I2 Enterprise Public Company (I2) Fair Value & Analysis
Technology · TH · Market cap 328M THB
Fair value as of: Jun 24, 2026
Analysis
I2 Enterprise Public Company (I2) currently trades at 0.7600 THB, while our model-based Fair Value estimate is 0.8900 THB — implying the stock looks roughly 17.1% 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
I2 Enterprise Public Company Limited, a system integrator, provides information and communications technology solutions for government agencies, state enterprises, and private sectors in Thailand. The company offers digital transformation solutions comprising enterprise content management, big data solutions, electronic workflow management systems, and enterprise performance management. It also provides energy saving and management solutions; internet and satellite service solutions; Endpoint Detection and Response, reduces the risk of data breaches and damage to organization systems; Identity Access Management, a tool for managing authentication and access organizational resources; and Secure Service Edge, a cloud native platform for centralized security. In addition, the company offers advisory, installation, design, and distribution of equipment related to IT Infrastructure systems consisting of servers, and HCI systems design and installation services; network system design and …
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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.