IRIS (IRIS) Fair Value & Analysis
Technology · Market cap ₹5.5B
Fair value as of: Jul 3, 2026
From 23 valuation models · updated today
Share price +1.8% over the past month.
Price vs Fair Value (12 months)
12‑month range ₹210.91 – ₹412.85 · fair‑value band ₹117.14 – ₹195.23 · the ₹267.15 price screens above the ₹156.19 fair value. As of Jul 3, 2026.
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IRIS (IRIS) currently trades at ₹267.15, while our model-based Fair Value estimate is ₹156.19 — implying the stock looks roughly 41.5% overvalued today. We read business quality at 55/100 (solid 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).
Over the trailing twelve months, IRIS generated revenue of ₹1.3B at a net margin of 98.4%. Revenue grew 13.0% year over year. It earns a return on equity of 10.2%. The balance sheet holds a net cash position of ₹437M. Fundamentals as of Jul 3, 2026
Key figures & financial health
More key figures
Figures from reported company fundamentals (EODHD) · as of Jul 3, 2026. TTM = trailing twelve months.
Revenue & earnings trend
FY2022 – FY2026 · reported fiscal years
IRIS reported revenue of ₹1.3B in FY2026 versus ₹613M in FY2022, a compound +20.3%/yr. Reported net income was ₹1.3B in FY2026, compounding +235.5%/yr from FY2022.
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6 more Software - Application stocks, each showing price versus our Fair Value estimate (as of Jul 3, 2026).
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| SAP SE SAPP34 | R$949.05 | R$674.65 | -29% |
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| Cadence Design Systems, Inc CDNS | $385.13 | $80.41 | -79% |
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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.