Tuya Inc (TUYA) Fair Value & Analysis
Technology · US · Market cap $1.1B
Fair value as of: Jun 24, 2026
Analysis
Tuya Inc (TUYA) currently trades at $1.84, while our model-based Fair Value estimate is $1.79 — implying the stock looks roughly 2.7% 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: high).
About the company
Tuya Inc. provides artificial intelligence (AI) cloud platform services in the People's Republic of China. Its AI cloud developer platform delivers a suite of offerings, including platform-as-a-service (PaaS), software-as-a-service (SaaS), and smart solutions to developers of smart device, commercial applications, and industries. The company's PaaS offering enables original equipment manufacturers and brands, and developers to develop, launch, manage, and monetize software-enabled smart devices and services. Its SaaS offering enables businesses to deploy, connect, and manage smart devices in various vertical scenarios for spatial intelligence and cloud-based software value-added services to build their own autonomous and controllable smart business platforms. Its solutions include cube private cloud, smart hospitality, smart residential, commercial lighting, and smart house and real estate. The company also offers a range of other cloud-based value-added services to enhance their ab…
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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.