Datasea Intelligent Technology Ltd (DTSS) Fair Value & Analysis
Technology · US · Market cap $7.9M
Fair value as of: Jun 24, 2026
Analysis
Datasea Intelligent Technology Ltd (DTSS) currently trades at $0.7900, while our model-based Fair Value estimate is $1.37 — implying the stock looks roughly 73.4% 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: low) — always confirm before acting.
About the company
Datasea Intelligent Technology Ltd., together with its subsidiaries, provides advanced acoustic products and solutions to businesses and individual users worldwide. It operates through Acoustic High-Tech and AI Multimodal Digitalization segment. The company offers smart city solutions for residential communities, schools, and commercial enterprises; and 5G messaging services, including 5G SMS, 5G MMCP, and 5G multi-media video messaging. It also provides its smart security solutions primarily to schools, tourist or scenic attractions, and public communities. In addition, the company offers acoustics health products, which include ultrasonic air sterilizers, ultrasonic cleaning devices, non-contact sleep aid devices, and medical beauty devices; ultrasonic disinfectors and purifiers for restrooms, bedrooms, living rooms, kitchens, and pets; and non-contact ultrasonic skin repair devices. Further, it provides digital rural, new media marketing, and AI multimodal services for small 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.