Unstructured data is everywhere — emails, contracts, reports, customer interactions, scanned documents and more. Unlike structured data, which fits neatly into databases, unstructured content is highly variable, making it difficult to organize, analyze and integrate into business processes.
The sheer volume is staggering: 80% of enterprise data is unstructured, and it is spread across multiple systems — on average, 21 different repositories within an organization, according to a Hyland-commissioned Forrester study.
This fragmentation of critical content across repositories creates significant challenges, including:
Despite these challenges, unstructured data holds enormous potential. When processed correctly, it becomes a goldmine of insights, fueling AI-driven decision-making, automation and solution building.
The key to unlocking the potential of unstructured data Knowledge Enrichment.
Knowledge Enrichment is a data management suite that transforms raw, unstructured content into meaningful, structured data that is ready for use in AI, automation, analytics and solution-building. This involves extracting key entities, applying metadata, linking contextual information, and ensuring content is machine-readable and actionable from the outset.
Knowledge Enrichment consists of two key components:
Instead of relying on multiple postprocessing steps to clean and structure data, Knowledge Enrichment embeds intelligence early in the workflow, ensuring content is optimized for downstream applications as soon as it is ingested.
The Knowledge Enrichment API is powered by a combination of robust technologies and automation capabilities that ensure high-quality structured data output:
Document Filters extracts, normalizes and structures content from over 600 file formats, ensuring clean and consistent data that is ready for downstream applications while maintaining the document’s logical structure. This allows organizations to seamlessly integrate data from diverse document types without losing its original meaning or intent.
Automated metadata tagging analyzes images to identify key elements, such as objects, scenes and text, then generates metadata to enhance searchability and AI model accuracy. This feature allows organizations to categorize and retrieve images more efficiently, improving content accessibility and relevance.
By converting unstructured text into standardized formats, Knowledge Enrichment makes content ready for machine learning, analytics and automation workflows. This process includes deduplication, format standardization and intelligent content segmentation.
NER technology identifies essential entities, such as people, organizations and locations from documents and assigns contextual meaning. This allows businesses to streamline categorization and automate intelligent workflows.
By automating these processes, Knowledge Enrichment:
In a recent survey conducted by Forrester Consulting and commissioned by Hyland, Forrester presented findings that underscore the importance of harnessing the power of enterprise content and unstructured data.
Explore their findings, which include insights on which content intelligence capabilities are ripe to flourish.
From transforming unstructured content into actionable insights to enhancing AI performance and scalability, Knowledge Enrichment streamlines workflows and improves operational efficiency. Let’s explore the key benefits of the solution, including its impact on data quality, cost reduction and decision-making.
By enriching data at the point of ingestion, Knowledge Enrichment turns raw documents into structured, AI-ready content. This eliminates the need for costly and time-consuming preprocessing steps. Additionally, by improving how data is organized and indexed, Knowledge Enrichment enhances accessibility, which allows businesses to quickly locate relevant information and take timely action. This ensures critical insights are readily available and reduces delays in decision-making while improving operational efficiency.
Clean, structured data leads to:
Organizations can trust that their insights are based on high-quality input.
By embedding enrichment within the content workflow, businesses reduce the burden of manual data processing. This frees up resources and improves efficiency across teams and workflows.
As organizations handle larger volumes of content, Knowledge Enrichment ensures they can process more data without added complexity, enabling seamless growth.
High-quality data is the foundation of effective decision-making and AI-driven insights.
Knowledge Enrichment enhances data consistency, accuracy and completeness by structuring unstructured content, applying metadata and establishing meaningful relationships between disparate pieces of information. This ensures that organizations are working with the most reliable and relevant data possible, reducing errors and improving overall operational effectiveness.
— The Rise of Content Intelligence: A New Era of Innovation in ECM, Forrester, 2025
From improving product discoverability to streamlining claims processing and structuring patient records, Knowledge Enrichment empowers organizations to deliver better outcomes and scale seamlessly. Let’s explore real-world applications that showcase the value of Knowledge Enrichment in solving complex data challenges.
A major retail company needed a solution to automate metadata generation and identify named entities across product catalogs. Knowledge Enrichment applied consistent metadata tagging and created contextualized descriptions. This enabled more accurate data about the documents and more efficient natural language search, as well as improved recommendation engines.
With Knowledge Enrichment:
These enhancements led to more reliable product data, improved search relevance and better personalization in recommendations.
Average number of enterprise content repositories
Say unstructured data is a largely untapped opportunity at their organization
Organizations not maximizing AI use for content intelligence
— The Rise of Content Intelligence: A New Era of Innovation in ECM, Forrester, 2025
Consider an insurance company that processes thousands of claims daily. Traditionally, these claims contain a mix of structured forms and unstructured supporting documents, such as medical reports and photographs. Without Knowledge Enrichment, processing these claims would require extensive manual intervention, unnecessary slow approvals and higher operational costs.
By implementing Knowledge Enrichment:
Applying Knowledge Enrichment results in faster claims processing, reduced manual workload and improved accuracy in fraud detection.
Healthcare providers deal with vast amounts of unstructured patient data, including physician notes, medical histories, prescriptions and test results. Extracting meaningful information from these records manually is time-consuming and prone to errors.
By implementing Knowledge Enrichment:
By transforming unstructured patient records into structured, actionable data, healthcare providers can improve operational efficiency, support better patient outcomes, and streamline compliance with regulatory requirements.
Hyland brings decades of expertise in document processing and content intelligence, making us uniquely positioned to deliver high-quality data curation and content enrichment solutions. Our approach ensures:
With Hyland Knowledge Enrichment, businesses gain a competitive edge — turning unstructured data into a strategic asset that fuels smarter decision-making and innovation.
