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Razor Labs (RZR) Fair Value & Analysis

Technology · Il · Market cap 194M ILA

Price4.15 ILA
Fair Value2.19 ILA
Upside-47.3%
Quality95/100
Evidence: Low Range 1.65 ILA – 2.74 ILA

Fair value as of: Jun 23, 2026

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Analysis

Razor Labs (RZR) currently trades at 4.15 ILA, while our model-based Fair Value estimate is 2.19 ILA — implying the stock looks roughly 47.3% overvalued today. We read business quality at 95/100 (high quality), in the Technology 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

Razor Labs provides artificial intelligence (AI) services to mining industry in Israel, Australia, South Africa, and internationally. It offers DataMind AI, an end-to-end predictive intelligence platform designed to protect every asset across mobile fleets, fixed assets, and AI-powered visual monitoring systems. The company was incorporated in 2016 and is based in Tel Aviv-Yafo, Israel.

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Frequently asked questions

Is Razor Labs (RZR) undervalued?
As of Jun 23, 2026, our model estimates a fair value of 2.19 ILA versus a price of 4.15 ILA — about −47% (overvalued). Model-based estimate, not financial advice.
What is the fair value of RZR?
Our 21-model fair value for Razor Labs is 2.19 ILA (as of Jun 23, 2026), built from audited fundamentals. The current price is 4.15 ILA.
What is the quality score of RZR?
Razor Labs has a Quality Score of 95/100, measuring profitability, growth and balance-sheet strength from non-valuation factors.

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.