Unstructured has formed a strategic partnership with Teradata, a leading enterprise data company, to bring advanced data ingestion and processing capabilities directly into Teradata Enterprise Vector Store. This new integration, which is anticipated to be available to eligible Teradata customers starting as early as April 2026, allows organizations to automatically ingest, process, and convert unstructured content into high-quality, AI-ready data without the need for additional infrastructure in most environments.
Through this collaboration, Unstructured’s document preprocessing and enrichment technology is embedded natively as a service within Teradata Enterprise Vector Store. This allows enterprises to ingest and transform unstructured data-including documents, PDFs, spreadsheets, emails, images, video and audio files-within the same environment used for structured analytics. Processed outputs are delivered directly into Teradata Enterprise Vector Store as vectors, structured data or a combination of both.
“This partnership is a validation of what we’ve been building toward: making unstructured data processing a core part of the enterprise data stack,” said Brian Raymond, Founder and CEO of Unstructured. “Teradata’s customers run some of the most demanding, highly regulated workloads in the world. Embedding our platform inside Teradata Enterprise Vector Store means those customers can now unlock their unstructured data for Gen AI with the same governance, security, and operational rigor they expect from everything else in their environment.”
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Unlocking Enterprise Data for Generative AI
Industry estimates suggest that nearly 80% of enterprise data exists in formats not readily usable by AI systems, such as PDFs, images, videos, scanned documents and email archives. The integration enables organizations to convert this information into structured formats suitable for AI-driven applications.
Unstructured’s platform can preprocess more than 70 file types, converting them into chunked JSON data while generating production-grade embeddings directly within Teradata Enterprise Vector Store. These capabilities help enterprises quickly transform large volumes of content into data ready for retrieval-augmented generation (RAG), hybrid search, agentic AI workflows and advanced analytics.
The integration also supports Teradata’s hybrid deployment model, which gives users access to all major cloud providers including Amazon Web Services, Microsoft Azure, and Google Cloud, as well as on-premises environments and air-gapped environments. This is particularly important for industries such as financial services, healthcare, defense, and government, where data sovereignty dictates where data can be processed.
“Our customers manage some of the world’s most complex, regulated data environments, and they need AI-ready data they can trust,” said Sumeet Arora, Chief Product Officer at Teradata. “Unstructured brings the depth of production-grade preprocessing our customers need—delivered natively inside Teradata Enterprise Vector Store across multi-cloud and on-premises environments. That means the reliability, governance, and compliance they require, with the flexibility to deploy wherever their data lives—without adding complexity or additional tools to their existing environment.”