AIO CODE
What is AIO CODE?
AIO CODE is a Digital Entity Operating System: an operating architecture for digital entities with canonical records, evidence rules, content relationships, source provenance, measurements and protected operations.
Its research and implementation methodology is an internal component. It studies how external systems retrieve, resolve, represent, cite and potentially recommend entities. Phase 2 connects the established infrastructure to controlled content and future pilots.
“Operating system” describes this coordinated framework, not computer OS software or a finished SaaS product. The partial baseline records 14 of 49 planned observations; it does not prove general results.
The project distinguishes observed facts, corroborated evidence, verified findings, hypotheses and unknowns. Claims are strengthened only as evidence strengthens.
Research pipeline
Canonical entities
AIO CODE maintains distinct canonical entities and explicit relationships. A relationship connects identities; it does not collapse them.
Method component: research cycle
Observation → Research Question → Hypothesis → Experiment → Baseline → Intervention → Measurement → Comparison → Evidence Classification → Interpretation → Finding → Replication / Refinement.
Individual experiments follow a controlled sequence: define the entity, observe, record, formulate the research question, state a hypothesis, implement an intervention, measure, compare, classify evidence, interpret and preserve the finding.
Open research infrastructure
Phase-2 components, implementation status and validation boundaries.
Read the system specificationVersioned research architecture, entity records, schemas, observations, experiments, metrics and controlled export definitions.
View repositoryMachine-readable downstream representation of the controlled AIO CODE entity and research data export.
View datasetEntity readiness check
Use the free self-check to review identity records, evidence, cross-platform consistency, provenance, rights and observation readiness. It does not query external AI systems or predict visibility.
Public evidence search
Explore the approved first-party sources with exact file and commit references. Search results are candidate passages, not a claim that outside AI systems recognize the entity.