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Agillic A/S (AGILC) Fair Value & Analysis

Technology · DK · Market cap 75.8M DKK

Pricekr 6.60
Fair Valuekr 3.78
Upside-42.7%
Quality95/100
Evidence: Low Range kr 2.08 – kr 5.48

Fair value as of: Jun 24, 2026

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Analysis

Agillic A/S (AGILC) currently trades at kr 6.60, while our model-based Fair Value estimate is kr 3.78 — implying the stock looks roughly 42.7% 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

Agillic A/S operates as a software company in Denmark and internationally. The company offers a marketing automation platform, enabling personalization that complies with GDPR. It also provides professional training services. The company serves its products to retail, financial services, media and subscription, and NGO and charity sectors. Agillic A/S was incorporated in 1999 and is headquartered in Copenhagen, Denmark.

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Frequently asked questions

Is Agillic A/S (AGILC) undervalued?
As of Jun 24, 2026, our model estimates a fair value of kr 3.78 versus a price of kr 6.60 — about −43% (overvalued). Model-based estimate, not financial advice.
What is the fair value of AGILC?
Our 21-model fair value for Agillic A/S is kr 3.78 (as of Jun 24, 2026), built from audited fundamentals. The current price is kr 6.60.
What is the quality score of AGILC?
Agillic A/S has a Quality Score of 95/100, measuring profitability, growth and balance-sheet strength from non-valuation factors.

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.