Build a personal knowledge base with RAG, vector search, and intelligent document indexing. Your context stays under your governance policy — self-hosted, hybrid, or managed.
Drop in PDFs, Markdown, code files, or entire folders. Alabobai indexes everything locally and makes it instantly searchable.
Find information by meaning, not just keywords. Powered by local embedding models that understand context and nuance.
Ask questions about your documents in natural language. Get precise answers with references to exact paragraphs and page numbers.
Choose secure runtime mode for regulated environments while maintaining full execution capability.
Understands code structure — functions, classes, imports. Ask questions like "where is auth handled?" across your entire codebase.
Embeddings are generated locally. No document content, queries, or metadata ever touches an external server.
Index your documents and start asking questions immediately.
Select folders, files, or entire drives. Alabobai watches for changes and re-indexes automatically in the background.
A local embedding model (nomic-embed-text via Ollama) converts your documents into searchable vector representations.
Query your knowledge base in natural language. The RAG pipeline retrieves relevant context and generates precise answers.
Index your first folder and start asking questions in under 3 minutes. No complex setup required.