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nDatalyze Corp (NDATF) Fair Value & Analysis

Healthcare · US · Market cap $6.1M

Price$0.0800
Fair Value$0.0240
Upside-70.0%
Quality95/100
Evidence: Low Range $0.0240 – $0.0320

Fair value as of: Jun 26, 2026

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Analysis

nDatalyze Corp (NDATF) currently trades at $0.0800, while our model-based Fair Value estimate is $0.0240 — implying the stock looks roughly 70.0% 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

nDatalyze Corp. provides technologically based solutions related to applying machine learning to a records database to predict probable mental health conditions. It offers Sigmund, a machine-learning-based online mental health application for the mental health system, such as misdiagnosis and mis prescription. The company was formerly known as MedXtractor Corp. and changed its name to nDatalyze Corp. in October 2021. nDatalyze Corp. was incorporated in 2018 and is headquartered in Calgary, Canada.

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Frequently asked questions

Is nDatalyze Corp (NDATF) undervalued?
As of Jun 26, 2026, our model estimates a fair value of $0.0240 versus a price of $0.0800 — about −70% (overvalued). Model-based estimate, not financial advice.
What is the fair value of NDATF?
Our 21-model fair value for nDatalyze Corp is $0.0240 (as of Jun 26, 2026), built from audited fundamentals. The current price is $0.0800.
What is the quality score of NDATF?
nDatalyze Corp 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.