2025년 May 19일 Use Cases

Building AI Training Data that Matches Complex Infographics with Text

Client A is,

One of Korea’s leading telecommunications companies, driving business innovation based on ICT convergence technologies such as AI, big data, and cloud. Recently, the company has been introducing AI company-wide to enhance operational efficiency.

Project Overview

To further improve efficiency, Client A wanted its AI systems to better understand, summarize, and analyze internal documents. As part of this effort, the company aimed to build large-scale AI training datasets. Specifically, through Crowdworks, they sought to construct a dataset of Korean-language infographics—hierarchical flowcharts, diagrams, and other graphic elements—meticulously labeled and matched with text.

This is a schematic image of the organizational structure of the Korean judiciary, with the Supreme Court at the top, followed by the Court Administration Office, the Judicial Training Institute, the Court Officials Education Institute, the Court Library, the High Court, and the Patent Court, and below the High Court are the District Courts, Family Courts, and Administrative Courts, with support and registry offices at the bottom.

Example images

The specific tasks of this project are as follows:

Collect Korean infographic image data using publicly available datasets without licensing issues
Collect images that have hierarchical structures and can express relationships between components
Process and match information about each component and node with information about inter-node relationships
Generate summary captioning that can describe the images

Why Client A Chose Crowdworks

End-to-end data services: From collection to processing, Crowdworks covers the entire workflow.
Quality assurance: A systematic validation system ensures high-quality data.
Expertise: Experienced professionals can design and execute even the most complex projects.

This was also our first time undertaking such a project—was it really possible?

Client A expected data quality that fully matched their high standards. Even for Crowdworks, with its years of industry-leading expertise in data labeling and AI dataset construction, this was a challenging project. The reasons were:

Collection of license-cleared data that meets the project’s specific conditions was required
They wanted high-difficulty data construction work that involves defining and connecting relationships between images (complex infographics) and text
Since Client A was also pursuing this as a new initiative with no similar experience, it was difficult to predict the project process or methods, and there were unclear standards and requirements

Project Solution Process

1) Designing the Data-Building Plan

We analyzed the requirements and sample data provided by Client A. Through this process, we identified areas where generative AI could be applied for automation. By combining our proprietary solutions with various open-source tools, we developed a customized data-building toolkit tailored to the client’s needs. The datasets were then categorized and managed by task difficulty, based on the number of nodes and connecting lines between objects.

A guided infographic explaining the process of the autonomous learning organization, including a step-by-step flow from open call → Planning and Evaluation Committee review → Chairman approval → Inauguration report → Operation → Final presentation, with explanations of each step and examples of key activities.

Step 1

A labeling task screen with multiple colored boxes overlaying an image of the Supreme Court organizational chart, with each organizational unit (e.g., Supreme Court, High Court, Support, etc.) color-coded, and a list of names and settings for each label on the right.

Step 2

A complex flowchart depicting the entire child abuse response system, with multiple labeled boxes overlaid on top of each other, visually organizing the response actors and processes from identification of a child in crisis to outreach to services to case management, with a list of labels on the right.

Step 3

2) Deploying Qualified Experts

We determined that this project required specialists with strong expertise and a deep understanding of data context. To that end, we assigned verified data specialists with knowledge of mathematical and logical structures, algorithmic frameworks, and the ability to create or interpret such structures. In addition, they were required to understand JSON and object-based data models. Before the project began, all workers underwent comprehensive guideline training and pre-tests to minimize risks that could affect quality.

3) Ongoing Review, Feedback, and Adjustments

Throughout the four-month project, we maintained regular communication with Client A, conducting periodic reviews of sample data and flexibly adjusting the workflow to reflect interim feedback. Since this was more than a simple image-labeling task, we implemented an integrated operational strategy that combined multiple tasks such as captioning, object mapping, and text transcription. Project managers collaborated closely with internal data engineers to map out the entire workflow and establish detailed guidelines, ensuring consistency and high quality across all deliverables.

“We want to work with Crowdworks again!”

At the beginning, Client A had significant concerns: the data structures were complex, and the tasks were entirely new territory, raising questions like, “Can this really work?” As the project progressed, however, Crowdworks built trust through fast and accurate communication, thorough requirement analysis, and flexible, tailored proposals. Client A was impressed with the project manager’s direction and operational strategy, and ultimately expressed strong satisfaction with the quality of the data delivered—so much so that they concluded, “We want to work with Crowdworks again on our next project.”

As AI technology advances and companies build increasingly diverse services, the need for high-quality, complex datasets continues to grow. If you ever encounter a project that seems almost impossible, Crowdworks is here to help. For us, it’s not just a challenge, but also an opportunity to provide the most efficient and effective solutions together with our clients.

Contact Crowdworks for Data-Building Inquiries