Knightscope, Inc (KSCP) Fair Value & Analysis
Industrials · US · Market cap $34.7M
Fair value as of: Jun 25, 2026
Analysis
Knightscope, Inc (KSCP) currently trades at $1.94, while our model-based Fair Value estimate is $0.7600 — implying the stock looks roughly 60.8% 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
Knightscope, Inc. designs, develops, manufactures, markets, deploys, and supports autonomous security robots (ASR) in the United States. The company provides K5 Outdoor ASR for external environments comprising parking lots, logistics facilities, and corporate campuses; K1 Hemisphere, a stationary unit for indoor and outdoor use; and Knightscope Security Operations Center (KSOC), a browser-based user interface that enables clients to monitor and manage their ASRs in real-time. It also offers emergency communication solutions, including K1 Blue Light Towers that are solar-powered emergency communication stations, which provides immediate access to emergency response personnel or law enforcement in parking lots, public parks, and college campuses; K1 Blue Light E-Phone, a compact emergency phone system that delivers one-touch connectivity and features a high-visibility blue strobe light, which is suitable for locations, such as parking lots, building interiors, college campuses, electr…
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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.