document-enricher

Document enrichment merges original content with new research findings to produce versioned iterations. It generates enriched Markdown files and updates knowledge graph nodes, keeping original documents intact while refreshing reference materials across SDLC phases.

Updating a knowledge graph with new research involves merging findings with original documents to produce versioned enrichments. The workflow generates enriched Markdown, creates corpus nodes, and applies updates to the index and graph automatically.

Yes, you can refresh outdated internal wiki documents while preserving originals by running an enrichment workflow. It creates versioned enriched Markdown iterations with new findings, maintaining a history of updates while keeping original files intact.

To start enriching documents, you need a document entry from your index and a JSON research payload. Supplying these inputs to the workflow generates an enriched Markdown file, enrichment metadata, and a new corpus node for graph indexing.

Document enrichment supports both automatic and manual workflows. Automatic mode detects related documents and merges findings to create enriched files, while manual workflows let you supply specific document entries and research payloads to control the process.

You should avoid automated document enrichment when no related research exists to refresh the reference materials. The workflow applies specifically when new research findings are available to merge with original content across SDLC phases.