VaultApprover vs DocWeave

VaultApprover approves Bitwarden "Log in with device" requests on bitwarden.com, bitwarden.eu or your own self-hosted Vaultwarden/Bitwarden server. It does one thing: shows who is signing in, so you can approve or deny it in one tap. KEY FEATURES: • Cloud or self-hosted — bitwarden.com (US), bitwarden.eu (EU) or any server URL • Client certificates (mTLS) — import a .p12/.pfx for a server that requires one • Biometric unlock — Face ID / Touch ID or fingerprint on every launch • Real-time requests — WebSocket updates with a polling fallback • Fingerprint phrase — the same 5-word phrase the official Bitwarden apps show • 5-minute countdown — an expired request can no longer be approved • Request history — every approval and denial with device, IP and response time • Two-step login — authenticator app, email code, YubiKey OTP or recovery code • PIN tab — offline tools for your own PINs: PIN Shift, PIN 24 (compatible with Ledger Passwords) and YubiKey PIN/PUK • Optional settings sync — sign in with Apple or Google to keep theme, language and timers the same on all your devices; delete the sync account anytime in Settings • English, Russian, Arabic and Simplified Chinese; light and dark themes HOW IT WORKS: 1. Pick bitwarden.com or bitwarden.eu, or enter your server URL 2. Sign in with your email and master password (used once, never stored) 3. Turn on biometric unlock 4. When you choose "Log in with device" on another device, the request shows up in the app 5. Check the fingerprint phrase and tap Approve — done SECURITY: • Your master password is never stored on the device • End-to-end encryption: RSA-2048-OAEP key exchange • Your user key is kept in the device's secure storage behind biometric lock • All cryptography runs on the device — the server never sees your keys • Argon2id and PBKDF2 key derivation • Privacy screen hides the app in the app switcher VaultApprover never opens or shows your vault items. It only approves sign-in requests. Works with accounts that unlock with a master password. SSO, trusted-device and Key Connector accounts are not supported.

Turn PDFs, images, and paper documents into structured content you can actually edit and reuse. DocWeave runs an AI document recognition model locally on your device. Import PDFs or images, scan paper documents, book pages, and lecture notes with your iPhone or iPad, or capture scrolling webpages and long articles through screen recording. Once the local model is installed, recognition works without an internet connection, and your documents never need to be uploaded to a server. What It Can Do • Scan Paper Documents Automatically detect and continuously capture pages on iPhone and iPad, then add them to the processing queue. Ideal for book pages, lecture notes, receipts, and temporary documents. • Capture Scrolling Content Record scrolling webpages or long articles and automatically stitch them into a long screenshot. Before recognition, you can remove ads, duplicate sections, and irrelevant content. • Understand Complex Layouts Go beyond plain text. DocWeave can recognize paragraph structures, tables, LaTeX formulas, code blocks, and algorithm blocks. • Export in Four Formats Generate reconstructed PDF, Markdown, EPUB, and MinerU packages in one pass—ready for reading, editing, archiving, or further processing. • Preview as Recognition Progresses View structured results as soon as each page is completed, so you can follow the progress and check the reconstructed layout. • Resume After Interruptions If a model download, page capture session, or large document recognition task is interrupted, continue from the saved progress instead of starting over. • Keep Documents on Your Device Model inference, page images, and recognition results are stored locally. Unless you choose to export, share, or send them to another app, your recognized content stays on your device. From capturing paper and importing files to understanding complex layouts and exporting reusable content, DocWeave keeps the entire document workflow on your device. First Use An internet connection is required to download the local recognition model, which is approximately 2.5 GB. The download begins only after you confirm it and can resume if interrupted. Once installed, the model can perform recognition offline. Device Requirements On-device AI recognition requires an A14 / M1 chip or newer and at least 6 GB of RAM. Requirements differ by recognition engine: • OvisOCR2 (faster, lower memory usage): a device with at least 6 GB RAM; keep at least 3 GB of free RAM before loading the model; model files are about 0.6–1 GB (varies by device). • MinerU (full-featured, supports reconstructed PDF export): a device with at least 8 GB RAM; keep at least 5 GB of free RAM before loading the model; the model file is about 2.5 GB. Note: free RAM is not storage; you also need enough storage for the model files and recognition results. Recommended devices: • iPhone 12 Pro / 13 Pro, iPhone 14 or newer (MinerU requires iPhone 15 Pro or newer) • iPad mini (A17 Pro) • iPad Air (M1) or newer • iPad Pro (M1) or newer • Mac with Apple silicon and at least 8 GB of unified memory Devices before A14 are not supported, e.g. iPad Pro (2018/2020, A12X/A12Z chip). Camera scanning and rolling-screen recording capture are only available on iOS/iPadOS. The macOS version supports importing PDFs and images via file picker, drag and drop, or paste.