Shrouva

Your most valuable data is also your most sensitive. So it never reaches the models that could predict your future. Until now.
PLATFORM OVERVIEW
The Architecture of Enterprise-Grade Privacy

Tokenization & Encryption
Transform sensitive PII into secure, non-identifiable tokens using FF1 and AES-256 before any processing.

Differential Privacy
Configurable ε noise budgets ensure model predictions are statistically robust without compromising individual privacy.

AI Handoff
Send protected data to tabular foundation models for classification, regression, and forecasting with full integrity.

Resolve & Audit
Map predictions back to real identifiers with per-row integrity seals and a comprehensive, immutable audit trail.
How It Works
The Architecture of Enterprise Privacy



01. Protect
02. Predict
03. Resolve
Shrouva employs AES-256 and format-preserving encryption to tokenize sensitive data, ensuring it remains confidential within your perimeter.
Protected data is securely handed off to tabular foundation models for classification, forecasting, and anomaly detection without exposing raw identifiers.
Shrouva maps model predictions back to real-world identifiers with per-row integrity seals and a full, immutable audit trail for every prediction.
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