⌘K
3 total · 1 independent · 2 dependent
Select a claim to edit
Select a claim from the tree to edit
Or add a new claim to get started
Invention: A computer-implemented system and method for converting unstructured electronic documents into a unified, self-contained container format ("Agent Document Format" or ADF) that AI agents can instantly parse, query, and reason over without redundant reprocessing. The system employs a multi-stage pipeline comprising: (1) text extraction with positional and typographic metadata; (2) heuristic-based structural detection of headings, sections, tables, and references; (3) large language model (LLM) semantic enrichment including summarization, entity extraction, document classification, and knowledge graph construction; and (4) vector embedding generation for each semantic chunk. All resulting artifacts -- the original document, structured semantic data, agent-oriented metadata, a knowledge graph, pre-computed vector embeddings, and conversion benchmarks -- are packaged into a single compressed archive file. The container format eliminates the need for downstream AI agents to independently re-extract, re-analyze, or re-embed document content, yielding substantial reductions in processing time, API token consumption, and computational cost.