Queriously
Local-first macOS PDF reader and research copilot. Cited Q&A, marginalia, and session trails. No cloud required.
Designer & Engineer
Academic and technical research is scattered: PDFs in one place, notes in another, AI answers with no provenance. You can't trust a summary you can't trace back to the source.
Queriously indexes papers locally and lets you ask questions with citations. Every answer traces to a page and sentence. Marginalia, sessions, and evidence trails stay on disk. Built with Tauri 2 and Rust for the shell, React for the UI, and a Python sidecar (FastAPI + sentence-transformers + ChromaDB) for the AI layer.
A research environment where answers are traceable and everything stays private — no API keys required for the core experience.
