Senstar Technologies Corporation (SNT) Fair Value & Analysis
Industrials · US · Market cap $47.4M
Fair value as of: Jun 24, 2026
Analysis
Senstar Technologies Corporation (SNT) currently trades at $2.04, while our model-based Fair Value estimate is $2.25 — implying the stock looks roughly 10.3% undervalued today. We read business quality at 95/100 (high quality), in the Industrials 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: high) — always confirm before acting.
About the company
Senstar Technologies Corporation provides physical, video, and access control security products and solutions in North America, Europe, South and Latin America and internationally. It offers solutions for critical sites, including a portfolio of homegrown perimeter intrusion detection systems, and video and security management software with intelligent video analytics security solutions, as well as access control products and technologies. The company's solutions and products are optimized for perimeter, outdoor, and general security applications. Its portfolio of critical infrastructure protection and site protection technologies include various fence mounted sensors, fence mounted sensors, virtual fences and gates, buried and concealed detection systems, tunneling sensors, and sensors for sub-surface intrusion, such as to secure pipelines, as well as video analytics software and video management systems. Senstar Technologies Corporation was founded in 1981 and is based in Ottawa, …
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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.