Knowledge architect, AI engineer
MarketBrew Reference Manual
A structured knowledge base of evidence-tagged atoms, turned into an exhaustive client reference manual.
An exhaustive, client-ready reference manual for MarketBrew (a deep SEO analytics platform), generated from a structured knowledge base. We extracted MarketBrew’s public reference material into evidence-tagged "knowledge atoms" through a parallel multi-model pipeline, then built the manual from that vetted database under strict schema and QA gates.
The problem
MarketBrew is a deep, technical platform whose knowledge is scattered across public docs, optimization guides, and patents. It is hard to learn and slow to reference. The goal was a single authoritative reference that was accurate, evidence-backed, and complete, not a loose summary.
What we built
We extracted the source material into a structured database of "knowledge atoms," each tagged with its supporting evidence, via a high-throughput pipeline that dispatched extraction across multiple models (Claude, ChatGPT, and Gemini) under strict evidence standards, schema compliance, and QA gates. The vetted atom database then generated the exhaustive, versioned reference manual delivered to the client.
What was delivered
- Structured knowledge-atom database built from MarketBrew public references
- Multi-model extraction pipeline with evidence standards, schema, and QA gates
- Exhaustive, versioned client reference manual generated from the database
- Glossary and sources index
Outcomes
- A single authoritative, evidence-backed reference for the platform
- Every claim in the manual traces back to a sourced knowledge atom
- A repeatable extraction pipeline for future source material
- The knowledge base the Oracle Agent was later built on
Services: Knowledge architecture, Knowledge-atom extraction, Multi-model pipeline, Technical documentation, QA gates