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Softlab S.p.A (SFT) Fair Value & Analysis

Industrials · IT · Market cap 60.5M GBX

Pricep0.1600
Fair Valuep0.0300
Upside-81.3%
Quality95/100
Evidence: High Range p0.0200 – p0.0300

Fair value as of: Jun 26, 2026

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Analysis

Softlab S.p.A (SFT) currently trades at p0.1600, while our model-based Fair Value estimate is p0.0300 — implying the stock looks roughly 81.3% 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: high).

About the company

Softlab S.p.A. provides business advisory and ICT consulting services in Italy, rest of European countries, the United States, and internationally. It offers data analytics, GRC audit and security, digital sales and marketing, RPA and customer services, and TLC network management, as well as develops and tests customized web, app, and network software solutions. The company was formerly known as Acotel Group S.p.A. and changed its name to Softlab S.p.A. in January 2021. Softlab S.p.A. is based in Rome, Italy. Softlab S.p.A. is a subsidiary of Softlab Holding s.r.l.

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Frequently asked questions

Is Softlab S.p.A (SFT) undervalued?
As of Jun 26, 2026, our model estimates a fair value of p0.0300 versus a price of p0.1600 — about −81% (overvalued). Model-based estimate, not financial advice.
What is the fair value of SFT?
Our 21-model fair value for Softlab S.p.A is p0.0300 (as of Jun 26, 2026), built from audited fundamentals. The current price is p0.1600.
What is the quality score of SFT?
Softlab S.p.A 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.