Awfis Space Solutions Limited (AWFIS) Fair Value & Analysis
Industrials · IN · Market cap ₹21.8B
Fair value as of: Jun 29, 2026
Analysis
Awfis Space Solutions Limited (AWFIS) currently trades at ₹304.85, while our model-based Fair Value estimate is ₹430.54 — implying the stock looks roughly 41.2% undervalued today. We read business quality at 97/100 (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: high) — always confirm before acting.
About the company
Awfis Space Solutions Limited provides flexible workspace solutions in India. The company operates through the Co-Working Space on Rent and Allied Services, Construction and Fit-Out Projects, and Other Services segments. It provides co-working solutions under the Awfis and Awfis Gold names, as well as enterprise workspace solutions comprising design, construction, and management. The company also offers mobility solutions, such as meeting rooms that are equipped with internet connectivity, audio and video conferencing facilities, and other amenities; day passes, which provides temporary access to workspaces; and Virtual Office and Virtual Office Plus that provide business location addresses and package handling services, as well as training rooms. In addition, it provides design and build solutions for developing centers and external commercial offices. The company was formerly knowns as Awfis Space Solutions Private Limited and changed its name to Awfis Space Solutions Limited. Awf…
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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.