Excalibur

Excalibur is a specialized web interface and computational engine designed for high-fidelity table extraction from PDF documents, built atop the Camelot framework. By 2026, it has solidified its position as the premier bridge between unstructured document layouts and structured data pipelines for enterprise ETL (Extract, Transform, Load) processes. Unlike standard OCR tools that treat documents as flat images, Excalibur utilizes spatial analysis to detect cell boundaries via two primary methods: 'Lattice' (for visual borders) and 'Stream' (for whitespace-delimited layouts). This dual-engine architecture ensures 99% accuracy in preserving table structures during conversion. The technical architecture supports a decoupled stack, allowing for localized deployments where data privacy is paramount, or cloud-native instances for high-throughput batch processing. Its 2026 market position focuses on 'Human-in-the-loop' (HITL) workflows, allowing data scientists to refine detection parameters through an intuitive UI before committing to large-scale automation. As LLMs evolve, Excalibur provides the essential ground-truth structured data required for RAG (Retrieval-Augmented Generation) systems that rely on precise tabular information from legacy corporate documents.