Library

Drop a 40-page architecture review into the Library. Ask in the Timeline: "What does the review say about API rate limits?" The answer cites page 12 of the document and a Redis decision you saved three months ago. Your documents and your memories search together.

The Library stores PDFs, Word files, presentations, and Markdown. Content is parsed, split into searchable segments, and indexed. Every document becomes searchable from the Timeline, global search, and connected AI tools via MCP.

Supported Formats

Adding Documents

Drag files into the Timeline input, or use the Library view to import.

Documents go through a processing pipeline:

1. Parsing: content extracted from the file format
2. Segmentation: split into searchable chunks
3. Indexing: added to both vector and keyword search indexes

Processing status is visible in the Library view. Once indexed, the document's content is searchable from the Timeline, global search, and connected AI tools via MCP.

Searching Documents

Documents are searched alongside memories. A Timeline question like "What does the Q4 report say about churn?" searches both your saved memories and any imported documents that match.

In the Library view, you can also browse and search documents directly.

How It Connects

Documents in the Library are sources for your knowledge base, not memories themselves. The distinction:

• Memories are atomic insights, decisions, or facts you or the system extracted
• Documents are reference material you imported whole

When you distill a document, individual insights can be extracted as memories and connected to the knowledge graph. The document remains in the Library as the source.

Next Steps

• Getting Started: The Timeline and all ways to add knowledge
• Background Intelligence: How imported knowledge connects to your graph
• Search & Relevance: How search ranks results across memories and documents