Rapolabs, which operates the 4050 lifestyle platform “Queenit,” recently launched the AX (AI Transformation) team and is focusing on applying AI-centered ways of working across the entire company. Rather than concentrating solely on AI technology development, the Rapolabs AX team positions itself as a company-wide innovation leader that helps all members naturally use AI in their daily work. ITDonga spoke with Rapolabs AX Team Engineer Choi Bong-su about the background behind the AX team’s launch and the organizational changes that followed.

From building an in-house AI platform to automating HR, sales, and marketing… accelerating AI-based work transformation

Since launching the AX team in September, Rapolabs has been accelerating AI-based work transformation, ranging from building an in-house AI platform to automating HR, sales, and marketing.

Engineer Choi Bong-su said, “AX’s role is not only to build internal AI services and develop convenience features, but also to support even non-developer roles so they can independently create AI tools, bots, and automation systems through company-wide training. Rather than focusing on making AI work instead of employees, we help practitioners redesign their own ways of working around AI,” adding, “We underpin company-wide innovation by applying AI across the organization and enabling members to actively leverage AI.”

Rapolabs had previously pushed for AI adoption and utilization, but the process was not easy.

Choi explained, “We had already recognized the need to use AI at the organizational level, but new AI tools appeared constantly, making adoption criteria ambiguous. Some members also struggled with configuration tasks requiring development knowledge, such as MCP (Model Context Protocol), which made adoption difficult,” and continued, “In response, AX made lowering the entry barrier to AI its first priority. To instill the perception that AI is not difficult, we presented easy and fun application examples, and for MCP configuration—an area where many struggled—we even developed and distributed a program that automatically sets it up. We also sat next to team members and demonstrated real examples of automating simple, repetitive tasks with AI.”

The AX team focused on ensuring that members could directly use AI and experience improvements in work efficiency. This approach led to achievements such as ▲ developing an HR automation system that reduced tasks previously requiring half a day to just three minutes ▲ building an internal AI platform that anyone can use without configuration ▲ creating a sales collaboration web app by a non-developer ▲ applying a Kakao campaign automation bot.

Choi said, “As the AX team and each Rapolabs unit coordinated and applied AI to their work, various innovation cases emerged. For example, the HR team had personnel information split between the HR management platform and internal ledger sheets, which forced staff to manually enter personnel data and download work logs every month. As new hires increased, the time required for related tasks grew exponentially,” and continued, “To address this inconvenience, the AX and HR teams fully automated the connection between the HR management platform and internal ledger sheets via API integration. As a result, work log review time was reduced from half a day to under three minutes, and more than 1,000 data entries can now be processed at the same speed.”

He added, “We also built an in-house AI platform that anyone can use without configuration. Previously, using internal data with AI services required complex MCP setup and installation procedures. Frequent errors occurred because each member’s work environment was different,” and continued, “To solve these issues, the AX team reflected member feedback and deployed an in-house AI web service based on the open-source LibreChat. Now, anyone can use AI immediately by simply opening a browser, with no separate installation or configuration. It automatically connects to the in-house MCP server, and prompts or agents can be easily created and shared internally.”

Non-developers are building apps to improve work efficiency

As a culture of actively using AI took root within the organization, cases emerged in which non-majors created and used apps to improve work efficiency.

Choi said, “The AX team organized an internal training system to create an environment where all members can naturally use AI. As we conducted various training and hands-on sessions, AI utilization rates steadily increased, and now several operational teams have reached the stage where they develop automation systems, bots, and service web apps on their own,” adding, “A representative case is the sales collaboration solution of the advertising business team. As the number of advertisers recently surged, the team was considering adopting an external paid tool, but a non-developer in the advertising business team independently used Claude, spreadsheets, and App Script to create a customized sales web app. This app is meaningful not only for cost savings, but also because it is a ‘field-oriented solution’ optimized for the team’s actual workflow. The entire team is currently using the tool for tasks such as reminders, contact records, and data management, and there are plans to expand it into an AI sales agent with features such as automatic lead generation and message creation.”

He continued, “The Performance Team developed a Kakao campaign automation bot. Thanks to this, the repetitive task of scheduling re-live dates after Kakao advertising campaigns end has been fully automated,” adding, “Campaigns can now be managed with a single tap from mobile devices, even without a PC, enabling a ‘24-hour operation system’ and significantly reducing the operational burden on staff.”

Aiming to build an AI-native operating system… “AI will not be the exclusive domain of a specific team but a shared core competency”

The AX team pointed to two key priorities in its efforts to expand AI adoption across Rapolabs. The first is to establish an AI utilization culture more broadly and deeply throughout the organization, and the second is to secure scalability and stability of internal systems in line with the rapidly changing AI environment.

Choi said, “To achieve these goals, the AX team is pursuing several strategies in parallel. We are continuously strengthening internal training programs, such as ▲ AI Newcomer sessions to help new hires quickly adapt to the technology ▲ App Script sessions that enable anyone to build dashboards and Slack bots ▲ sessions for setting up integrated development environments (IDEs) to use AI effectively in coding tasks. We are also providing hands-on support, such as templates tailored to each team’s objectives and work structure, so that members can naturally utilize AI,” adding, “We are also advancing the in-house AI platform to ensure that anyone can use AI in a fast and stable environment, thereby improving infrastructure quality. Elevating both the technological foundation and organizational culture in tandem to accelerate company-wide AX adoption is the AX team’s core strategy.”

He continued, “Going forward, the Rapolabs AX team aims to build an ‘AI-native operating system’ so that even small, high-density organizations can achieve high productivity and rapid execution, based on the results achieved so far. To this end, each department will not merely use AI, but will enhance its capabilities to independently define problems and design AI-based solutions. The goal is to establish AI as a shared, basic capability across the company, rather than the exclusive domain of a specific team,” adding, “Until now, the focus has been on individual automation cases, but going forward, we plan to connect the core workflows of all departments—such as sales, marketing, CS, and product operations—into a real-time automation system to boost overall productivity. We will support each team with systematic training and assistance so they can design and implement new AI-based ways of working.”

ITDonga reporter Kim Dong-jin (kdj@itdonga.com)

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