Kudra Information

Kudra solves the fundamental problem with agentic and RAG systems: direct LLM ingestion destroys document structure and creates noisy analysis. The Problem: Most RAG and agentic systems fail on complex documents. Chunks lose context, tables break, cross-references disappear, and models waste capacity parsing formatting instead of reasoning. The result: poor quality, high token costs, and queries that require synthesis simply don't work. Our Solution: We use custom trained AI document intelligence to transform documents into structured, multi-layer knowledge: → Extract accurate information from PDFs and scanned images including tables, text using OCR, checkboxes, images, etc. → Entity/relations extraction: extract any entity and relation from any document → Enrich: Comprehensive, LLM-generated analysis → Cross-document intelligence: Relationships and patterns that span your corpus → Visual grounding: Always available for human-in-the-loop verification THE RESULT: - 7-10x reduction in inference tokens - Superior quality on complex analytical queries - Cross-document reasoning that actually works - Consistent performance at any scale - Table data becomes fully searchable Who we serve: Organizations with serious document problems—complex submissions, dense reports, technical documents, multi-document analysis.