Fabrity S.A (FAB) Fair Value & Analysis
Technology · PL · Market cap 79.2M PLN
Fair value as of: Jun 24, 2026
Analysis
Fabrity S.A (FAB) currently trades at 25.40 PLN, while our model-based Fair Value estimate is 30.23 PLN — implying the stock looks roughly 19.0% 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: high) — always confirm before acting.
About the company
Fabrity S.A. provides technological solutions in Poland. The company offers enterprise software and web and mobile development, legacy system modernization, and digital transformation; data engineering services, including snowflake deployment, data migration and integration, AI-powered data analytics, big data solutions, data processing and transformation, and data governance and security; and generative AI. It also designs and build blockchain business applications. In addition, the company offers Nexen Suite, an industrial IoT platform designed for industry, smart cities, and large enterprises; Azure development services comprising Azure AI Services, Azure Internet of Things (IoT), Azure Cloud architecture and consulting, Azure Infrastructure as a Service, Azure Platform as a Service, and Azure Software as a Service; and digital solutions. Further, it provides B2C eCommerce development, B2B eCommerce development, migration, maintenance, UX/UI audit, eCommerce CRO, code audit, team…
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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.