Data Privacy
Privacy controls, tags, and workflow from source.
Data Privacy
BondingAI AIOS is designed to operate in complex enterprise environments where privacy, compliance, and trust are non-negotiable. As an AI Operating System that processes sensitive business and personal data, AIOS embeds data privacy controls at every level of the architecture—from ingestion to inference.
The platform applies privacy-by-design and least-privilege access principles to meet stringent regulatory requirements (e.g., GDPR, LGPD, HIPAA, CCPA) and enterprise data standards.
Privacy Management Principles
- Classify Data Before Ingestion: All data is pre-classified by source and domain using a configurable privacy taxonomy via Platform Interface.
- Masking and Redaction by Default: Sensitive data is masked, encrypted, or anonymized before reaching AI agents or model pipelines.
- Fine-Grained Access Controls: Data access is enforced at the row, column, or document level, based on user roles and data policies.
- Data Minimization: Agents only retrieve the minimum data required to perform their task, respecting both system rules and user context.
- Auditability: All data access and transformations are logged and traceable, enabling full compliance audits and user-level accountability.
Data Confidentiality (Tags)
| Tags Classification | Description |
| Public | Freely accessible data (e.g., public knowledge base) used by agents |
| Corporative | Data accessible only to internal AI agents and employees (e.g., product documentation, training material) |
| Confidential | Shared under NDA and limited to specific internal users or agents (e.g., financial plans, internal strategies) |
| Sensitive (Personal Data) | Includes PII and regulated data—must be encrypted, masked, and accessed only under strict rules (e.g., HR records, customer data) |
| Restricted | Access granted only to named individuals or systems with formal responsibility (e.g., legal data, IP, board materials) |
Privacy Enforcement
| Mechanism | Purpose |
| Policy Engine | Enforces data access at the domain, user, groups and role level, integrated into every data interaction |
| Metadata Tagging | Data objects tagged by sensitivity level to automate masking, access limits, and expiration policies |
| PII Detection Pipelines | Automated scanning and classification of personal data using AI-enhanced detectors |
| Agent-Aware Privacy | Agents are scoped to operate only on data permitted to their role, with built-in context restrictions |
| Data Governance | Visibility into who accessed what, when, and under what policy, with audit-ready logs |
Data Classification Workflow
- Ingest Data → Pre-classify by Product creation, using metadata, source rules, and AI-assisted tagging
- Apply Policies → Enforce filtering, based on sensitivity
- Use in AIOS → Serve data to agents, APIs, or users with policy-bound access and purpose limitation
- Monitor & Audit → Log access, monitor violations, and enforce data expiration/retention rules