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Saultech Technology Co (6812) Fair Value & Analysis

Industrials · TW · Market cap 2.1B TWD

Price69.20 TWD
Fair Value12.71 TWD
Upside-81.6%
Quality95/100
Evidence: High Range 12.35 TWD – 13.08 TWD

Fair value as of: Jun 24, 2026

Analysis

Saultech Technology Co (6812) currently trades at 69.20 TWD, while our model-based Fair Value estimate is 12.71 TWD — implying the stock looks roughly 81.6% overvalued today. We read business quality at 95/100 (high quality), in the Industrials 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

Saultech Technology Co., Ltd engages in the manufacture and sale of precision equipment in Taiwan. The company offers hybrid bonfing, fan out, mini LED display/backlight/ FOB, image sensor/re-con, AOI, multi-function pick and place, and customize products. Saultech Technology Co., Ltd is based in Zhubei, Taiwan.

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Frequently asked questions

Is Saultech Technology Co (6812) undervalued?
As of Jun 24, 2026, our model estimates a fair value of 12.71 TWD versus a price of 69.20 TWD — about −82% (overvalued). Model-based estimate, not financial advice.
What is the fair value of 6812?
Our 21-model fair value for Saultech Technology Co is 12.71 TWD (as of Jun 24, 2026), built from audited fundamentals. The current price is 69.20 TWD.
What is the quality score of 6812?
Saultech Technology Co has a Quality Score of 95/100, measuring profitability, growth and balance-sheet strength from non-valuation factors.

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.