[Customer Success Story] LFIT: Three Years of Public-Sector AI Data Projects, from Labeling to De-Identification

LFIT, a Korean systems integration and GIS company, used Superb Platform across public-sector AI training-data projects from 2023 through 2026, adapting its workflows for visible-light, thermal, high-resolution 4K, urban, waterfront, and mountainous imagery. After previously outsourcing labeling and de-identification separately, LFIT brought external annotators, automated initial labeling, review, communication, compliance records, and final submission into one platform, reducing rework, setup time, and duplicate privacy reviews. In its 2023 autonomous-driving dataset project, LFIT labeled 400,000 visible-light and 100,000 thermal images with object, keypoint, and caption data, while later projects reused established classes and guidelines and evaluated Superb AI’s ZERO vision model. The case study highlights Korea’s amended Personal Information Protection Act, which will take effect in March 2027 and permits limited use of original personal data for qualifying AI projects under strict review, while leaving de-identification as the standard approach for most projects. By integrating face detection and blurring into the labeling workflow, LFIT reported that annotators needed to review data only once and that the company could avoid the cost and delays of a separate de-identification service.

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