Discovery you can trace to the figure.
Figure 3
Fig. 3. A single concept node — Discovery — connected to its grammatical neighbours under the Elman knowledge graph. Edges denote co-occurrence in the substantive sentence; weight reflects semantic proximity to the focal node.
A collaboration with the Allen Institute for Brain Science — full architectural reveal of the discovery engine, validated against single-cell data in human substantia nigra.
Every finding anchored to a specific experimental arm in a specific paper or in-silico run — never to a model's parametric memory.
The reasoning agent chases specific questions through the graph one edge at a time, surfacing low-magnitude but significant signal where the tractable biology lives.
A single schema across literature, in-silico and wet-lab evidence. Every result sharpens the substrate every future run consumes — across indications, not within one.
The discovery flow
Each step lives on the same compounding knowledge graph. Two are sold as standalone services right now; the rest run end-to-end in beta.
Public datasets, literature, and in-silico runs land in a single Neo4j graph at arm-level resolution.
Multi-agent traversal proposes mechanistic hypotheses, each verified concurrently against the literature.
Rational pruning surfaces candidate intervention points at sub-population resolution — for any indication.
Propagate the intervention through the graph to predict cohort and sub-population response.
Freedom-to-operate, patent landscape, and engineering mitigation on the target, asset, or technology area.