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AiRWA Inc (YYAI) Fair Value & Analysis

Technology · US · Market cap $7.3M

Price$6.92
Fair Value$9.30
Upside+34.4%
Quality90/100
Evidence: Medium Range $6.97 – $11.62

Fair value as of: Jun 25, 2026

Analysis

AiRWA Inc (YYAI) currently trades at $6.92, while our model-based Fair Value estimate is $9.30 — implying the stock looks roughly 34.4% undervalued today. We read business quality at 90/100 (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: medium) — always confirm before acting.

About the company

AiRWA Inc. through its subsidiaries, operates artificial intelligence software that provides online matchmaking and dating experiences in Hong Kong, the United States, and the United Kingdom. The company was formerly known as Connexa Sports Technologies Inc. and changed its name to AiRWA Inc. in October 2025. AiRWA Inc. was founded in 2021 and is headquartered in Smyrna, Delaware.

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Frequently asked questions

Is AiRWA Inc (YYAI) undervalued?
As of Jun 25, 2026, our model estimates a fair value of $9.30 versus a price of $6.92 — about +34% (undervalued). Model-based estimate, not financial advice.
What is the fair value of YYAI?
Our 21-model fair value for AiRWA Inc is $9.30 (as of Jun 25, 2026), built from audited fundamentals. The current price is $6.92.
What is the quality score of YYAI?
AiRWA Inc has a Quality Score of 90/100, 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.