Redirecting to WHL Knowledge Layer...

536,264 documents indexed. 22GB SQLite corpus. FTS5 full-text plus semantic vector search using 768-dimensional embeddings. Flask query interface, self-hosted. Deep coverage of physics, mathematics, cryptography, philosophy, signal processing, and governance systems. Queryable today; productization path identified as the Canon Concepts Knowledge Graph SKU.

How the Knowledge Substrate Works

A 22GB indexed research corpus with hybrid full-text and semantic retrieval.

The substrate stores 536,264 documents in a SQLite corpus with two retrieval paths working in parallel: SQLite FTS5 for exact-term and lexical search, and a 768-dimensional vector store for semantic similarity. Queries hit both. Results carry document provenance and an integrity-anchored corpus reference.

FTS

Full-Text Search (FTS5)

SQLite FTS5 over the full document corpus. Exact-term, phrase, and lexical queries. Useful when the researcher knows the term they need and wants the citing documents back, ranked.
SEM

Semantic Vector Search

768-dimensional embeddings. Concept-level retrieval, query in natural language, recover documents that share semantic neighborhood without sharing surface terms.
MINE

Concept Mining

Deep coverage across physics, mathematics, cryptography, philosophy, signal processing, and governance systems. Useful for R&D teams running prior-art sweeps, decision warehousing, and concept-cluster analysis.
PROV

Document Provenance

Every returned document carries its source path within the indexed corpus. Researchers can trace a result back to the originating file. No floating snippets.
SHA

Hash-Anchored Corpus Integrity

The corpus is integrity-anchored via SHA-256. Tamper events are detectable. The substrate is the same artifact every researcher queries, not a moving target.
UI

Flask Query Interface

Lightweight self-hosted Flask surface, query box, hybrid result panel, provenance link, integrity status. Researchers can be working against the substrate inside an afternoon of access provisioning.
API

Queryable Today

The substrate is online and queryable. Pilot access surfaces the Flask UI and a structured-query path suitable for downstream tooling. No long productization wait for first-value.
SKU

Canon Concepts Knowledge Graph SKU

Productization path is identified: the Canon Concepts Knowledge Graph SKU layers concept extraction and graph navigation on top of the indexed substrate. Pilot customers shape the SKU.
DOM

Domain Coverage

Physics, mathematics, cryptography, philosophy, signal processing, and governance systems. The substrate is broad enough to support cross-domain queries, exactly the queries R&D labs and IP firms care about.

Why the Substrate

A corpus you can search, cite, and trust the integrity of.

Research teams already have vector databases. They already have full-text search. What they do not have, often, is a single integrity-anchored corpus where the document set under query is provable across sessions and across reviewers.

Hybrid Retrieval

FTS5 plus semantic vectors in the same query path. Lexical precision when you know the term, semantic recall when you don't. One result panel, two index types.

Integrity-Anchored

Corpus carries a SHA-256 anchor. Two reviewers running the same query against the same anchor get the same document set. Audit trails over research workflows become possible.

Productization Path Identified

Canon Concepts Knowledge Graph SKU layers concept extraction and navigation on top. Pilot customers shape what gets prioritized, extraction, ontology, graph UI, or export contract.

Verified Output

Tests pass. Receipts on disk.

Health check on the live knowledge substrate.

$ python tools/health_check.py
Connecting to ACTIVE_KNOWLEDGE.db (22.0 GB)...
Total documents:      536,264
FTS5 index status:    ready
Embedding coverage:   128,256 / 536,264 (semantic)
Sample query "phi":   6,206 hits in 12 ms
Sample query "consciousness": 6,070 hits in 9 ms
Flask UI status:      running
Corpus SHA-256:       [anchored, verifiable on request]

Verified live: 536,264 documents indexed, FTS5 + 128K semantic embeddings, self-hosted. Corpus hash anchored.

A 22GB indexed research corpus with hybrid full-text and semantic retrieval.

A corpus you can search, cite, and trust the integrity of.

Enterprise license inquiry. Scoped to seat count and corpus footprint.

Research labs, federal R&D, decision warehouses, IP firms.

Tests pass. Receipts on disk.

Query a 536K-document integrity-anchored corpus.