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SIA

Architecture

Persistent external semantic governance for models, agents, and AI workflows.

A technical view for CTOs, architects, AI researchers, and evaluators. Less marketing, more mechanism.

An architect working through a system diagram

Canonical sequence

Objective in, evidence out.

  1. 01Objective stated by a person
  2. 02Persistent external governance state
  3. 03AI model / agent
  4. 04Observable output or proposed action
  5. 05Consistent state comparison / semantic authorization
  6. 06Machine control
  7. 07Governance record
  1. Objective Established by People
  2. Persistent External Governance StateExternal
    Outside the model boundary
  3. AI Model / AgentProvider
    Interchangeable · defined by provider
  4. Observable Output
  5. Comparison Using Consistent State
    PRESERVEDREGULATEWITHHOLDREVIEW
  6. Machine Control
  7. Governance Record

Persistent state

Persistent, external, and authorized to change only under recognized authority.

A new system version does not automatically grant authority to redefine the governing objective.

Persistent

Available for later comparison or control across a workflow.

External

Independent of model weights, hidden activations, or a workspace specific to one provider.

Authorized transitions

Changes to governance state require separately recognized authority with recorded lineage.

Consistent state comparison

The output state representation is compared against retained state.

The comparison produces a relationship for machine control.

Release
Regenerate
Change instruction
Withhold
Route for review
Select model / configuration
Create governance record

Claim provenance

Provenance travels with the claim.

MeasuredSupported by sourcesAssisted by a modelCalibrated / estimatedUnavailableInconclusive

Privacy architecture

Remove identifying details inside the trust boundary.

SIA supports architectures that remove regulated identifiers inside organizational trust boundaries before external model processing, then associate results again under governed control. A deployment pattern, not a compliance guarantee.

Efficiency architecture

Separate meaning from realization.

The architecture allows semantic content generation and linguistic realization to be separated. Preliminary internal evaluations have indicated potential savings in output token costs on evaluated workloads. Results depend on the workload. Updated benchmark results are coming soon.

Capability evolution

A research boundary, stated plainly.

Increasing AI capability should not, by itself, constitute authority to redefine the human objective governing that capability.

What SIA does not claim

  • Reads unexpressed human mental states.
  • Requires access to hidden model reasoning.
  • Replaces cybersecurity.
  • Replaces human accountability.
  • Guarantees regulatory compliance.
  • Currently claims to control recursive improvement.

Technical overview

Go deeper on the architecture.

Download Technical OverviewRead the White Paper