Transform raw, fragmented inputs into canonical, agent-ready intelligence. The missing primitive for the AI agent economy.
The AI agent economy requires a universal data foundation. Today’s data is unstructured, inconsistent, and incompatible across systems. Canonical3 introduces the Canonical Layer : a normalization framework for transforming documents, datasets, and sensor signals into canonical, queryable, interoperable intelligence.
AI agents depend entirely on the data they consume. While models have advanced rapidly, the data feeding them has not. There is no universal schema, no consistent normalization, no canonical layer.
Operational knowledge lives in PDFs, slides, and emails without typed attributes or lineage.
GPS and IoT feeds produce raw signals lacking canonical semantics or context.
Normalizing patient history documents.
Standardizing SLAM and spatial data.
Automating policy verification rules.
Unifying logistics manifests.
Vectorizing internal knowledge bases.
Merging satellite and drone telemetry.
The universal primitive. Normalizes inputs before they touch compute or models.
Canonical3 unifies the stack by providing the trusted memory layer for all upstream agents.
Creators of canonical datasets receive perpetual reward flows. Each query generates token-based yield routed to canonical data owners, creating a self-sustaining economy of high-quality intelligence.