graphify

You can build a knowledge graph by applying deterministic extraction to folders of code, documents, and media, transforming them into navigable nodes and edges. It requires no external dependencies and outputs query-ready formats for immediate analysis.

Cross-format knowledge graph workflows analyze relationships in research papers and video transcripts by applying optional transcription and semantic extraction, creating a unified navigable structure with dependency audit trails.

You can perform community detection and shortest path queries directly on a repository analysis graph. The process supports graph queries and explanations to investigate clusters and trace dependencies across project content.

Knowledge graph generation extends beyond codebases to process images and videos. It applies optional transcription to media files alongside code and documents, creating a comprehensive navigable structure across formats.

Generated knowledge graphs output as portable HTML visualizations, GraphRAG-ready JSON for retrieval, and markdown reports. These formats enable immediate reuse across querying tools and cross-format exploration workflows.

Incremental rebuilds use cache-aware processing to update a project knowledge graph. This mechanism ensures only modified content undergoes re-extraction, making updates faster while maintaining deterministic relationship outputs.