Winland Holdings (WELX) Fair Value & Analysis
Technology · US · Market cap $11.9M
Fair value as of: Jun 25, 2026
Analysis
Winland Holdings (WELX) currently trades at $2.35, while our model-based Fair Value estimate is $0.9800 — implying the stock looks roughly 58.3% overvalued today. We read business quality at 95/100 (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: medium).
About the company
Winland Holdings Corporation, through its subsidiaries, provides critical condition monitoring devices to the security industry. Its products are used to protect against loss of assets due to damage from water, excess humidity, extremes of temperature, and loss of power. The company offers EnviroAlert, which monitors temperature, humidity, and/or water presence in critical environments; TempAlert, a temperature monitoring device for residential and commercial environments through security systems; WaterBug, a water presence and leak detection system; and Power-Out Alert, a power outage detector. It also provides INSIGHT, an automated cloud-based platform that offers early alerting, reporting, and logging services designed to ensure regulatory compliance. The company offers its products through a network of distributors, dealers, security installers, and integrators for industries including health and medical, grocery and food services, and commercial and industrial, as well as agric…
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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.