unified-multi-source-search
Indexes and searches across 20+ connected data sources (Slack, Confluence, Notion, Gmail, GitHub, etc.) through a single query interface. Eliminates the need to manually search each platform separately by consolidating all organizational knowledge into one searchable index.
context-aware-semantic-search
Uses AI to understand the semantic meaning and context of search queries rather than relying on keyword matching. Returns relevant results based on intent and meaning, not just exact word matches, reducing irrelevant noise.
user-feedback-and-answer-rating
Collects user feedback on search results and AI-generated answers through rating and feedback mechanisms. Uses this data to improve search quality and identify problematic results.
search-analytics-and-insights
Provides analytics on search behavior, popular queries, and knowledge gaps. Tracks what users are searching for, what they find, and what they don't find to identify organizational knowledge gaps.
slack-integration-and-bot
Integrates Danswer directly into Slack as a searchable bot, allowing users to search the knowledge base and get answers without leaving Slack. Enables inline search and question-answering within chat conversations.
source-attribution-and-citation
Automatically tracks and displays the original source of each search result, allowing users to verify information and trace where answers came from. Provides clickable links back to the original document or message.
knowledge-base-indexing
Automatically crawls, extracts, and indexes content from connected data sources into a searchable knowledge base. Handles continuous updates and maintains index freshness as new content is added to source platforms.
ai-powered-question-answering
Generates direct answers to user questions by synthesizing information from the indexed knowledge base, rather than just returning search results. Uses AI to compose coherent responses with relevant context.
+5 more capabilities