Enables AI assistants to analyze documents larger than their context window by loading files into RAM and querying them via search, navigation, and Python execution tools. Supports recursive reasoning to process massive datasets in chunks using sub-agents.
Enables AI agents to efficiently process large local and online PDFs through selective extraction of text, images, and metadata. It provides tools for content search and document outline navigation to optimize context window usage.
Enables document Q&A and knowledge retrieval through hybrid semantic and keyword search, with tools for document ingestion, chunking, summarization, PII redaction, and RAGAS-based evaluation.
Enables processing and analysis of large PDF files through text extraction, search functionality, and intelligent chunking strategies. Provides comprehensive PDF operations including metadata retrieval, page-range text extraction, and content search with contextual results.
Provides AI agents with document conversion to Markdown, intelligently routing small and large files, and enabling targeted extraction via sections, search, and token budgets.
Provides AI agents with comprehensive document parsing capabilities including PDF text extraction, OCR, HTML-to-markdown conversion, table extraction, and summarization, optimized for agent workflows.
