add evals page, made edits across pages

Author: devalog

fern/products/ask-fern/pages/features/evals.mdx

@@ -1,4 +1,12 @@
 ---
 title: Evals
-subtitle: Point users to the exact source of the answer. 
----
+description: Benchmark Ask Fern's performance against competitors and track improvements.
+---
+
+Fern evaluates how accurately Ask Fern answers questions on your documentation site compared to competitor AI search solutions. 
+
+Fern first generates evaluation questions from your documentation files, then runs those questions through both Ask Fern and competitor systems. Finally, Fern evaluates each answer against the original documentation for accuracy. You receive detailed performance metrics and comparative analysis.
+
+## Availability
+
+Evals are currently provided as custom analysis delivered directly by the Fern team.

fern/products/ask-fern/pages/features/insights.mdx

@@ -3,13 +3,7 @@ title: Insights
 description: Fern identifies documentation gaps and improvement opportunities from your user queries.
 ---
 
-Fern analyzes Ask Fern query patterns to surface actionable recommendations for improving your documentation. After collecting sufficient query data over a month, Fern processes this through specialized models to identify documentation gaps, common themes, and areas where your docs could be enhanced.
-
-The Fern processes your Ask Fern usage data in three steps:
-
-1. Data Collection: All user queries and responses are logged as they occur
-1. Analysis: Fern's insights model analyzes query-response pairs to identify patterns and themes
-1. Recommendations: The system generates specific, actionable suggestions for documentation improvements
+Fern analyzes Ask Fern query patterns to surface actionable recommendations for improving your documentation. After collecting sufficient query data over a month, Fern processes this through specialized models that analyze query-response pairs to identify documentation gaps, extract common themes, and generate specific suggestions for enhancing your docs.
 
 ## Availability
 

fern/products/ask-fern/pages/getting-started/what-is-ask-fern.mdx

@@ -1,5 +1,5 @@
 ---
-title: AI Search Overview
+title: What is Ask Fern?
 subtitle: Let your customers find answers in your documentation instantly. 
 ---
 
@@ -13,9 +13,9 @@ subtitle: Let your customers find answers in your documentation instantly.
 
 Ask Fern is Fern's AI Search feature that indexes your documentation and provides an interface for your users to ask questions and get answers. It helps our customers
 
-- **Decrease the time to find needed information** - Help users quickly locate crucial documentation without navigating through a maze of tabs and endpoints.
-- **Integrate your product faster** - Accelerate implementation with ready-to-use code samples that demonstrate practical applications.
-- **Surface where your docs have gaps** - Identify documentation weaknesses through user feedback and search patterns.
+- **Decrease the time to find needed information** – Help users quickly locate crucial documentation without navigating through a maze of tabs and endpoints.
+- **Integrate your product faster** – Accelerate implementation with ready-to-use code samples that demonstrate practical applications.
+- **Surface where your docs have gaps** – Identify documentation weaknesses through user feedback and search patterns.
 
 <Frame caption="Users can ask questions and get support in an intuitive chat interface.">
 <img src="../assets/ask-ai-modal.png" alt="Preview of AI Search" />
@@ -62,15 +62,15 @@ Ask Fern is Fern's AI Search feature that indexes your documentation and provide
 
 Ask Fern is a **Retrieval Augmented Generation (RAG)** system built on top of your documentation site that transforms your documentation into an intelligent, searchable knowledge base. The main parts of the Ask Fern system are:
 
-* **Content Indexing**: Fern automatically processes your documentation pages,
+* **Content indexing** – Fern automatically processes your documentation pages,
   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 processing** – When users ask questions, Ask Fern vectorizes their
   query and searches the database to find the most relevant documentation
   chunks.
-* **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. 
+* **Response generation** – Ask Fern uses the retrieved chunks as context to
+  generate accurate answers with [citations](/ask-fern/features/citations) for the user. If the initial context isn't sufficient, it performs an additional keyword search. 
 
 ### Life of a query