The AI knowledge base that answers with sources.
Atlas is a team wiki with built-in vector search. Ask questions in plain English and get RAG-grounded answers cited back to the exact pages, PDFs and meeting transcripts in your workspace.
Free for unlimited users. 1 AI credit included per month.
How Atlas turns your docs into an AI knowledge base
Automatic vector indexing
Every wiki page, PDF transcript and meeting note is chunked and embedded as soon as it is published. No manual tagging, no search configuration.
Cited RAG answers
Ask a question and Atlas retrieves the most relevant chunks, then answers with inline citations linking back to the exact source pages.
Permission-aware retrieval
Search results respect the spaces and pages each user can read. AI never leaks information across organizations or private spaces.
Connected to your tools
MCP support lets Claude, ChatGPT and Cursor search, create and update pages. Avoma meetings can also be synced into your knowledge base.
“What was our Q3 pricing decision and who signed it off?”
Atlas searches every page and transcript the user is allowed to read, ranks the most relevant chunks, and synthesizes an answer with direct links to the source material.
Q3 pricing moved to a three-tier model ($500 / $1,500 / $5,000) after the revenue review on June 12. The decision was signed off by the CRO and is documented in the Revenue Brief and Pricing Decision pages.
Atlas vs. the usual knowledge base tools
Confluence stores docs. Notion stores notes. Atlas is built from the ground up as an AI knowledge base with search that understands meaning.
Build your AI knowledge base today
Unlimited users, pages and spaces are free forever. AI search is metered fairly by token usage — roughly 300–700 answers per $1 credit.
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