Tatung System Technologies Inc (8099) Fair Value & Analysis
Technology · TW · Market cap 6.1B TWD
Fair value as of: Jun 24, 2026
Analysis
Tatung System Technologies Inc (8099) currently trades at 59.20 TWD, while our model-based Fair Value estimate is 50.52 TWD — implying the stock looks roughly 14.7% overvalued today. We read business quality at 95/100 (high quality), in the Technology sector. Bear case: priced above our estimate, the market already discounts strong expectations. Bull case: above-average quality can justify a premium — the entry price still matters most (evidence: high).
About the company
Tatung System Technologies Inc. engages in the design, research and development, and sale of computers, communication, network security, and other related software and hardware. The company offers TSTI OneAi solution, which integrates AI computing architecture, data management, AI agents, and manufacturing quality inspection assistants to allow enterprises to build AI agents; and the AIoT Smart Restroom, which provides a one-stop solution for restroom security and user experience management. It also provides ticc on cloud contact center; Helion CloudSystem Foundation, which provides private cloud infrastructure-as-a-service (IaaS) configuration and resource lifecycle management with OpenStack technology as the core; Helion CloudSystem Enterprise, which includes cloud service automation. In addition, the company offers TSTI AIoT smart toilet solution; TSTI ESG zero carbon integrated management system; IoT event triggering management platform; 5G transportation intelligent real-time m…
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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.