Master Privacy & Data Governance Policy
Applicable to Your Legal Indian OPC and all subsidiary nodes.
1.0 Objective & Jurisdictional Scope
This Master Privacy & Data Governance Policy outlines the data processing, retention, and cryptographic protocols executed by Your Legal Indian OPC ("the Enterprise") and its operational divisions (HashPaper, FinalDemand.ORG, SOWRegistry, NesaWorks, and Nesadiv).
All data infrastructure and algorithmic processing are engineered in strict compliance with the Digital Personal Data Protection (DPDP) Act, 2023 and the Information Technology Act, 2000 of the Republic of India. The primary legal jurisdiction for all data-related arbitration shall be Bengaluru, Karnataka.
2.0 Zero-Retention Cryptographic Protocols (HashPaper)
The HashPaper division operates on a Zero-Retention Architecture. When a client executes an IP timestamping protocol, the original file is mathematically hashed (SHA-256) locally on the client's hardware.
Your Legal Indian OPC receives, logs, and inscribes only the resulting cryptographic hash onto our evidentiary ledger. At no point do we upload, transmit, read, or store the underlying intellectual property or raw file data.
3.0 Evidentiary Ledgering (FinalDemand & SOWRegistry)
Data submitted to FinalDemand.ORG (for dispute automation) and SOWRegistry (for career gap validation) is classified as Evidentiary Material. This data is processed as a Data Fiduciary strictly to execute the requested legal or validation framework.
Evidentiary Material is stored in encrypted, segmented silos and is retained for a mandatory statutory period of 36 months to ensure court admissibility and HR audit compliance, after which it is systematically purged unless an active dispute hold is applied.
4.0 Algorithmic Objectivity (Nesadiv & NesaWorks)
Nesadiv and NesaWorks deploy proprietary Large Language Model (LLM) structures and Answer Engine Optimization (AEO) frameworks. These algorithms are strictly constrained to evaluate human capital metrics mathematically.
To prevent algorithmic bias, demographic identifiers (including but not limited to age, gender, religion, and caste) are actively stripped from the dataset prior to salary matrix calculations or compliance audits. Data ingested by our models is never sold to third-party data brokers or external advertising networks.
Document Metadata
YLI-FD-02
YLI-SR-03
YLI-NW-04
YLI-ND-05