How Ask Fern works

Ask Fern is a Retrieval Augmented Generation (RAG) system that appears as a side panel on your documentation site, transforming your documentation into an intelligent, searchable knowledge base.

Visual design and behavior

Ask Fern appears as a resizable side panel on your documentation site. Users can drag to resize it or use the expand/minimize button to control their viewing experience.

Key behaviors:

• Adaptive layout – Seamlessly integrates with all Fern Docs layouts
• Persistent navigation – Side panel stays open as users browse different pages or click links provided by the AI responses
• Document-specific queries – Users can ask questions about the current page through a dropdown option
• Mobile optimization – Expands to full screen when users start typing on mobile devices
• Filtered responses – Ask Fern automatically respects versions, products, and roles, so users only see what’s relevant to them

The interface maintains your site’s design language while providing a familiar chat experience that feels native to your documentation.

How it works

The main parts of the Ask Fern system are:

• Content and code indexing – Fern automatically processes your documentation pages and Fern-generated SDK code, breaking them into semantic chunks and converting each chunk into a vector using sentence embedding models. They’re stored in a database that serves as Ask Fern’s search index.
• Query processing – When users ask questions, Ask Fern vectorizes their query and searches the database to find the most relevant documentation and code chunks. If you have role-based access control configured, Ask Fern filters results based on the user’s permissions.
• Response generation – Ask Fern uses the retrieved chunks as context to generate accurate answers with citations for the user. If the initial context isn’t sufficient, it performs an additional keyword search.