Most knowledge sits in folders — isolated, disconnected, impossible to cross-reference. The Knowledge Graph turns an entire corpus into a living, interactive map where ideas find each other.
It runs entirely on your own infrastructure. Nothing leaves.
A traditional filing system forces every document into one folder, severing the connections that matter most. The Knowledge Graph reads meaning — not just keywords — and positions related work side by side.
Like a mapping application, you move from a continent-wide overview down to a single street — each level revealing more detail.
Open the graph and you see thematic groups as coloured circles. A circle's size reflects how many documents it holds; related themes naturally sit close together.
Click any group to see every document within it. Lines show how similar documents are — brighter, thicker lines mean stronger relationships. Open any node for a full dossier: metadata, key concepts, an excerpt, and all of its connections.
The most valuable discoveries: how a single document connects to work filed in completely different categories. An environmental paper revealing strong ties to a human-rights document — a link a folder structure would never show.
Each tool offers a different way to interrogate the corpus — turning hours of manual cross-referencing into a single click.
Surfaces documents from different groups that are highly similar yet were filed apart — the connections a folder structure would never reveal.
Identifies concepts that recur across many groups. A term appearing in fifteen groups is a meta-theme — a pillar that transcends categories.
Toggle the key topics of any group on and off to narrow a large cluster down to exactly the documents that matter.
A diagnostic on every group — similarity, density, orphaned documents, and cross-group bridges — showing what is strong and what needs attention.
Search by meaning, not keywords. Ask for "climate policy" and also find "environmental regulation" and "carbon frameworks" — matches glow on the map.
Tune the minimum-similarity threshold to reveal or simplify connections, and save or restore an exact research state at any time.
Three analytical engines run continuously, computing insight about the structure of your knowledge base — not just drawing it.
Some documents act as critical intersections, connecting clusters that would otherwise be isolated. The graph identifies these high-centrality nodes and renders them larger — the load-bearing pillars of your corpus.
Highly similar documents that were classified into different groups represent structural gaps — missed connections. Surfacing them reveals research opportunities and cross-disciplinary insight hiding in plain sight.
By scanning for concepts that appear across every category, the graph distils the fundamental themes that hold an entire body of knowledge together.
Switch lenses depending on the question — exploration, structure, or systematic audit.
An interactive, force-directed map where similar documents cluster naturally. Best for exploring relationships and stumbling on the unexpected.
A hierarchical tree of a group — its documents, their top concepts, and strongest links. Best for understanding internal structure.
A sortable, spreadsheet-style audit of every document and its metadata. Best for systematic review at scale.
The entire graph is computed and explored on your own infrastructure. No cloud service is required; no document, query, or discovery is sent to an external server. For sensitive research, proprietary strategy, and confidential policy work, that is not a feature — it is a precondition.
The same principle that governs the entire Digital Brain.
The Knowledge Graph is one capability of the Ethos Digital Brain — the governance-grade intelligence system behind our assessments.
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