Discover thematic overlaps, structural patterns, and hidden connections across your knowledge base.
Find thematic connections, structural patterns, and unexpected overlaps across documents, conversations, and extracted outputs. Keimenon reveals how your knowledge connects — surfacing relationships that manual browsing would never find.
| Discover | Cluster | Connect |
|---|---|---|
| Find thematic overlaps across documents, conversations, and extracted outputs. | Group related concepts into emergent topic clusters automatically. | Surface relationships between ideas across disparate sources and time periods. |
Intuition tells you that an idea from three months ago connects to something you read last week. But across thousands of documents and conversations, finding the specific connection is nearly impossible.
You could tag every document with themes and topics, but it's inconsistent, incomplete, and biased by what you think is relevant at the time. Automatic similarity detection surfaces connections without manual curation.
Every new document enters as an isolated file. Without similarity detection, it never joins the network of existing concepts — even when it directly relates to material you already have.
Beyond keyword matching — Keimenon analyses the meaning and structure of content to find thematic connections even when different terminology is used.
Related material is automatically grouped into emergent clusters. Clusters evolve as new content enters the corpus — they're not static categories but living organisational structures.
A concept in a document connects to the same concept in a conversation connects to a related concept in extracted code. Similarity detection works across source types, not just within them.
Track how themes develop over time — which concepts recur, which evolve, and which connect to new domains. Temporal analysis reveals intellectual development across months or years.
The graph surface where similarity relationships become navigable connections between concepts, entities, and sources.
The organised corpus provides the structured content that similarity analysis operates on.