Sidus Space, Inc (SIDU) Fair Value & Analysis
Industrials · US · Market cap $293M
Fair value as of: Jun 24, 2026
Analysis
Sidus Space, Inc (SIDU) currently trades at $2.94, while our model-based Fair Value estimate is $2.34 — implying the stock looks roughly 20.4% overvalued today. We read business quality at 95/100 (high quality), in the Industrials 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: low).
About the company
Sidus Space, Inc. engages in the design, manufacture, launch, and data collection of commercial satellites worldwide. The company offers Fortis, a VPX module used for computing, machine learning, GPS navigation, and near real-time data analytic; LizzieSat Satellite Platform, a modular, hybrid 3D-printed satellite architecture designed to support multi-mission deployments across LEO, GEO, cislunar, and lunar orbits; Orlaith AI Ecosystem by integrating the FeatherEdge radiation-tolerant edge processor with the Cielo AI software suite; and end-to-end mission operations services, including mission planning, payload integration, satellite monitoring and control, and data delivery. It also provides operates a vertically integrated manufacturing and engineering facility supporting precision machining, additive manufacturing, avionics and assembly, cable harness fabrication, and environmental testing. It serves commercial space, aerospace, government, intelligence customers, and defense ind…
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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.