SOPHiA GENETICS SA (SOPH) Fair Value & Analysis
Healthcare · US · Market cap $447M
Fair value as of: Jun 24, 2026
Analysis
SOPHiA GENETICS SA (SOPH) currently trades at $5.23, while our model-based Fair Value estimate is $2.53 — implying the stock looks roughly 51.6% 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
SOPHiA GENETICS SA operates as a cloud-native software technology company in the healthcare space. It offers SOPHiA DDM platform, a cloud-native software platform for analyzing data and generating insights from multimodal data sets and diagnostic modalities. Its SOPHiA DDM platform and related solutions, applications, products, and services are used by hospitals, laboratories, and biopharmaceutical companies through its own sales force as well as distributors and industry collaborators in Switzerland, France, Italy, rest of Europe, North America, the United States, Latin America, and the Asia-pacific. The company has a partnership with Synnovis to bring blood-based cancer testing to patients in the United Kingdom. The company was incorporated in 2011 and is based in Rolle, Switzerland.
Open the full interactive analysis →
Similar stocks
Frequently asked questions
Is SOPHiA GENETICS SA (SOPH) undervalued?
What is the fair value of SOPH?
What is the quality score of SOPH?
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.