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SIJE is a company specializing in the digital transformation of the apparel supply chain. SIJE offers the software-as-a-service (SaaS) 'Monolis' for apparel sourcing and production management, and the Internet of Things (IoT)-based real-time productivity monitoring solution 'Monolog.' Through these, it supports the digital transformation of the entire apparel production process.

Over the past two years, SIJE has conducted proof of concept (PoC) with 12 factories in Vietnam and major Korean apparel companies, achieving an average productivity improvement of over 20%. Based on this, it has signed contracts with several apparel companies and secured actual implementation cases. In November last year, it established a branch in Hanoi, Vietnam, and plans to expand to Indonesia and the United States in the first half of next year.

An interview was conducted with Shin In-jun, CEO of SIJE, to discuss SIJE, Monolis, and Monolog.


Founded to Solve Problems Discovered in the Apparel Industry

IT Donga: Hello, CEO Shin In-jun. Please introduce yourself.

CEO Shin In-jun: Hello, I am Shin In-jun of SIJE. After graduating from Hanyang University's Department of Clothing and Textiles, I worked for five years as an industrial engineering researcher at Jiji Trading. During that time, I oversaw smart factory system projects in Vietnam and Indonesia and served as the head of the Process Analysis Center (PAC).

The Process Analysis Center analyzes and researches the optimal production processes for apparel production. Whenever designs or fabrics change, it studies the optimal production processes and calculates production costs or manufacturing costs by computing work time, workforce, and input costs. It connects office work with production factories. As the head of the Process Analysis Center, I was able to broadly observe phenomena occurring in the apparel supply chain, and I founded SIJE to improve the problems I discovered in the apparel industry during that process.

IT Donga: What were the problems you discovered at that time?

CEO Shin In-jun: There are mainly two issues. The first is the problem of industrial structure. During the COVID-19 pandemic, many industries faced difficulties, including the apparel trade industry. Our company was also directly hit by a sharp decline in order quantities. Observing these phenomena, I discovered the problems in the industrial structure.

The existing apparel industry reduces apparel costs through production in low-wage countries, but it faces significant difficulties when external factors such as the COVID-19 pandemic or tariff policies occur. Experiencing such difficulties firsthand, I thought that digitally transforming the supply chain system flowing from developed countries to developing countries could solve the issue of apparel manufacturing costs.

The second issue is the absence of a quantitative production management system. Apparel production factories have multiple lines, and the process times of each line must be uniform to efficiently match production volumes. However, due to the labor-intensive nature of the industry, it was challenging to apply a quantitative production management system. Therefore, while conducting a smart factory system project, I created a device that measures workers' production volumes in real-time. I realized that by adding technologies such as big data, it would be possible to quantify production processes and secure clear evaluation criteria. However, at that time, the company was focused on apparel manufacturing and trade as its main business, so it was reluctant to invest in IT technology.

While pondering these issues, I saw acquaintances realizing their dreams and achieving excellent results through startup ventures, which led me to decide to start my own business.


Digital Transformation of Apparel Production Processes, Monolis and Monolog

IT Donga: Please introduce SIJE. What kind of company is it?

CEO Shin In-jun: SIJE is a company focused on the digital transformation of the apparel supply chain. Under the vision of 'making the apparel industry a core industry of the future,' we provide the data-driven supply chain management solutions Monolis and Monolog, which digitally transform the entire process of apparel manufacturing, processing, and shipping. The company name 'SIJE' encompasses the past, present, and future, meaning 'creating the future by improving the present based on the legacy of the past.'

IT Donga: Please introduce Monolis and Monolog, the core solutions of SIJE.

CEO Shin In-jun: Let me start with Monolis. Monolis is a SaaS solution for apparel sourcing and production management. It contributes to reducing office work and unnecessary costs by digitally transforming the global outsourcing-based apparel supply chain system.

The feature of Monolis is its mapping technology. Typically, when a company requests apparel production, it provides documents such as work orders, purchase orders (PO), bill of materials (BOM), and technical packages (TP). These documents contain about 1800 to 2000 items that must be adhered to during apparel production. Depending on size, color, pattern, and design, the number of items can increase. We created a map of these items based on their interrelationships and work paths. It's a map that allows you to see the entire process from work orders to shipping at a glance. Due to the complexity of the industrial structure, it took three years to create the map.

By simply uploading documents like work orders to Monolis, all the information needed for apparel production is automatically placed where needed and processed according to the workflow. As a result, office work can be reduced by about 65%. The person in charge only needs to decide whether to proceed to the next stage without writing reports. It is easy to understand why a specific task is necessary, what the next task is, and data errors can be immediately identified.

The mapping technology of Monolis can be applied to various industries beyond apparel. Therefore, we are considering expanding into other industries with a primary and subcontractor industrial structure, and we are actually discussing the possibility of adoption with companies related to shoes and bags.


Monolog is an execution management solution that monitors real-time productivity with IoT devices and provides statistical analysis. In the case of apparel production, it is a labor-intensive industry, making productivity visualization challenging, but we have realized it through big data technology.

In addition to measuring production quantity and work time, it suggests optimal management plans based on this data. It sets optimal production times or suggests appropriate processes considering the capabilities of the workers. Monolog contributes to increasing factory productivity by over 15%, thereby boosting sales.

IT Donga: I heard that you are also preparing SIJEOS (tentative name) in addition to Monolis and Monolog. What kind of solution is SIJEOS?

CEO Shin In-jun: SIJEOS is an integrated artificial intelligence (AI) agent for apparel supply chain data based on the data operation infrastructure of Monolis and Monolog. It provides functions such as production planning and sourcing, order automation, and production simulation. It can also predict production, allowing for early detection and preemptive response to potential bottlenecks. If a report is needed, it can be easily processed using an AI chatbot.

SIJEOS was developed for customers who want to use only some of our solution's functions. By linking it to the system the customer is using, it is being developed to utilize the core values of Monolog, such as data statistics and analysis, and data mapping. SIJEOS is scheduled to be introduced in the first half of 2026.


Technology Verification Through Collaboration with Vietnamese Factories and Major Korean Apparel Companies

IT Donga: Please tell us about the current progress of your business.

CEO Shin In-jun: We have conducted PoC in 12 factories in Vietnam over the past two years. Through this, we have improved factory productivity by an average of over 20%. In 2024, we also performed PoC with major Korean apparel companies, achieving significant results. Based on this, we have signed contracts with various apparel companies and applied our solutions.

In November last year, we established a branch in Hanoi, Vietnam, and plan to establish branches in Indonesia and the United States in the first half of next year. Through this, we plan to fully enter Asia, including Indonesia, Bangladesh, and India, from next year, and meet the demand of fashion companies in the United States.

IT Donga: You are currently receiving support from the SeoulTech Global Enterprise Collaboration Program. What kind of support have you received?

CEO Shin In-jun: We are participating in the Amazon Web Services (AWS) Jungle Program. Through this program, we received AWS credits and visited the AWS headquarters in the United States last May to receive training on solution building and B2B business strategies. We gained information about the U.S. market and confirmed the possibility of market entry. We were also able to network with startup representatives with similar business models. We are receiving a lot of help in various aspects.


IT Donga: Lastly, please tell us about your future plans and goals.

CEO Shin In-jun: First, we plan to continuously enhance our solutions and add new features. We are also preparing a function to automatically create apparel production work orders. Along with this, we plan to expand our business area to global markets such as the United States to secure a diverse customer base.

We are also conducting a Series A funding round. Through this, we aim to accelerate the advancement of our AI model and the development of SIJEOS. For reference, we completed a pre-Series A funding of KRW 2 billion in May last year.

Our goal is to build a SaaS model that integrates the outsourcing industry across multiple countries. By expanding beyond apparel to various industries such as manufacturing, we aim to create an industrial environment that does not rely on workers.

IT Donga Reporter Han Man-hyuk (mh@itdonga.com)

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