wiki/projects/semantic-integrity/pilot-architecture

Semantic Integrity Pilot Architecture

wiki/projects/semantic-integrity/pilot-architecture/index.md

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Semantic Integrity Pilot Architecture

This page extracts the pilot half of the initial due diligence FAQ into a deeper working model. The pilot is a bounded, real-client workflow exercise, not a broad transformation program.

Working Read

The pilot tests whether a regulated workflow becomes more legible, auditable, and safely assistable when its policies, roles, evidence requirements, and review obligations are made explicit inside a semantic container.

The claim is not that AI should make decisions on its own. The claim is that structured context can make local or private AI meaningfully more useful in the workflow boundary humans already control.

What The Pilot Must Prove

  • A real workflow can be mapped without flattening its authority boundaries.
  • Semantic containers improve AI usefulness more than generic prompting does.
  • Human review stays explicit, especially around uncertainty and exceptions.
  • The resulting artifacts are portable, readable, and auditable.

Semantic Container

A semantic container is the working unit for the pilot. It is a human-readable structure that records:

  • meaning
  • boundaries
  • inputs and outputs
  • authority
  • dependencies
  • evidence requirements
  • review obligations

In practice, this can be expressed as plain English, structured prompts, YAML, JSON, checklists, workflow maps, role definitions, policy references, approval rules, or audit trail logic.

Good Pilot Candidates

  • client onboarding
  • month-end review
  • compliance exception routing
  • document intake
  • regulated approval workflows
  • vendor review
  • audit preparation

The workflow should matter, but it should not be the most fragile or mission-critical process in the organization.

Pilot Outputs

  • workflow map
  • role and authority map
  • evidence and source map
  • policy and procedure conversion
  • human review and escalation model
  • semantic container representation
  • local or private AI test harness
  • before/after performance comparison
  • auditability and traceability review
  • final pilot report

Evaluation

The pilot is successful if:

  • humans say the workflow is clearer
  • AI is more useful with structured context than without it
  • review burden drops or becomes more focused
  • authority boundaries remain intact
  • outputs can be exported and maintained
  • there is a credible path to production

Boundaries

  • No broad automation mandate.
  • No autonomous decision-making in regulated areas.
  • No obscuring of provenance or authority.
  • No client lock-in through hidden structure.

The client should retain the workflow artifacts. Semantic Integrity should retain the general methods and non-client-specific learnings.

Source Artifact

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