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Strata Critical Medical, Inc (SRTA) Fair Value & Analysis

Healthcare · US · Market cap $491M

Price$5.57
Fair Value$0.9200
Upside-83.5%
Quality95/100
Evidence: Low Range $0.6100 – $1.15

Analysis

Strata Critical Medical, Inc (SRTA) currently trades at $5.57, while our model-based Fair Value estimate is $0.9200 — implying the stock looks roughly 83.5% overvalued today. We read business quality at 95/100 (high quality), in the Healthcare 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

Strata Critical Medical, Inc. provides time-critical logistics and medical services to the healthcare industry in the United States. It operates in two segments, Logistics and Clinical. The company offers logistics services, such as air and ground transportation for human organs, transplant teams, and related medical materials and organ placement services; transplant clinical services, including organ recovery procedures, normothermic regional perfusion, and preservation services. It also provides other clinical services comprising cardiac perfusion services, blood management and autotransfusion services, extracorporeal membrane oxygenation services, perfusion staffing, and equipment rentals. The company was formerly known as Blade Air Mobility, Inc. and changed its name to Strata Critical Medical, Inc. in August 2025. The company was founded in 2014 and is headquartered in New York, New York.

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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.