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Adveritas Limited (AV1) Fair Value & Analysis

Technology · AU · Market cap A$74.1M

PriceA$0.0800
Fair ValueA$0.1360
Upside+70.0%
Quality95/100
Evidence: Low Range A$0.0880 – A$0.1760

Fair value as of: Jun 26, 2026

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Analysis

Adveritas Limited (AV1) currently trades at A$0.0800, while our model-based Fair Value estimate is A$0.1360 — implying the stock looks roughly 70.0% 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

Adveritas Limited provides funnel measurement, verification, and fraud prevention solutions for digital advertising in North America, Latin America, Asia Pacific, Australia, Europe, and internationally. The company operates through Product and Engineering; and Sales and Marketing segments. It develops TrafficGuard, a software as a service product that prevents fraud from infiltrating clients' budgets, as well as provides customer service. The company was formerly known as Tech Mpire Limited and changed its name to Adveritas Limited in December 2018. Adveritas Limited is based in Bentley, Australia.

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Frequently asked questions

Is Adveritas Limited (AV1) undervalued?
As of Jun 26, 2026, our model estimates a fair value of A$0.1360 versus a price of A$0.0800 — about +70% (undervalued). Model-based estimate, not financial advice.
What is the fair value of AV1?
Our 21-model fair value for Adveritas Limited is A$0.1360 (as of Jun 26, 2026), built from audited fundamentals. The current price is A$0.0800.
What is the quality score of AV1?
Adveritas Limited 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.