VRODIA is building the fit intelligence layer for fashion commerce.
Fashion tracks payments, inventory, and transactions at global scale, yet still treats fit as guesswork. Most fit outcomes disappear into returns, exchanges, and abandoned carts instead of becoming usable intelligence.
The result is structural: apparel returns and fit-related inefficiencies are estimated to cost global retail more than $890B annually across inventory, logistics, reverse supply chains, and lost purchase confidence.
VRODIA converts checkout sizing inputs and post-purchase fit outcomes into structured SKU-level signals designed to improve size prediction and create cross-brand visibility into how garments actually perform on real bodies over time.
Every returned garment is a data failure the industry normalized.
Founded by Risha Debbarma, VRODIA is currently operating through controlled pilots with select fashion retail and DTC partners while continuously expanding its fit feedback dataset across real transaction environments.
The thesis is simple: once fit becomes measurable, apparel commerce starts compounding through outcome data instead of assumptions.

VRODIA

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VRODIA

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