, data can be built without incurring significant additional costs. Due to the demand for lightweight and agile data organization solutions, Necton's YuringPower stands out, and its future performance is highly anticipated.

IT Donga Nam Si-hyun (sh@itdonga.com)

Popular News