On-device document intelligence

Sensitive documents should never have to leave your device just to benefit from AI.

An AI workspace for confidential knowledge.

See how it works

No account. No server. Nothing uploaded — ever.

Live in your workspace — nothing sent anywhere

"Sample size across the three trials was consistent with prior work."

Supported — Source 2, p.4

"No conflicting results were found in related literature."

Contradicted — Source 5, p.11

Every claim traced back to its source. Every contradiction surfaced before you submit, publish, or file.

The problem

Every upload to a cloud AI is a trust decision. For a meaningful slice of real work, that's not a decision you're allowed to make.

Researchers

Unpublished findings, unreviewed manuscripts, proprietary datasets.

Journalists

Leaked material, source-sensitive documents, unpublished stories.

Founders

Investor documents, cap tables, unreleased plans.

Engineers

Proprietary source code, internal architecture docs.

Legal & HR

Contracts, NDAs, case files, anything under obligation.

If it isn't ready for the world, it isn't ready for someone else's servers.

How it works

01
Upload your sources
Drop in drafts, papers, notes, or files. Everything is indexed locally — nothing leaves the device.
02
Extract what each source claims
Gemma 4 reads every document and surfaces its claims as structured data, not more prose to re-read.
03
Cross-reference for contradictions
Claims across every uploaded source are checked against each other automatically.
04
Verify your own citations
Check that what your draft cites actually holds up against the source it points to.
05
See the outline and the gaps
A structure emerges from your sources — with the parts still missing made visible, not buried.

Why on-device

Not a privacy policy. A property of the architecture.

Nothing you upload is sent anywhere. There is no server for it to go to.

Works fully offline. No connection required after the model is loaded once.

No account, no logs, no provider who could be compelled to hand anything over — because no one else ever holds it.

Self-Host & Deployment

100% Data Sovereignty. Run locally on your PC or self-host on a private VPS.

Confide is fully open-source and containerized. Run it 100% air-gapped on your personal laptop, or deploy a private server instance for your team using Dokploy, Coolify, or Docker Compose.

Deployment Flexibility

✔ macOS, Linux & Windows compatible

✔ Docker & Docker Compose containerized

✔ Self-hostable on Dokploy, Coolify, or VPS

1. Clone & Run InstallermacOS / Linux / Windows
git clone https://github.com/ahmadktn/confide.git && cd confide && ./install.sh
2. Open Local WorkspaceBrowser

Open http://localhost:3000. Model weights automatically download to storage/models/ on first launch and operate 100% offline.

The workspace

Sources

draft_v3.pdf
source_02.pdf
+ Add source

Document

Click to open workspace →

Verdicts

SupportedContradictedSupported

Powered by Gemma 4, running locally through LiteRT-LM. Native function calling turns documents into structured claims and verdicts — not just another chat window.

Edge / On-Device Track