Celebrus Technologies plc (DFORF) Fair Value & Analysis
Technology · US · Market cap $38.1M
Fair value as of: Jun 25, 2026
Analysis
Celebrus Technologies plc (DFORF) currently trades at $1.00, while our model-based Fair Value estimate is $2.41 — implying the stock looks roughly 141.0% undervalued today. We read business quality at 95/100 (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
Celebrus Technologies plc, together with its subsidiaries, operates a digital identity and data platform in the United Kingdom, rest of Europe, the United States, and internationally. It offers Celebrus Data Platform, a data and digital identity technology; Celebrus Data Platform Marketing, which enables customers interact across different channels, devices, and domains; Celebrus Data Platform Fraud that provides data to prevent fraud; Celebrus Analytics and Reporting, which captures every digital interaction across devices, sessions, and domains that gives a real-time view of customer behavior; Celebrus Digital Analytics, connects the dots between visits, devices, and behaviors; and Celebrus Cloud, enables businesses to ingest and unify customer interactions across digital channels providing real-time decisioning for marketing, fraud prevention, and compliance use cases. The company also provides professional and non-celebrus managed services; and third party products. It serves fi…
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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.