Unstructured

SAP selected Unstructured after evaluating ten providers to power document ingestion and preprocessing across its global generative-AI stack in a multi-year partnership, demonstrating a specifically identified production-scale enterprise integration beyond general customer-list evidence.

Unstructured is used by Fortune 500 teams and serves as document ingestion/preprocessing infrastructure for organizations including SAP, IBM, Intel, Teradata and Uniphore.

Unstructured is used by Fortune 500 teams and serves as document ingestion/preprocessing infrastructure for organizations including SAP, IBM, Intel, Teradata and Uniphore.

Unstructured supports 65+ file types with layout-aware parsing, OCR, table preservation, multimodal extraction, connectors and production-scale transformation for agent and RAG pipelines.

Unstructured supports 65+ file types with layout-aware parsing, OCR, table preservation, multimodal extraction, connectors and production-scale transformation for agent and RAG pipelines.

Unstructured introduced a schema-driven Extract enrichment that transforms heterogeneous documents into validated structured records rather than only retrieval chunks, extending its existing partition-chunk-embed architecture to direct operational database ingestion.

Unstructured's March 2024 company announcement disclosed a $40 million Series B led by Menlo Ventures, bringing total capital raised to $65 million. This historical financing is independent of the previously documented enterprise integrations and does not establish current liquidity.

Unstructured has strategic platform integrations and OEM relationships with SAP, IBM, Teradata, Microsoft Azure and other enterprise infrastructure ecosystems.

Unstructured has strategic platform integrations and OEM relationships with SAP, IBM, Teradata, Microsoft Azure and other enterprise infrastructure ecosystems.

Unstructured spans multimodal ingestion and transformation for documents, images, tables and enterprise content; its platform integrates with vector databases, data warehouses, object stores and major cloud/AI ecosystems, supporting portability across data engineering, RAG, document AI and AI-platform roles.

Document intelligence, ETL, parsing, RAG, multimodal preprocessing and data infrastructure skills transfer exceptionally broadly across enterprise AI and agent platforms.

Document intelligence, ETL, parsing, RAG, multimodal preprocessing and data infrastructure skills transfer exceptionally broadly across enterprise AI and agent platforms.