Research program
Trustworthy AI work is an institutional systems problem.
Waveframe Labs studies the complete path from human authority and scientific method to machine-readable constraints and durable evidence.
Aurora Research Initiative
Institutional governance for research conducted with AI systems.
Read the governance model → ReproducibilityAurora Workflow Orchestration
Role-separated workflows, stable artifacts, explicit gates, and independent review.
Read the methodology → ProvenanceNeurotransparency
Why AI-assisted cognition requires disclosure—and how that requirement becomes normative.
Read doctrine and specification → EnforcementCRI-CORE
Deterministic evaluation of proposed actions against explicit, published authority.
Read the technical model →Shared commitments
What remains true across the work.
Humans retain institutional authority.
AI can contribute analysis, proposals, and transformations. It does not silently acquire the right to approve its own work.
Artifacts carry the research record.
Claims, evidence, reviews, decisions, and execution results must survive beyond a conversation or model session.
Ambiguity is surfaced, not guessed away.
When authority or evidence cannot be positively established, the system should stop and require resolution.
Consequences require admissibility.
Reasoning and execution are separate boundaries. A plausible proposal is not automatically an authorized action.
Research record
Follow the artifacts, not the claims.
Publications, DOI-backed releases, source repositories, and the chronological institutional log provide the inspectable record behind the work.