Integrity Technology Group (688244) Fair Value & Analysis
Technology · CN · Market cap 2.4B CNY
Fair value as of: Jun 24, 2026
Analysis
Integrity Technology Group (688244) currently trades at ¥15.54, while our model-based Fair Value estimate is ¥19.31 — implying the stock looks roughly 24.3% 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: low) — always confirm before acting.
About the company
Integrity Technology Group Inc. engages research and development, production, and sale of information security software products in China. The company offers digital wind tunnel product systems; Yuanfang native security large model machine; spring and autumn cloud realm network targeting platform; spring and autumn cloud array new generation honeypot system; Chunqiu cloud security management platform; and spring and autumn cloud situation awareness platform. It also provides spring cloud shield industry customized products and services; spring and autumn cloud security series services; spring and autumn cloud talent cultivation systems; AI spring and autumn period model; digital security insurance products; and intelligent penetration and attack simulation system. The company was formerly known as Beijing Integrity Technology Co.,Ltd and changed its name to Integrity Technology Group Inc. in July 2023. Integrity Technology Group Inc. was founded in 2010 and is based in Beijing, China.
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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.