Build a Document Vault
This tutorial walks you through creating a document vault, importing a file, and asking questions about it. By the end, you’ll have a personal knowledge base you can query with AI.
1. Open the Vault
Section titled “1. Open the Vault”Click the folder icon on the Daneel launcher bubble to open the vault overlay.
2. Create a vault
Section titled “2. Create a vault”If this is your first time, you’ll see an empty vault list. Click Create Vault and give it a name — something like “Research Papers” or “Project Docs”.
3. Import a document
Section titled “3. Import a document”Click the Import button inside your vault. You can:
- Click to open a file picker
- Drag and drop files directly onto the vault area
Supported formats: PDF, DOCX, TXT, HTML, PPTX, Excel (XLS, XLSX).
Pick a document — a PDF works well for this tutorial. Daneel converts it to text, splits it into chunks, generates embeddings, and stores everything locally.
You’ll see the document appear in the vault with its name, format icon, and chunk count.
4. Ask a question
Section titled “4. Ask a question”With your document imported, type a question in the chat input at the bottom of the vault overlay:
What are the main conclusions of this paper?
Daneel searches the vault’s vector index, finds the most relevant chunks, and generates an answer using your active AI model.
5. Import more documents
Section titled “5. Import more documents”Add more files to the same vault. Daneel deduplicates by content hash (SHA-256), so importing the same file twice won’t create duplicates.
6. Try the knowledge graph (optional)
Section titled “6. Try the knowledge graph (optional)”If you want to visualize entity relationships across your documents:
- Open the vault’s settings (gear icon)
- Enable Knowledge Graph
- Daneel extracts named entities (people, organizations, places, concepts) using a local NER model and builds an interactive 3D graph
See How to Build a Knowledge Graph for the full guide.
What just happened
Section titled “What just happened”Daneel converted your document to structured Markdown (using EdgeParse for PDFs, Mammoth for DOCX), chunked it into overlapping segments, and embedded each chunk with the BGE Small model on WebGPU. The vectors are stored in IndexedDB, partitioned by vault ID. Queries run semantic search over those vectors and feed the top matches into a RAG prompt.
Everything stays in your browser. Your documents are never uploaded anywhere.
Free vs. paid limits
Section titled “Free vs. paid limits”| Free | Paid | |
|---|---|---|
| Vaults | 1 | Unlimited |
| Documents per vault | 5 | 50 |
| Max file size | 1 MB | 10 MB |
| Max characters per doc | 50,000 | 500,000 |
Upgrade your license to unlock the full limits.
Next steps
Section titled “Next steps”- Connect a Cloud Provider for more powerful AI responses
- Learn how to create a custom agent to specialize your vault’s AI
- Browse linked pages from a vault document — turn web-origin docs into a navigable surface
- Read about the privacy model to understand what stays local