Hyland, the pioneer of the Content Innovation Cloud ™, is announcing the launch of Knowledge Enrichment, a breakthrough innovation that transforms unstructured enterprise content into AI-ready data. Designed to eliminate one of the most persistent barriers to AI success — poorly structured, fragmented content from documents and images to audio and video — Knowledge Enrichment transforms raw data into clean, contextualized, and intelligently structured information. This empowers AI agents and automation workflows to understand, reason, and act with confidence across diverse content types, enabling every layer of the Content Innovation Cloud to operate with deeper understanding and better governance from Knowledge Discovery to Agentic Solutions.
“Organizations are rapidly adopting AI agents and automation, but without properly connecting their unstructured content and data, these AI-driven workflows consistently fall short of expected business outcomes,” said Michael Campbell, chief product officer at Hyland. “Knowledge Enrichment solves this fundamental challenge by transforming content, creating the structured, contextually rich data foundation that AI agents need to deliver meaningful business value. This innovation represents our continued commitment to ensuring the Content Innovation Cloud provides the most sophisticated content intelligence capabilities available.”
Hyland Knowledge Enrichment Key Differentiators:
Unlike approaches from other vendors, which primarily focus on enhancing user experiences or modernizing legacy systems, Hyland Knowledge Enrichment transforms raw unstructured content into AI-ready, intelligently structured data. This enriched content enables large language models (LLMs) and autonomous agents to understand, reason, and act across every layer of enterprise operations.
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Here’s how Hyland stands apart:
- Multimodal enrichment (text, images, audio, video) pulls structure, semantics, and content directly from files using deterministic extraction
- Data catalogs can be enabled to consistently manage enriched metadata for unstructured and structured data
- Deep integration with governance and content workflows in the Content Innovation Cloud
Federated, Flexible, Future-Ready
Whether content lives in a content lake, enterprise content management (ECM) platform, or across federated repositories, Knowledge Enrichment delivers value by bringing clarity to chaos. It preserves layout, semantics, and relationships that are critical for AI systems to accurately interpret, reason, and act on information. With Hyland‘s decades of experience in content-intensive industries, it delivers industry-aware data transformations that meet the needs of sectors like healthcare, insurance, financial services, government, legal, and compliance.
Knowledge Enrichment delivers breakthrough capabilities that directly enhance AI effectiveness across the enterprise:
- Preserve Document Meaning and Context: Extracts intelligence from 600+ file formats while maintaining original structure, layout, and semantic meaning, which is crucial for downstream AI understanding and accuracy.
- Deep Contextual Structuring: Structures and enriches content beyond traditional metadata, transforming documents, images, audio, and video into structured outputs such as labeled entities, tables, summaries, and semantic tags, alongside embeddings and vector representations that large language models can interpret with nuance.
- Seamless Enterprise Integration: Converts unstructured content into enriched, structured data that integrates seamlessly into enterprise data lakes, catalogs, and analytics pipelines. This empowers data scientists and engineers to build and deploy AI models more efficiently using trusted, context-rich inputs that reduce data preparation and improve model accuracy.
Accelerating AI-Readiness and Deployment
Knowledge Enrichment is an API-first solution that integrates directly into any enterprise AI workflow, enabling data engineers, data scientists, and developers, to fine-tune their own LLMs or deploy AI agents that act with deeper context and relevance. It supports low-code tools and workflow platforms, allowing both technical and business users to tap into enriched metadata without friction.
- Improve AI Accuracy: Structured, enriched data enables more context-aware reasoning and better decision-making from AI systems.
- Simplify AI Deployment: Reduces the need for manual data preparation and accelerates model training and deployment.
- Scale with Confidence: Provides a consistent, AI-ready content foundation that supports automation, analytics, and LLM integration across the enterprise.
Source: PRNewswire