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Regenera Insights Inc (DCTIF) Fair Value & Analysis

Industrials · US · Market cap $1.3M

Price$0.0100
Fair Value$0.0110
Upside+10.0%
Quality95/100
Evidence: Medium Range $0.0100 – $0.0110

Fair value as of: Jun 26, 2026

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Analysis

Regenera Insights Inc (DCTIF) currently trades at $0.0100, while our model-based Fair Value estimate is $0.0110 — implying the stock looks roughly 10.0% undervalued today. We read business quality at 95/100 (high quality), in the Industrials 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

Regenera Insights Inc. engages in the methane collection and destruction; and trading businesses in Canada. The company was formerly known as Delta CleanTech Inc. and changed its name to Regenera Insights Inc. in March 2025. Regenera Insights Inc. was incorporated in 2020 and is headquartered in Calgary, Canada.

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Frequently asked questions

Is Regenera Insights Inc (DCTIF) undervalued?
As of Jun 26, 2026, our model estimates a fair value of $0.0110 versus a price of $0.0100 — about +10% (undervalued). Model-based estimate, not financial advice.
What is the fair value of DCTIF?
Our 21-model fair value for Regenera Insights Inc is $0.0110 (as of Jun 26, 2026), built from audited fundamentals. The current price is $0.0100.
What is the quality score of DCTIF?
Regenera Insights 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.