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A vectorless, reasoning-based retrieval engine for RAG that extracts verifiable answers from long, complex documents without embeddings, chunking, or vector databases. It is for developers and data teams in businesses that need to analyze domain-specific documents such as financial, legal, healthcare, and technical files, with enterprise-grade deployment options. It is positioned against vector-database RAG by using logical reasoning over document structure with page and section references instead of semantic similarity search.

Key features

• Reasoning-based retrieval without embeddings
• No chunking preserves document structure
• No vector database required
• Retrieves all relevant passages without top-K
• Traceable retrieval with page references
• Explainable reasoning-driven retrieval
• Context-aware retrieval with full context
• Human-like table-of-contents navigation
• Lightweight JSON tree index
• MCP and API access
• Streaming retrieval during generation