Ingest and preprocess complex natural language data from any document, file type or layout. Under the hood, the Unstructured engine involves breaking a document into its constituent parts and identifying the document's structure, such as its header, tables, body text, and more. Unstructured provides diverse preprocessing strategies for documents each catering to different document types and requirements. Utilizing the optimal strategy enhances document element classification accuracy and extraction efficiency, crucial for image-based files and layout-intensive documents. Key Benefits: Transform all your data for downstream analytics Next-generation vision transformer for images, PDF, and table extraction Enhanced models for table extraction, document hierarchy and element classification Chunk your data for LLM applications Compatible with any embedding model, vector database and LLM framework API client libraries in multiple client languages (eg Python, Javascript) No data storage Data is secure Reduce compute costs and enhance quality of inferences