AI Security Architecture

Architecture direction. Availability depends on the workflow, deployment, and verification surface in scope.

Lattix is designed to keep AI capability separate from security authority. A model can help interpret structured intent or surface a semantic relationship, but the model output is not itself an authorization decision.

The qualified neurosymbolic model

We use neurosymbolic security architecture as a qualified systems term:

1. Model-assisted signal — a model or automated analyzer helps interpret intent, classify content, or propose a relationship.
2. Governed semantic context — approved relationships, classifications, purpose, lineage, and regulatory context are versioned and scoped.
3. Bounded verification — supported AI-mediated actions are represented as explicit constraints and checked by repeatable controls.
4. Policy enforcement — verification evidence is passed into the existing authorization and enforcement path.

This describes how security controls surround AI-mediated actions. It does not mean that model generation is deterministic, that every model behavior is formally proven, or that semantic context independently grants access.

Why the boundary matters

Model confidence is not authority. A model-assisted candidate remains a proposal until it passes the applicable governance workflow. Semantic context explains which relationships and policy inputs are in scope. Verification tests a supported action against explicit constraints. Authorization and protected-data enforcement still decide whether data or keys can be released.

The separation supports:

• Reviewable change — proposed semantic relationships can be accepted, modified, or rejected before becoming trusted context.
• Repeatable controls — supported actions can be evaluated against bounded rules rather than relying on a second model to judge the first.
• Fail-closed handling — ambiguity, mismatch, unavailable verification, or incomplete context can stop the workflow from receiving authority.
• Auditable evidence — the security path can retain the policy context, verification result, and enforcement decision as distinct evidence.

Where it fits in the platform

The architecture complements the rest of Lattix:

• Policies and ABAC remains the authorization model over principal, data, and context.
• Trusted Data Format keeps protection and policy attached to governed objects.
• Zero Trust Fabric provides policy enforcement at the point where access occurs.
• Ontological Data Security provides the semantic security context that can make relationships explicit and reviewable.

What this architecture is not

• It is not a new model or model-vendor claim.
• It is not deterministic AI generation.
• It is not universal formal verification of arbitrary prompts or model behavior.
• It is not a replacement for policy decisions, key release controls, or protected-data enforcement.

For the broader data-centric model, see AI Security and the Platform Overview.