Uthereal K2M Interface turns expertise into a machine-readable mind.
Uthereal — Knowledge-2-Machine Interface & Ontology. Drop a research PDF anywhere on this field and watch the scattered dots align into seven interlocking layers, each grounded in the source span it came from.
✦ Try the Replication Agent/ the value escalator
corpus to knowledge-product categories.
Each layer above answers a question the layer below cannot — and commands a higher price for the Knowledge Product.
How does the system get smarter as it's used?
Recurring intelligence subscription
What does this mean for our specific portfolio and context?
Enterprise customer platforms
What does the corpus say? Where is consensus, where is contradiction?
State-of-the-field intelligence
What does each paper actually assert, with what evidence?
Claim-level data licensing
What drugs, diseases, methods are mentioned?
Annotated corpus feeds
What papers exist on this topic?
TDM API — text access
Substrate layers stay open and interoperable. Superstructure layers are proprietary value.
/ the ontology stack
From substrate to apps.
Every layer rests on the spans below it. Base layers preserve the document, knowledge, and evidence. The structure store reasons across the corpus. Apps (L7) sit on top — re-runnable workflows that pull attributes from any layer.
Apps & Actions Layer
L7 — Where knowledge becomes work
Proprietary Layer
L4 · L5 · L6 — Your private intelligence stack
Interoperability Layer
L1 · L2 · L3 — Standards-aligned, grounded base
/ inspect each layer
Click to expand attributes
/ implementation
Ontology Implementation Dictionary
Every attribute across the seven layers, with the inputs it consumes, the formula or extractor that produces it, and the shape of its output. This is the contract the pipeline writes against.