홈 / 기능 / 프라이버시 및 로컬 우선

osFoundry로 로컬 우선, 비공개, 오프라인 가능 AI

온디바이스에서 모델을 실행하고, 비공개 채널을 클라우드에서 벗어나게 유지하고, 오프라인으로 작업합니다. 귀하의 데이터, 귀하의 기기.

osFoundry는 로컬 우선입니다: 온디바이스에서 모델을 실행하고, 비공개 채널이 절대 동기화되지 않게 유지하며, 완전히 오프라인으로 작동하는 데스크톱 앱입니다. 종단 간 암호화가 동기화되는 항목을 보호합니다. 로컬 동기화 엔진은 워크스페이스를 파일 시스템에 투영하고, osIndex를 통해 디바이스 측에서 점수 및 인덱싱이 발생하며, 누출 없는 로컬 LLM 모드는 어떤 프롬프트도 기기를 떠나지 않도록 보장합니다.

요점

로컬 우선 데스크톱 앱 — 오프라인으로 작동하고, 온라인 상태일 때 동기화됩니다.
비공개 채널은 절대 기기를 떠나지 않습니다. 끝.
동기화되는 모든 것에 대한 종단 간 암호화.
누출 없는 로컬 LLM 모드 — 공급자 중립, 클라우드 라우팅 없음.
로컬 동기화 엔진 — 디스크의 폴더로서의 워크스페이스.

개요

Most AI products are cloud services with a desktop shell: your prompts, files, and history live on someone else’s servers, and “privacy” means a policy promise. osFoundry inverts that. The desktop app is the primary home of your workspace — the local sync engine projects it into your file system as ordinary folders and files, models can run entirely on-device, and cloud features are opt-in additions rather than the foundation.

Privacy is enforced at the architecture level, not the policy level. A private channel is excluded from the sync queue at creation — its messages and attachments are never uploaded, so there is nothing on a server to leak, subpoena, or misconfigure. The no-leak local-LLM mode applies the same idea to inference: it is a workspace-level switch that disables every cloud route, so no prompt can leave the machine regardless of which chat or agent sends it.

Everything that does sync — because you chose multi-device or team features — travels end-to-end encrypted with workspace-controlled keys. The result is a gradient you control: fully offline and local, selectively synced, or cloud-augmented, per workspace and per channel.

주요 기능

로컬 우선 동기화 아키텍처 — 양방향, 충돌 인식.
비공개 워크스페이스 모드 — 플래그된 데이터는 기기를 떠나지 않습니다.
오프라인 가능 앱 — Room App은 네트워크 없이 작동합니다.
디바이스 측 osIndex 점수 — 모델 점수가 자체 하드웨어에서 실행됩니다.
누출 없는 LLM 모드 — 모든 클라우드 경로를 비활성화하는 워크스페이스 설정.
워크스페이스 제어 키가 있는 종단 간 암호화.

osFoundry에서 하는 방법

Flag what is private — Create a private channel for sensitive work. It is excluded from sync at creation — messages and attachments are never enqueued for upload, and other devices on your account cannot see it.
Go local for inference — Install a local model from the catalog, then enable no-leak LLM mode in workspace settings to disable all cloud routes for prompts.
Verify it yourself — Disconnect from the network and keep working — chat with local models, edit notes, run offline-capable Room Apps. Sync resumes for non-private data when you reconnect.

활용 사례

Legal and back-office teams: Draft against contracts and HR documents with a local model in a private channel — nothing ever leaves the machines that hold the files.
Consultants under NDA: One private channel per client. Client material stays on-device while general research uses cloud models in normal channels.
Frequent travelers: Full workspace on a laptop: local models, notes, and apps work in flight; encrypted sync catches up on landing.

자주 묻는 질문

Does osFoundry require a cloud account to use?

No. The desktop app runs locally with no sign-in required. Cloud features (sync, hosted GPU, public app URLs) are opt-in.

Can I work entirely offline?

Yes — install local models, disable cloud routes, and the app works without network access. Sync resumes when you reconnect.

How is "private channel" different from a normal channel?

A private channel is flagged at creation. The local sync engine never enqueues its messages or attachments for upload. Even other devices on your account can’t see it.

Which data leaves my machine in the default setup?

Only what you opt into. Private channels never sync. Non-private data syncs end-to-end encrypted when you enable multi-device or team features; local-model prompts never leave the device, and no-leak mode extends that guarantee to the whole workspace.

Can I mix cloud models with local privacy?

Yes — route sensitive prompts to local models (or keep them in private channels) while public-information prompts use cloud models. The routing is configurable per path in osStudio.