PagerDuty, Inc (PD) Fair Value & Analysis
Technology · US · Market cap $654M
Analysis
PagerDuty, Inc (PD) currently trades at $8.49, while our model-based Fair Value estimate is $15.97 — implying the stock looks roughly 88.1% undervalued today. We read business quality at 94/100 (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
PagerDuty, Inc. engages in the operation of a digital operations management platform in the United States and internationally. The company collects data and digital signals from virtually any software-enabled system or device and leverages artificial intelligence and powerful machine learning to correlate, process, predict, and remediate incident. Its platform includes PagerDuty Incident Management that provides a real-time view status of a digital service; AIOps that applies machine learning to correlate and automate the identification of incidents from billions of events; automation offers centralized design time and run time environment for orchestrating automated workflows; customer service operations, which is offered to orchestrate, automate, and scale responses to customer issues; and artificial intelligence offers generative AI capabilities for the PagerDuty operations cloud platform . The company serves various industries, including software and technology, telecommunicatio…
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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.