BeiJing Seeyon Internet Software Corp (688369) Fair Value & Analysis
Technology · CN · Market cap 2.6B CNY
Fair value as of: Jun 24, 2026
Analysis
BeiJing Seeyon Internet Software Corp (688369) currently trades at ¥21.90, while our model-based Fair Value estimate is ¥21.44 — implying the stock looks roughly 2.1% overvalued today. We read business quality at 94/100 (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: low).
About the company
BeiJing Seeyon Internet Software Corp. engages in the solutions, software products, and services in the collaborative management software and services industry in China. It offers A9, a cloud-native collaborative operation platform for large, group-type enterprises; A8, a collaborative operation platform for medium and large enterprises; information technology-driven office solutions; and A6 for the organizational management of small and medium-sized enterprises. The company also provides G6, an e-government collaborative management platform; CAP, a collaborative business customization platform; M3, an enterprise mobile collaboration management platform; big data analytics platform; CoMi, an AI intelligent agent product line; and collaborative human resources payroll and tax cloud. In addition, it offers state-owned assets operation and supervision platform; project, asset, contract, procurement, and expense control management solutions. The company was founded in 2002 and is headqu…
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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.