Chat with your documents privately — no Docker, no homelab
Journal Genie lets you chat with your own documents and get answers that cite the exact passage — privately, with no self-hosting. There’s no Docker, no homelab, and no CS degree required. Your documents are isolated per user, never used to train AI, never sold, and exportable in one click.
Journal Genie lets you chat privately with your own documents — cited answers, no self-hosting, and never trained on your data.
The privacy-conscious answer to “chat with your PDFs” has usually been: self-host it. Run a local model, wire up a vector database, keep it patched. That’s real ownership — and real friction. Most people never get past the setup.
Journal Genie is the private option you don’t have to self-host. You upload documents, ask questions, and get grounded, cited answers — and the privacy is contractual and architectural, not something you maintain on a server in your closet.
Journal Genie vs. self-hosting your own document AI
Self-hosting a local model with your own retrieval stack is a legitimate, maximally private choice. The trade-off is setup, maintenance, and quality. Journal Genie trades a subscription for zero ops.
| Capability | Journal Genie | self-hosting (local LLM + your own RAG stack) |
|---|---|---|
| No setup — works in a browser today | Yes. Sign up and upload; nothing to install | No. Docker, models, a vector DB, and upkeep |
| Cited answers from your sources | Yes. Every claim cites the page it came from | Depends on the stack you build |
| No training on your data; no ads; no sale | Yes. Contractual + isolated per user | Yes. You control it entirely — the upside of local |
| One-click full export in plain markdown | Yes. Leave with everything, any time | Your files are local, but no portable account |
| Maintained, patched, and supported for you | Yes. It’s a product, not a project | No. You are the ops team |
Upload, ask, verify
Add PDFs, URLs, or pasted text. Ask a question in plain language. The answer cites the exact source passage, and you can click to read it. When the documents don’t support a confident answer, the AI says so.
Private without the server
Your documents are scoped to your account with per-user row-level isolation and encrypted in transit and at rest. We do not train AI on them and we do not sell them. You get the privacy posture of self-hosting without becoming a sysadmin.
No lock-in
Because privacy without portability is just a nicer cage, Journal Genie exports your whole account — documents, citations, and all — in plain markdown, one click. Leave whenever you want.
Where self-hosting wins
- A fully local setup keeps your documents on hardware you physically control and can run entirely offline — the strongest possible privacy posture if you’re willing to maintain it.
- Self-hosting has no subscription and no third-party processor at all; Journal Genie uses named providers (Supabase, OpenAI, Stripe) under a no-training arrangement.
Questions, answered first.
How can I chat with my documents privately without Docker?
Use Journal Genie. You upload documents in the browser and ask grounded questions with cited answers — no Docker, no local model, no vector database to run. Your documents are isolated per user and never used to train AI or sold.
Is it as private as self-hosting?
Self-hosting on hardware you control is the strongest posture. Journal Genie gives you contractual no-training, per-user isolation, encryption in transit and at rest, and one-click export — privacy without the maintenance burden.
What document types work?
Text-extractable PDFs, web URLs we fetch and parse, and pasted plain text. Scanned/image-only PDFs need OCR first.
Related, and the proof behind it.
Skip the setup. Keep the privacy.
Upload one document and ask one question — cited, private, and yours to export. Free to start.