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Thinkific Labs Inc (THNC) Fair Value & Analysis

Technology · CA · Market cap C$80.9M

PriceC$1.21
Fair ValueC$0.5000
Upside-58.7%
Quality95/100
Evidence: High Range C$0.4000 – C$0.6400

Fair value as of: Jun 24, 2026

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Analysis

Thinkific Labs Inc (THNC) currently trades at C$1.21, while our model-based Fair Value estimate is C$0.5000 — implying the stock looks roughly 58.7% 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: high).

About the company

Thinkific Labs Inc. engages in the development, marketing, and support management of cloud-based platform in Canada, the United States, and internationally. It provides a learning commerce platform that provides courses, communities, AI and commerce. The company was incorporated in 2012 and is headquartered in Vancouver, Canada.

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Frequently asked questions

Is Thinkific Labs Inc (THNC) undervalued?
As of Jun 24, 2026, our model estimates a fair value of C$0.5000 versus a price of C$1.21 — about −59% (overvalued). Model-based estimate, not financial advice.
What is the fair value of THNC?
Our 21-model fair value for Thinkific Labs Inc is C$0.5000 (as of Jun 24, 2026), built from audited fundamentals. The current price is C$1.21.
What is the quality score of THNC?
Thinkific Labs Inc 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.