We turned academic papers, market reports, and regulatory documents into a living, interlinked knowledge base of 146 cross-linked pages using a four-stage process, then hardened it with an integrity layer. Here's how it works at a high level.
01 - Extract
We studied the document archive and identified the knowledge structures buried inside: entities (companies, regulators, labs), products (peptides, therapeutics), markets (segments, pricing, access channels), and concepts (mechanisms, delivery methods, regulatory frameworks). Each source was read once, deeply, and the key information was pulled out - not summarized, but structurally decomposed into atomic fragments.
02 - Structure
We designed custom templates for each page type - product, concept, entity, market, source - so every fragment follows a consistent schema. A product page always has the same fields. A market page always has the same sections. This consistency is what makes the system compoundable: new information slots into a known structure instead of floating as unstructured text.
03 - Connect
Every fragment was cross-linked into an interlinked knowledge graph. A company mentioned in three reports gets one page with three sources. A peptide referenced across a clinical paper, a market report, and a regulatory notice gets all three perspectives unified on a single page. Contradictions between sources are flagged, not hidden. The graph view reveals clusters, gaps, and relationships that no single document could show.
04 - Compound
With the base built, every new source and every new question strengthens the whole. A query about "commercially in-demand peptides" draws on 50 product pages, 7 market analyses, and 10 entity profiles to produce an answer no single search could replicate - and that answer gets filed back into the wiki, making the next query even richer. The knowledge compounds.
The integrity layer
A knowledge base is only useful if you can trust it. Every claim carries its source and a confidence tier - peer-reviewed, official, or practitioner - and nothing is stated as fact without provenance. Regulatory-status claims must cite a primary authority; anecdotal and grey-market sources are quarantined, never laundered into fact.
Before any new claim is saved, a skeptic pass attacks it: single-source hype and contradictions get flagged, not filed. In this build, it caught an unverifiable clinical-trial statistic circulating in secondary coverage and refused to promote it to fact - leaving it marked as unverified until a primary source confirms it. A regression test runs on every update, so if a fact silently changes, a red check catches it. The base is auditable and self-checking - and it can't quietly rot.
The result: 146 interlinked pages - including 50 product pages, 23 source summaries, 39 concept deep-dives, 7 market analyses, and 10 entity profiles - all cross-linked, all source-tiered, all regression-checked, all browsable in Obsidian or any markdown reader. 1,131 internal links, 100% resolving; 11 golden-fact checks, all green. This was the first build - the one where the method was invented, over three months. Once it was an engine, the fourth knowledge base took a single day.