Beryl 8 Plus Public Company (BE8) Fair Value & Analysis
Technology · TH · Market cap 1.5B THB
Fair value as of: Jun 24, 2026
Analysis
Beryl 8 Plus Public Company (BE8) currently trades at 5.40 THB, while our model-based Fair Value estimate is 7.18 THB — implying the stock looks roughly 33.0% 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
Beryl 8 Plus Public Company Limited operates as a digital technology consulting company in Thailand. It operates through Strategy and Technology Consulting, and Technology Support Services segments. The company offers CRM, analytics, and digital technology solutions with specialization in customer relationship management (CRM) systems with Salesforce. It is also involved in consultation on telecommunication, branding and digital marketing, and computer and other information, as well as penetration testing for web applications, mobile applications, and network systems; design and installation software to support CRM; accounting, financial, legal, human resource, and procurement services; sales of subscription; and integrated system service management after installation. In addition, the company sells computer hardware and software and related equipment, including network communication equipment and software; engages in the development of enterprise software and project management; an…
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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.