OpenClaw vs FrankenOCR

OpenClaw is a personal AI assistant you run on your own devices. Pair this iOS app with your OpenClaw Gateway to use your iPhone as a secure node for chat, voice, approvals, sharing, and device-aware automation. What you can do: - Pair with your private OpenClaw Gateway by QR code or setup code - Chat with your assistant from iPhone - Use realtime and background Talk mode - Review Gateway action approvals from your iPhone - Share text, links, and media directly from iOS into OpenClaw - Enable device capabilities such as camera, screen, location, photos, contacts, calendar, and reminders when you choose - Receive push wakes and node status updates for connected workflows OpenClaw is local-first: you control your gateway, keys, configuration, and permissions. Device access is managed by iOS permissions and can be enabled only for the capabilities you want to use. Getting started: 1) Set up your OpenClaw Gateway 2) Open the iOS app and pair with your gateway 3) Start using chat, Talk mode, approvals, and automations from your iPhone

Extract text from an image or scanned PDF without uploading the document. FrankenOCR uses the same pure-Rust Unlimited-OCR engine as the FrankenOCR command-line project. Choose a photo, file, camera capture, tall scrolling screenshot, or scanned PDF. The app reads the input in memory and produces structured Markdown on the device. The flagship recognition path uses a downloaded, verified Baidu Unlimited-OCR model for careful document extraction. Tall screenshots are divided with overlap-aware smart cuts, while PDF pages are processed as a document and low-yield pages are called out instead of silently disappearing. Live Camera mode uses Apple's on-device Vision text recognition for speed. It is less accurate than the flagship FrankenOCR model, and the app labels that tradeoff clearly. Recognized words flow from their camera positions into the capture tray as the view updates. The current app ships one flagship model: Unlimited-OCR. It does not claim to include GOT-OCR2, SmolVLM2, OneChart, or a music-recognition model. Images, PDFs, camera frames, and recognized text stay on the device. Network access is used only to download the static flagship model files.