Privacy Policy & Data Sovereignty
Zero-Leak Institutional Privacy Architecture for JyotOS and Product Ecosystem
Student & employee records are cryptographically isolated per institution.
Client data is strictly never used to train public commercial AI models.
Full alignment with India Digital Personal Data Protection mandates.
1. Institutional Trust & Purpose
Hi-Tech AI Solutions & Services (“Company”, “we”, “us”) provides high-performance AI systems, academic operating platforms (including JyotOS, ScholarCard AI, jyotAssist AI, StaffBridge, and EventOS), and automated enterprise software.
This Privacy Policy governs the processing of technical, academic, and administrative information collected through our official portal (hi-tech-ai-solutions.github.io) and client-contracted institutional cloud environments.
2. Data Classification & Collection Boundaries
We strictly limit data processing to necessary operational parameters:
- Institutional Administrative Data: College department configurations, curriculum structures, examination grade entries, and sanctioned capacities required for operating JyotOS.
- Student Identity & Verification Data: Digital identity records for ScholarCard AI, enrollment IDs, and tamper-evident QR verification tokens.
- Faculty & Staff Attendance Metrics: Biometric sync logs, duty rosters, and leave approvals processed through StaffBridge.
- Consultation & Inquiry Information: Contact names, institutional email addresses, and phone numbers willingly submitted via our executive consultation portal.
3. AI Core Safeguards: Zero Model Training Guarantee
A fundamental tenet of our engineering philosophy is that institutional data belongs solely to the institution.
When AI reasoning, RAG (Retrieval-Augmented Generation), or anomaly detection is performed via the AAI (Academic Artificial Intelligence) Engine or jyotAssist AI:
- • Client datasets are NEVER submitted into public foundation models for model retraining.
- • Prompts dispatched for contextual inference are sanitized to scrub personally identifiable information (PII).
- • Vector embeddings generated for institutional knowledge bases reside in dedicated, private PostgreSQL pgvector instances.
4. Storage, Encryption & Multi-Tenant Partitioning
All client databases leverage AES-256 at-rest encryption and TLS 1.3 in-transit protocol enforcement. Each college, university, or enterprise client operates in logically and physically isolated tenant schemas, completely eliminating cross-tenant visibility.
5. Data Subject Rights & Grievance Officer
In accordance with the Digital Personal Data Protection Act, institutional users and individuals retain the right to access, correct, or request deletion of personal information.