INFORTEC (INFORTEC) Fair Value & Analysis
IN · Market cap ₹329M
Fair value as of: Jul 5, 2026
From 10 valuation models · updated today
Share price +5.2% over the past month.
Price vs Fair Value (12 months)
12‑month range ₹68.78 – ₹98.42 · fair‑value band ₹7.62 – ₹12.70 · the ₹79.00 price screens above the ₹10.16 fair value. As of Jul 5, 2026.
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INFORTEC (INFORTEC) currently trades at ₹79.00, while our model-based Fair Value estimate is ₹10.16 — implying the stock looks roughly 87.1% overvalued today. We read business quality at 40/100 (below-average quality). 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: medium).
Trailing-twelve-month revenue stands at ₹14.2M. Revenue declined 45.3% year over year. It earns a return on equity of 1.0%. Net debt stands at ₹2.4M. Fundamentals as of Jul 5, 2026
Our scenario range runs from ₹7.62 (bear case) to ₹12.70 (bull case); at ₹79.00, the current price sits above that range. The share trades about 27% below its 52-week high and 21% above its 52-week low, currently below its 200-day average.
Key figures & financial health
More key figures
Figures from reported company fundamentals (EODHD) · as of Jul 5, 2026. TTM = trailing twelve months.
Revenue & earnings trend
FY2022 – FY2026 · reported fiscal years
INFORTEC reported revenue of ₹12.1M in FY2026 versus ₹26.4M in FY2022, a compound −17.8%/yr. Reported net income was ₹2.5M in FY2026, compounding −36.3%/yr from FY2022.
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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.
Not financial advice · no buy/sell recommendation. Model-based estimates are not certainties; their reliability depends on data quality and assumptions.