Project

Compliance Plan Generator

An in-development, rule-driven system for structuring product inputs, applicability logic, and traceable compliance-planning outputs with mandatory human review.

Review boundary viewArchitecture illustration · in-development workflowProduct inputsRule logicDraft planHuman reviewProduct DNAMarket contextApplicabilityRequirement packagesAssumptionsTraceable outputConfirm and resolveDecisions remain reviewable; automation does not replace confirmation.
In-development decision pathThe intended control points for a draft planning workflow that still requires expert review.
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Project thesis

This in-development system is intended to turn structured product and market inputs into traceable draft compliance-planning outputs. Applicability remains deterministic, unresolved questions stay visible, and expert review is mandatory.

Project scale

Development focus
Structure, traceability, and review
Decision boundary
Deterministic applicability; AI does not decide scope
Public boundary
Architecture only; no public demonstration

Context and constraints

Compliance planning requires product characteristics, target markets, regulatory domains, missing information, applicability rules, required evidence, and review decisions to remain coordinated. Those inputs can be incomplete and rules can change by market, while proprietary knowledge must stay protected and every conclusion still requires expert judgment.

Selected engineering decisions

The current architecture is designed to move from structured Product DNA and classification through deterministic applicability rules, requirement packages, and draft outputs. AI may support explanation or drafting, but it does not determine final applicability. Missing inputs and open questions remain explicit, with human review serving as a required system boundary.

Structure inputs before rules

The design uses explicit Product DNA and classification fields so the planning context can be reviewed before any applicability path is evaluated.

Separate decisions from drafting

Applicability remains deterministic and traceable; AI assistance may explain or draft text but cannot establish the final compliance scope.

Make expert review a system boundary

Carry assumptions, missing inputs, and open questions into review instead of hiding them behind an apparently final plan.

System model

  • Structured product inputs

    The current design starts with Product DNA and target-market inputs that establish the planning context.

  • Product classification

    Classification is intended to organize the attributes that may affect later rule evaluation.

  • Applicability rules

    Deterministic rule paths are being developed without exposing proprietary rule content.

  • Requirement packages

    The architecture is intended to group related requirements without implying complete rule coverage.

  • Structured draft output

    Draft output structures are intended to carry source inputs, assumptions, and planning context forward.

  • Missing inputs and open questions

    Unresolved information remains visible for follow-up instead of being converted into an unsupported conclusion.

  • Human review

    Expert review remains mandatory before any draft output can inform an operational decision.

Interface evidence

Review boundary viewArchitecture illustration · in-development workflowProduct inputsRule logicDraft planHuman reviewProduct DNAMarket contextApplicabilityRequirement packagesAssumptionsTraceable outputConfirm and resolveDecisions remain reviewable; automation does not replace confirmation.
Review-boundary illustrationA public-safe architecture view of assumptions, open questions, and mandatory human confirmation.

Outcome and current boundaries

The project remains in active development, with no public demonstration and no readiness for external operational use. Rule coverage, output structures, and review behavior are still being implemented and validated. This public record describes architecture and workflow only; proprietary rules, internal datasets, and company-sensitive material are excluded. Any output remains draft material requiring expert review.

  • Validate rule accuracy against representative product scenarios.
  • Improve missing-input and open-question handling.
  • Strengthen traceability from source inputs through applicability decisions and draft outputs.
  • Verify output structures and the expert-review workflow with controlled test coverage.
  • Determine whether any future implementation can meet the separate gate for a public-safe demonstration.