Unstructured has partnered with Teradata to embed its data processing platform natively within Teradata Enterprise Vector Store. This integration allows enterprises to ingest, preprocess, and transform unstructured content—such as documents, PDFs, spreadsheets, emails, images, video, and audio—into high-quality, AI-ready vectors and structured data directly inside the Teradata environment, eliminating external tools, pipelines, or additional infrastructure in typical deployments.
Quick Intel
This native integration empowers Teradata customers to unlock the estimated 80% of enterprise data trapped in unstructured formats, enabling secure, scalable use in hybrid search, retrieval-augmented generation (RAG), agentic AI, and traditional analytics within a trusted, compliant platform.
Enterprises face significant challenges in making unstructured content usable for AI applications. Traditional approaches often require fragmented tools, external ingestion services, and complex pipelines that introduce security risks, compliance gaps, and operational overhead. By embedding Unstructured directly into Teradata Enterprise Vector Store, the partnership delivers preprocessing—parsing, enrichment, chunking, and embedding generation—as a core platform service.
All processing occurs within the same environment used for structured analytics, ensuring data never leaves the controlled perimeter. Outputs land as vectors or structured data ready for immediate consumption in AI-driven use cases, while maintaining alignment with Teradata’s governance framework.
Brian Raymond, Founder and CEO of Unstructured, stated: “This partnership is a validation of what we’ve been building toward: making unstructured data processing a core part of the enterprise data stack. 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.”
The integration supports Teradata’s flexible hybrid model, allowing processing to occur wherever data resides—multi-cloud, on-premises, or air-gapped—critical for sectors with strict data sovereignty requirements. Features include deterministic outputs for reliability, role-based access controls preserved in embeddings, and compliance with enterprise standards.
Sumeet Arora, Chief Product Officer at Teradata, added: “Our customers manage some of the world's most complex, regulated data environments, and they need AI-ready data they can trust. 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.”
This collaboration simplifies the path to production-grade GenAI by consolidating ingestion, preprocessing, and vector storage into a single, governed platform, reducing time-to-insight and operational risk for large-scale enterprise deployments.
About Unstructured
Unstructured is the leading enterprise platform for transforming unstructured data into AI-ready formats. The company’s platform ingests, preprocesses, and delivers data from 70+ file types and 30+ enterprise data sources, powering production GenAI and agentic AI workflows for organizations worldwide. Unstructured supports flexible deployment across multi-tenant SaaS, dedicated instance, and customer-managed environments including VPC and on-premises. The platform is SOC 2 Type II, ISO 27001, HIPAA, and GDPR compliant, with FedRAMP High authorization and Authority to Operate (ATO) at Impact Level 5 (IL5).
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