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Knowledge Graphs
A knowledge graph, also known as a semantic network, represents a network of real-world entities - i.e. objects, events, situations, or concepts - and illustrates the relationship between them.

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Features

KMWorld Readers' Choice Award Winners 2025

KM is about people and their ability to capture, organize, share, and make actionable knowledge. KM relies on technologies that can enable this core mission. Congratulations to the KMWorld Readers' Choice Award winners, and many thanks to all of you who submitted nominations and took the time to vote.

KMWorld Leader Group for 2025

While our Readers' Choice Awards honor the top companies in each of the categories, we've expanded this year's coverage to include a supplementary list we're calling the Leader Group that showcases the broader landscape of exceptional KM solutions available to organizations today. So much excellent work is being done, and done quickly, given the rapid changes in technology. We urge you to review the winners and our new Leader Group of companies to check out how they could help you in your KM journey.

Readers' Choice Awards 2025 - Franz: Agentic AI with AllegroGraph’s Neuro-Symbolic Knowledge Graphs

To achieve true autonomy, AI systems must integrate both neural networks (for learning and pattern recognition) and symbolic AI (for structured knowledge and reasoning). This fusion, known as Neuro-Symbolic AI, is essential for bridging the gap between data-driven insights and human-like decision-making.

2025 KM Leaders Circle: Enterprise Knowledge, LLC. - Harnessing assorted data, content, and other knowledge assets in an AI-ready format

Enterprise Knowledge helps organizations harness their assorted data, content, and other knowledge assets in an AI-ready format, building the necessary organizational models and mechanisms to support enterprise-level alignment.

ViewPoints

How Semantic AI & Knowledge Graphs Can Turn M365 Environments Into a Smart Knowledge Hub

By eliminating data silos, semantic AI enriches customer data and content and enables greater knowledge discovery across an organization. Due to its diverse capabilities, such as text mining, tagging, semantic search, etc., it can be implemented along the whole data and content lifecycle in order to develop intelligent applications. When integrated with an organization's CMS, semantic AI can help individuals get the information they need sooner.

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Scarcity Versus Abundance

The Knowledge Age we've been talking about for so long has finally arrived. The potential for scarcity is real, but so is the potential for overflowing abundance. Let's bring every tool in our KM arsenal to bear, along with our decades of experience, and help make it happen.

What is Bharat and why should you care?

Knowledge should always be considered as accretive, not something that's "here today, gone tomorrow."

Knowledge Management Whitepapers

The Trend-Setting Products in Knowledge Management 2025

AI-Powered PLM in Manufacturing: Making PLM Content AI-Ready

How ENOVIA + Adlib turn CAD, BOMs, and SOPs into reliable knowledge for search, RAG, and compliance

Pharma Launches Don’t Fail Because of Strategy. They Fail Because of Documents.

Discover how Veeva + Adlib eliminate content bottlenecks, accelerate approvals, and make your launches AI-ready.

Managing Information Through Transition: The Merger and Acquisition Integration Playbook

Knowledge Graphs Companies and Suppliers
Knowledge Graphs Directory