A2Z Cust2Mate Solutions Corp (AZ) Fair Value & Analysis
Technology · US · Market cap $252M
Fair value as of: Jun 24, 2026
Analysis
A2Z Cust2Mate Solutions Corp (AZ) currently trades at $5.26, while our model-based Fair Value estimate is $7.88 — implying the stock looks roughly 49.8% undervalued today. We read business quality at 92/100 (high quality), in the Technology 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: low) — always confirm before acting.
About the company
A2Z Cust2Mate Solutions Corp., a technology company, focuses on the development and commercialization of retail smart cart solutions for grocery stores and supermarkets in Israel and internationally. It operates through Precision Metal Parts, Advanced Engineering, and Smart Carts segments. The company provides Cust2Mate system, which incorporates a smart cart that automatically calculates the value of the customers purchases in their smart cart without having to unload and reload their purchases at a customer checkout point. It also manufactures and sells precision metal parts; provides retail automation solutions; and develops Fuel Tank Inertia Capsule System technology (FTICS), a vehicle device cover for the military and civilian automotive industry. In addition, the company provides maintenance services for various electronic systems. It serves its products to grocery stores, hardware stores, household essentials, do it yourself (DIY) retailers, discount stores, warehouse stores,…
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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.