Q-Interline A/S, an engineering company, (QINTER) Fair Value & Analysis
Technology · DK · Market cap 57.9M DKK
Fair value as of: Jun 24, 2026
Analysis
Q-Interline A/S, an engineering company, (QINTER) currently trades at kr 2.78, while our model-based Fair Value estimate is kr 0.7300 — implying the stock looks roughly 73.7% overvalued today. We read business quality at 95/100 (high quality), in the Technology sector. Bear case: priced above our estimate, the market already discounts strong expectations. Bull case: above-average quality can justify a premium — the entry price still matters most (evidence: low).
About the company
Q-Interline A/S, an engineering company, develops solutions for process optimization and quality based on infrared spectroscopy and correct sampling in Denmark and internationally. The company offers quant analysers, a quant FT NIR analyser; DairyQuant GO, a laboratory milk analyser; InSight Pro, an in-line process analysis solution for production optimization; quant sampling accessories, comprising cup, bottle, petri, spiral, pivette, bag, and vial samplers; support agreements; and AnalyticTrust, a cloud-based surveillance tool to secure analyser performance. It also provides InfraQuant, a software platform used to streamline QC operations and produce analytical results; InSightView, a frontend software to monitor and control the daily operation of the InSight Pro analyser; and proficiency tests for data referencing and comparison. It serves dairy, plant-based beverages, agricultural, food and ingredients, chemical, and pharmaceutical industries. Q-Interline A/S was founded in 1996…
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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.