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Security

Data security is not a premium feature.

It is the foundation.

STRATIS is built from the ground up as a security-first platform. Every deployment includes the full security model. We do not ask customers to pay extra to protect their own sensitive design intelligence.

Principles

Security Is Default

Every deployment includes tenant isolation, encryption, access control, audit logging, classification tagging, and segmented retrieval. These are not paid add-ons.

Zero-Trust Knowledge Access

No user, service, or AI system is implicitly trusted. Every request is evaluated against identity, role, tenant, classification level, and access policy before any result is returned.

Data Segmentation From Day One

Every persisted object carries a tenant identifier, segment identifier, classification level, ownership metadata, and access policy reference. Segmentation applies to documents, graph relationships, embeddings, and audit records.

Relationships May Be Sensitive

STRATIS treats graph edges, semantic similarity scores, inferred relationships, and metadata associations as governed intelligence — not just the documents themselves.

AI Must Respect Governance Boundaries

Authorization checks, classification validation, and policy evaluation happen before any AI retrieval, summarization, or recommendation is produced. AI reasoning is a governed operation.

Inferences Are Governed Intelligence

Embeddings, AI-generated summaries, similarity scores, and reasoning outputs are subject to the same access controls as the source data they are derived from.

Technical Controls

Tenant Isolation

Multi-tenant architecture with strictly tenant-scoped data, search, graph relationships, and audit logs.

Role-Based Access Control

Granular RBAC enforced at document retrieval, relationship traversal, workflow actions, and AI context assembly.

Classification Tagging

Documents and relationships carry classification levels. Retrieval is filtered against the requestor's authorization level before results are returned.

Audit Logging

Tamper-evident audit events for every meaningful operation — foundation for compliance reporting and forensic investigation.

Encryption

Data encrypted at rest and in transit across all deployment models.

Segmented Retrieval

Search indexes, vector embeddings, and graph traversal are scoped to segment boundaries with no cross-segment leakage.

Policy Enforcement Service

A dedicated policy layer evaluates every retrieval and reasoning request before any result is produced.

Portable Deployment

SaaS, private cloud, and on-premises via configuration — no security trade-offs for deployment model choice.

Air-Gap Readiness

Architecture designed to support future classified and air-gapped environments. No design decisions foreclose regulated deployment.

Secure Retrieval Pipeline

Every request passes through the same pipeline.

No step can be bypassed — not by a user, not by a service, and not by an AI reasoning workflow. Policy enforcement is a first-class architectural requirement, not a wrapper added after the fact.

1

User request received

2

Tenant resolved

3

Policy evaluation

4

Retrieval scope generated

5

Filtered semantic retrieval

6

Graph relationship filtering

7

Context assembly

8

AI reasoning

9

Response filtering

10

Audit event generated

Questions about security?

Reach out to discuss deployment models, compliance requirements, or specific security controls.

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