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Knowledge Organization

Turn disconnected content into AI-ready, trustworthy enterprise assets

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The challenges of modern data, content, and knowledge management have evolved beyond a question of pure volume. Today, the critical metrics are findability, factual fidelity, referenceability, reusability, and machine-processability.

Knowledge organization does more than just categorize information; it captures and structures domain-specific, tacit knowledge. By establishing governed taxonomies and controlled vocabularies, you transform raw text into a standardized, machine-readable asset, laying the structural groundwork that all downstream data and AI applications rely on.

The costs of fragmented enterprise knowledge

Obsolete tooling

Relying on static spreadsheets (e.g. Excel) or rigid open-source tools for taxonomy management creates operational bottlenecks, stalls scalability, and introduces human error

Unclassified content

The lack of a clear classification scheme and knowledge organization means that elaborately produced but poorly indexed content disappears undiscoverable

Inconsistent vocabularies

Corporate nomenclature naturally diverges across departments, regions, or following M&A activity. Without automated mapping, synonym management, and cross-system linking, critical information remains trapped in data silos

Disconnected delivery

Traditional, manual metadata tagging cannot scale with modern enterprise workflows. For data to drive downstream value, machine-readability and semantic standardization must be embedded into your operational processes

Graphwise’s taxonomy management opens up new possibilities

AI-Assisted Knowledge Modeling

We introduced the Taxonomy Builder, our large language model (LLM)-based suggestion tool that streamlines the process of creating taxonomies and organizing your knowledge. The Taxonomy Builder promises the following:

  • Reliable recommendations: The LLM is connected to company documents and data so that the suggestions are domain specific and not random
  • Less time researching: The user still has the ability to refine or reject the Taxonomy Builder’s suggestions, but spends less time having to outline new terms from scratch
  • Adding concepts: Users can select and edit from suggested narrower and related concepts 
  • Generated concept definitions: Users can add/edit auto-generated definitions that are suggested by the Builder
  • Streamlined editing: Users can add suggestions in bulk operations or singularly, depending on their preference

Controlled vocabularies

With Graphwise’s collaborative interface, departments can bundle synonymous terms under one concept and relate it to other concepts, creating a consistent knowledge organization that reduces confusion while searching for information. This is especially pertinent to international companies that use different foreign languages in different offices.

Agile metadata

Organizations need to be able to pivot and shift based on growing trends within the market. Agile taxonomy management means that you can reuse and add data for other types of data models. The flexibility to continuously revise and update taxonomies by key stakeholders ensures that organizations stay relevant and up-to-date with consumer and industry demands alike.

Intelligent content

Taxonomies help organize your knowledge to understand how your information is structured, and build a strong foundation for search platforms that can retrieve results based on these connected dots. Having a structured taxonomy in combination with text mining capabilities, helps machines understand connections and hierarchies between all of your data – which can then suggest further information relevant to the user’s search.

The Foundation for Semantic AI

Taxonomy management is the essential first step toward building a robust Semantic Backbone. This layer serves as the engine powering intelligent search platforms, recommendation engines, and virtual assistants. Ultimately, this structured foundation unlocks advanced AI capabilities (including GenAI, GraphRAG, Composite AI, and Explainable AI) ensuring your models reason using verified enterprise context rather than raw data alone.

Explore Our Success Stories:

Turning a Legacy Thesaurus into a Strategic Knowledge Asset
Success Story

Turning a Legacy Thesaurus into a Strategic Knowledge Asset

With Graphwise’s Data Management Suite, CABI transformed its outdated, single-use thesaurus for smarter search.

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Digital Transformation as an Accelerator for Semantic Technologies
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Digital Transformation as an Accelerator for Semantic Technologies

Wolters Kluwer used Graphwise’s Knowledge Management Suite to streamline enterprise taxonomy management and accelerate digital transformation.

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Creating a National Vocabulary Service for Research Data Discovery
Success Story

Creating a National Vocabulary Service for Research Data Discovery

ANDS used Graphwise’s Knowledge Management Suite to create a national platform for publishing, managing & accessing controlled vocabularies.

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