Role in Valnative AI OS for Retail
Define retail business context
This is one component of the platform. A working product does not establish that every cross-product handoff or retailer integration is available.
// Reference & substrate
RetailAsset.
MVP readyThe canonical retail taxonomy and ontology: versioned reference snapshots, package locks and seed packs that keep every product speaking the same retail language.
Inputs and outputs
Inputs: Reference processes, entities, KPI definitions and scope.
Outputs: A shared retail reference model for downstream decisions and data work.
Problem & who it’s for
Every retail-tech product reinvents its own semantic layer — categories, KPIs, processes — and the copies drift. Semantic sprawl quietly breaks integrations and makes every number disputable.
Offer & core workflow
RetailAsset maintains one canonical retail taxonomy/ontology with versioned snapshots, package locks and compiler seed packs. Downstream products consume reference slices instead of building local semantic cores.
What exists now
- Retail taxonomy, ontology and versioned reference snapshots.
- Package locks and compiler seed packs consumed by design-time tooling.
Next milestones
- Complete the source-to-package update process with governance gates.
- Standardize the boundary contract with the client semantic-mapping substrate.
Connections in the platform
Directional value exchanges with explicit implementation status, separating current capability from the roadmap.
- RetailAsset → DecidRA — reference scope and candidate decision packages. Partially implemented
- RetailAsset → BoardRA — reference slices and compiler seed packs. Partially implemented
- RetailAsset → stratifyx — reference package IDs for SMB diagnostics. Planned
Talk to us about RetailAsset.
Bring the workflow, data and systems you have in mind. We can discuss current availability, an appropriate demonstration and the work needed to assess a fit.
More in Retail decision intelligence