How Teams Use Yavy
From developer documentation to customer support, Yavy helps teams stop AI hallucinations and get real answers from real content. Discover how organizations are using semantic search, MCP servers, and portable Skills packages to transform their knowledge bases.
Popular Use Cases
Detailed guides for the most common applications
Developer Documentation
Index framework docs, API references, and technical guides. Your AI coding assistant gets accurate answers from real documentation instead of hallucinating outdated patterns.
Common examples:
Knowledge Base
Turn your help center into an AI-searchable knowledge base. Customers and support agents get instant, accurate answers. Support ticket volume decreases.
Common examples:
More Applications
Yavy works for any content you want AI to search accurately
Internal Documentation
Index company wikis, onboarding guides, and internal processes. New hires get instant answers without bothering colleagues.
Educational Content
Index course materials, tutorials, and learning resources. Students get AI-assisted study help grounded in your curriculum.
Legal & Compliance
Index policies, procedures, and compliance documentation. Get accurate answers about regulations and requirements.
Research & Academia
Index research papers, literature reviews, and academic resources. AI assistants can cite your actual sources.
Who Uses Yavy?
Teams and individuals turning their content into AI knowledge
Developer Teams
Engineering teams index their stack documentation (React, Node, AWS, etc.) so AI coding assistants give accurate, up-to-date answers.
SaaS Companies
Product companies index their documentation so customers can get instant, accurate support through AI assistants.
Open Source Projects
Maintainers index their documentation so contributors can get quick answers without waiting for responses.
The Problem with AI Today
AI assistants are powerful, but they have a fundamental limitation: they can only work with their training data. When you ask about specific frameworks, APIs, or your own documentation, they often make things up - confident-sounding answers that are completely wrong.
This is especially problematic for developers, support teams, and anyone who needs accurate, current information. You end up fact-checking everything the AI says, which defeats the purpose of using AI in the first place.
How Yavy Solves It
Yavy turns your documentation into an AI-searchable knowledge base. When your AI assistant needs information, it queries Yavy's MCP server and gets real answers from your actual content - with sources.
- Semantic search finds relevant content by meaning, not keywords
- Source attribution so you can verify and learn more
- Real-time sync keeps content current automatically