Case Study

Content related to Content Engineering for Personalized Product Release Notes

What’s Next for Search? Moving Beyond Q&A to Context, Discovery, and Action

Beyond the Search Box Enterprise search is in the middle of a reset. For years, most enterprise search programs were built to return documents and links across repositories, and success was measured by whether employees could locate the right file. … Continue reading

Building the Semantic Layer: Scaling Enterprise Intelligence at a Global Investment Firm

The Challenge A global investment firm with a $330 billion dollar portfolio and 50,000+ employees struggled with fragmented data. Investment professionals were losing critical time hunting for assets across disconnected systems. Detailed deal records were scattered as a mix of … Continue reading

Making Search Less Taxing: Leveraging Semantics and Keywords in Hybrid Search

Explore how Tax Analysts, the nonpartisan nonprofit behind Tax Notes, upgraded its search functionality to help subscribers both easily find information and discover unexpected, relevant content. At KMWorld 2025, Chris Marino of Enterprise Knowledge partnered with Jaime Martin, Senior Product Manager … Continue reading

How to Leverage LLMs for Auto-tagging & Content Enrichment

When working with organizations on key data and knowledge management initiatives, we’ve often noticed that a roadblock is the lack of quality (relevant, meaningful, or up-to-date) existing content an organization has. Stakeholders may be excited to get started with advanced … Continue reading

Defining Governance and Operating Models for AI Readiness of Knowledge Assets

Artificial intelligence (AI) solutions continue to capture both the attention and the budgets of many organizations. As we have previously explained, a critical factor to the success of your organization’s AI initiatives is the readiness of your content, data, and … Continue reading

Top Ways to Get Your Content and Data Ready for AI

As artificial intelligence has quickly moved from science fiction, to pervasive internet reality, and now to standard corporate solutions, we consistently get the question, “How do I ensure my organization’s content and data are ready for AI?” Pointing your organization’s … Continue reading

Auto-Classification for the Enterprise: When to Use AI vs. Semantic Models

Auto-classification is a valuable process for adding context to unstructured content. Nominally speaking, some practitioners distinguish between auto-classification (placing content into pre-defined categories from a taxonomy) and auto-tagging (assigning unstructured keywords or metadata, sometimes generated without a taxonomy). In this article, I use ‘auto-classification’ in the broader sense, encompassing both approaches. Continue reading