Yavy

Key Features

• •Semantic Search: Uses vector embeddings to find concepts, not just keywords. Agents retrieve relevant content even when query terms differ, ensuring accurate results. This eliminates the need for exact keyword matching and improves search reliability. Yavy's semantic search understands the context of a query, so questions like 'how do I authenticate' will correctly match documentation on OAuth 2.1 even if those exact words aren't in the query.
• •Structured Context: Data is returned in clean JSON format optimized for LLM consumption, making it easy for AI assistants to parse and present information. The structured output includes URL, relevance score, and snippet, giving the assistant exactly what it needs to cite sources accurately. This format reduces the need for additional parsing and ensures that the AI can immediately use the content in its response, improving response speed and accuracy.
• •CLI-First: Search and generate from the terminal. Install the Yavy CLI with `npm install -g @yavydev/cli`, then run `yavy search` to query your indexed docs without a GUI. The CLI integrates seamlessly with dev workflows, allowing developers to get answers without leaving their terminal. It also supports automated scripting, enabling CI/CD pipelines to verify documentation accuracy or pull content for automated tasks.
• •Skills Export: Generate portable skill packages that work offline with any AI tool. Drop skills into your project and your AI loads them as local knowledge, eliminating the need for a server connection. This is ideal for remote work, secure environments, or when building offline-capable applications. The skills are self-contained and can be version-controlled alongside your codebase, ensuring that your AI always uses the exact documentation version intended.
• •Easy Setup: Add your content source (website, GitHub, Notion, or Confluence) and Yavy handles discovery and indexing automatically. No manual configuration of crawlers or embedding pipelines is required. Within minutes, your content becomes searchable by any integrated AI tool. The platform uses a semantic engine that intelligently chunks content based on headers, so the most relevant sections are indexed without redundancy.
• •Always Fresh: Automatic re-indexing keeps your content up-to-date as docs change. The frequency depends on your plan: daily for Starter, hourly for Pro, or real-time for Team. This ensures AI assistants always have the latest information, preventing stale answers from outdated documentation. Combined with semantic search, this freshness guarantees that even recently updated policies or API changes are immediately reflected in AI responses.

Use Cases

• •Developer Documentation: Developers can query AI assistants for current API references and SDK guides. Without Yavy, the AI might suggest deprecated endpoints, costing 20 minutes of debugging. With Yavy, every answer cites the current version, saving time and reducing errors. This ensures that onboarding, feature development, and troubleshooting are all based on accurate, up-to-date documentation.
• •Customer Support Knowledge Base: Support teams can ground their AI chatbots in the actual help center articles. Instead of inventing refund policies, the chatbots link to source articles, providing accurate and trustworthy answers to customer queries. This reduces escalations and improves customer satisfaction, as users receive verifiable answers directly from the official documentation.
• •Internal Documentation: Teams can search internal wikis or runbooks from within their AI coding assistant. New hires find onboarding instructions instantly, and senior engineers get quick answers on system architecture, accelerating productivity across the organization. Yavy's portable skills also allow offline access, ensuring that the internal knowledge base remains available even without internet connectivity.
• •Educational Content: Educators and students can index course materials, textbooks, and lecture slides. AI assistants then provide accurate citations and summaries, helping students study more efficiently and teachers prepare lessons with verified sources. This makes Yavy a valuable tool for EdTech platforms looking to integrate AI knowledge directly into their curriculum.
• •Legal & Compliance: Legal teams can index their compliance documents, policies, and regulatory updates. AI assistants can then query these documents to ensure responses align with the latest regulations, reducing the risk of non-compliance. Yavy's real-time sync on higher plans ensures that changes to regulatory documents are immediately reflected in AI responses, providing peace of mind.

Who is this for?

Yavy is designed for individual developers (Starter plan), growing teams (Pro plan), and large organizations (Team plan). Specific roles include software developers using Claude Code, Cursor, Windsurf, or VS Code; technical writers managing documentation websites; documentation engineers maintaining internal wikis; support teams building AI chatbots grounded in knowledge bases; and product managers seeking to embed accurate product information into AI tools. Also suitable for educators, legal compliance officers, and knowledge managers who need a reliable bridge between static content and AI assistants. Yavy's pricing tiers make it accessible for personal projects as well as enterprise deployments.