Elliptic Laboratories ASA (ELABS) Fair Value & Analysis
Technology · NO · Market cap 390M NOK
Fair value as of: Jun 24, 2026
Analysis
Elliptic Laboratories ASA (ELABS) currently trades at kr 2.90, while our model-based Fair Value estimate is kr 4.51 — implying the stock looks roughly 55.5% 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: low) — always confirm before acting.
About the company
Elliptic Laboratories ASA, an artificial intelligence (AI) software company, engages in the provision of AI virtual smart sensors for the smartphone, laptop, Internet of Things, and automotive markets in Norway, the United States, China, South Korea, Taiwan, and Japan. The company offers AI Virtual Human Presence Sensor, a presence-detection solution used to improve the security of data stored on devices and to allow intuitive responses based on natural human interaction; AI Virtual Proximity Sensor that enables exquisite full-screen devices; and AI Virtual Connection Sensor that allows pair and authenticate smart devices that are in the same room using ultrasound. It also provides AI Virtual Position Sensor which automatically detects the location of an external display in relation to a laptop; AI Virtual Gesture Sensor that enables touchless user interactions; AI Virtual Breathing sensor that enables to track person's breathing; and AI Virtual heartbeat Sensor that tracks a person…
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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.