Scaling Search and Content Governance with Semantic Technology
Microsoft Docs used Graphwise’s Knowledge Management Suite to transform millions of technical documents into a semantically enriched, scalable knowledge system — improving content governance, accelerating search, and enabling intelligent content delivery.
The Client
Microsoft’s centralized platform for technical documentation serving developers, IT professionals, and end users
The Challenge
Exponential content growth across 450 GitHub repositories, 3,5M pieces of content, 4,500+ authors and 45 Microsoft products created a fragmented, unstructured documentation environment with no unified content model.
The Solution
Microsoft implemented Graphwise’s Knowledge Management Suite to transform millions of documents into a semantically enriched knowledge system for automated classification and improved governance.
Technical capabilities
- Turned 3.5M content pieces from 450+ repositories into a unified, intelligent documentation platform
- Automated semantic classification & discovery with > 70% initial accuracy
Business outcomes
- Cut taxonomy management from weeks to hours and automated 8 months of manual tagging effort
- Delivered smarter internal search and recommendations, ensuring scalable knowledge governance
The Challenge
As Microsoft Docs grew rapidly following its 2016 launch, the team faced a steep content management challenge:
- 3,5 million+ content items
- 450+ GitHub repositories
- 4,500+ distributed authors
- 45+ Microsoft products
This complex and decentralized documentation landscape lacked a central content model, making it difficult to ensure findability, consistency, and a high-quality user experience. Manual tagging and classification efforts were time-consuming and inconsistent, slowing down delivery, weakening search functionality, and hampering intelligent site features.
The Solution
To regain control, Microsoft Docs implemented Graphwise’s Knowledge Management Suite to bring structure, automation, and intelligence to its documentation system.
This included:
- Centralizing content regardless of authoring team or location using shared vocabularies and controlled taxonomies
- Building ontologies to map complex relationships between concepts and products
- Automating tagging workflows using the Knowledge Management Suite’s semantic classification and machine learning
PoolParty features that were used
This semantic infrastructure powered consistent classification, search, and contextual recommendations across the Microsoft Docs ecosystem.
In June 2021, Microsoft Docs started using the Knowledge Management Suite’s corpus management features to programmatically discover new concepts and synonyms by examining own content as well as general industry and competitor resources.
The Impact
By adopting Graphwise’s Knowledge Management Suite, Microsoft Docs achieved:
- Accelerated workflows reducing taxonomy management time from weeks to hours and retagging thousands of documents in <1 hour (previously 8–10 hours)
- Automated tagging replacing 8 months of manual effort
- Smarter internal search and recommendations with intelligent site features and contextual discovery
- 70%+ accuracy in tagging during the initial PoC with no training data
- Scalable knowledge governance to support intelligent content delivery and innovation
Today, Microsoft Docs runs on a future-ready semantic platform that accelerates documentation workflows, strengthens search, and supports enterprise-wide AI strategies.
Facing Similar Challenges?
Struggling with fragmented documentation, inconsistent tagging, or unscalable content operations? Whether you're dealing with siloed content, slow manual workflows, or limited search functionality, Graphwise can help you:
- Unify massive documentation landscapes across teams and platforms
- Automate classification, tagging, and taxonomy governance
- Enable intelligent content discovery and reuse across your ecosystem