WITHTECH Co (348350) Fair Value & Analysis
Technology · KR · Market cap 87.2B KRW
Fair value as of: Jun 24, 2026
Analysis
WITHTECH Co (348350) currently trades at 7,320 KRW, while our model-based Fair Value estimate is 8,149 KRW — implying the stock looks roughly 11.3% undervalued today. We read business quality at 95/100 (high quality), in the Technology sector. Bull case: trading below our estimate, it may offer upside if the fundamentals hold. Bear case: a low price can be a value trap when quality is weak or the data is thin (evidence: high) — always confirm before acting.
About the company
WITHTECH Co., LTD. provides solutions for manufacturing environment, and process pollution and management in materials and utilities in semiconductor and display industries in South Korea. It offers environment monitoring products, including ammonia, acid gas, total AMCs, ozone, TVOC, fast multi organic gas, and highly concentrated organic gas monitoring systems, as well as individual/multi-gas sensors and monitoring systems; utility monitoring products, such as metal and ion monitoring systems; process monitoring products comprising FOUP and wafer contamination monitoring systems, as well as FOUP cleaners; and industrial environment monitoring products, including emission gas and effluent monitoring systems. It also provides radionuclide separation and extraction products; and offers inorganic, organic, metal, and radionuclide analysis and consulting services. The company was founded in 2003 and is based in Daejeon, South Korea.
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How we calculate Fair Value
Each company is valued through a stack of independent intrinsic-value models (DCF variants, residual-income, multiples and more), blended into one family-balanced consensus and weighted by how much trustworthy data backs it. A separate quality layer scores the fundamentals. Every input is real reported data — nothing guessed.
Educational research only · not financial advice · no buy/sell recommendation. Model-based estimates are not certainties; their reliability depends on data quality and assumptions.