graphify-windows

You can convert a folder into a knowledge graph by running an extraction pipeline that processes code, documents, and media files to generate a persistent graph with auditable edges, community clusters, and navigable outputs.

Visualizing project connections is best achieved by exporting an interactive HTML view from your folder, transforming scattered code and documents into a navigable knowledge graph that reveals clusters and workflows.

GraphRAG-ready JSON works by structuring extracted entities and auditable edges from your document analysis into a queryable format, enabling downstream retrieval-augmented generation tasks over your project folder's knowledge graph.

Yes, you can build a graph from mixed media and research papers by running the extraction pipeline, which applies deterministic entity extraction across diverse file types to reveal connections and clusters within research folders.

No, graphify-windows requires no specific dependencies to analyze project folders, allowing you to directly process code, documents, and media into a persistent knowledge graph with community detection and an auditable edge trail.

While effective for codebase analysis, a knowledge graph relies on deterministic extraction, meaning complex or ambiguous logic may require manual review of the auditable edge trail and plain-language report to ensure accurate workflow mapping.