Solutions 30 SE (SLUNF) Fair Value & Analysis
Technology · US · Market cap $304M
Fair value as of: Jun 24, 2026
Analysis
Solutions 30 SE (SLUNF) currently trades at $2.84, while our model-based Fair Value estimate is $2.84 — implying the stock looks roughly 0.0% undervalued today. We read business quality at 91/100 (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: medium) — always confirm before acting.
About the company
Solutions 30 SE provides support solutions for new digital technologies in Benelux, France, Spain, Italy, Germany, Portugal, Poland, and the United Kingdom. The company offers energy solutions, including installation and maintenance of smart meters; charging stations for electric vehicles; photovoltaic power plants for professional and residential markets; smart appliances comprising thermostats, light bulbs, plugs, and sensors; and L/H gas converters, as well as logistics services. It also provides IT solutions, such as the installation and maintenance of IT hardware, IT infrastructure, and servers; the implementation of automated robotic processes; the deployment and maintenance of Internet of Things (IoT) systems; TOTEM/KIOSK design, manufacturing, installation, and maintenance; console creation for data analytics; and logistics of spare parts and systems. In addition, the company offers energy solutions, including the installation and maintenance of smart meters; charging statio…
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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.