[AI Revolution](132) Wello Addresses Policy Blind Spots with AI

Accurate Policy Information Matching Through AI
From Policy Data Analysis to Sophisticated User Curation Implemented by AI

Policy information that can benefit the public is scattered everywhere. For example, if someone wants to receive startup-related support, they must check support programs spread across central government agencies, local governments, associations, and foundations, and apply according to the specific requirements and timeframes. As a result, it is easy to miss out on available support. Wello is a startup that aims to solve this mismatch between policy information and eligible recipients using artificial intelligence (AI) technology.

On December 1, Anna Kim Yuri, CEO of Wello, stated, "Our goal is to maximize the potential of public services and policies through AI- and data tech-driven solutions, ultimately contributing to the improvement of people’s quality of life." Founded by Kim in 2021, Wello is a Gov-Tech company based on AI. Gov-Tech refers to technologies that utilize public data to innovate citizen services and address current issues or social problems. Through its data solutions, Wello provides a platform for policy promotion, offering guidance on policies in areas such as welfare, housing, transportation, employment, and startups. It also connects individuals and businesses with policies optimized for their life cycles. To achieve this, Wello automatically collects and analyzes more than 10,000 policy data updates daily from over 2,700 sources, including 46 central government agencies, 593 local governments, public interest foundations, and private social contribution organizations nationwide.

Anna Kim Yuri, CEO of Wello

Wello’s solutions include “Wello,” an AI-based personalized policy recommendation service, and “Wellobiz,” a digital transformation (DX) software-as-a-service (SaaS) for corporate policy project management. Kim explained, "We are focusing on building a Gov-Tech market that encompasses not only B2C, but also B2B and B2G," adding, "We are presenting a variety of policy experiences under the vision of expanding tangible benefits."

First, the individual-oriented Wello leverages AI technology from the data accumulation stage. It begins by using natural language processing (NLP) to clearly classify and collect policy data, which is recorded in various formats by each institution, such as Hangul files or website text. By modularizing the content, duration, and target of each policy, Wello enhances the usability and value of policy data. The matching function is also implemented with AI. Considering the information registered at sign-up, Wello filters and presents only personalized policies from its vast policy database to each user. Users can easily find the policies they need depending on their circumstances, such as housing, starting a business, or pregnancy.

Wellobiz supports the entire process of managing government support programs and procurement projects. It helps companies explore and receive recommendations for suitable policy programs, and enables them to manage the entire participation process-including application, selection, and management-through a single service. Currently, about 40,000 major projects from approximately 2,500 institutions are linked to the system. Based on this, AI supports companies in efficient procurement bidding and operations. The number of cumulative client companies has reached about 5,100. Kim introduced, "We can reduce the time required to search for public projects by up to 18 times compared to manual methods."

These solutions are also informed by Kim’s own experiences. While attending university, she researched big data and AI and participated in the “Seoul City Dream Tree Card Data Analysis Project.” At that time, Kim identified students in welfare blind spots through data analysis, and the results were reflected in actual policy improvements. This experience convinced her that AI and data tech can contribute to solving social problems. Kim emphasized, "Beyond simply expanding policy experiences, we plan to establish a public data business and complete a Korea-style standard model."