remio for Android

remio, from Everdent, is a mobile to desktop personal knowledge hub designed to reduce manual document and meeting management for knowledge workers. The app captures meeting audio, photos of documents, and quick notes on Android devices, then hands those captures to a desktop client for local indexing and natural-language search. Key capabilities include multilingual transcription, image OCR, and source-linked answers. It targets professionals, students, and researchers who need a searchable, private archive.

What tasks can you actually use the app for?

The app accepts live meeting audio through a professional recording mode with smart scene detection, photos of whiteboards or documents for optical character recognition, and instant quick notes with rich text formatting. Outputs include searchable transcripts, extracted text from images, and indexed note items that help assemble meeting minutes, lecture archives, or a project memory without manual retyping.

How accurate are the outputs compared to doing it manually?

The app generates answers by applying a Retrieval-Augmented Generation approach against locally indexed captures, and it exposes clickable references back to the original recordings and documents so users can verify claims. Automatic transcription supports English, Chinese, Japanese, and Korean; accuracy depends on source quality and the desktop processing model selected. Users can compare generated summaries directly to source files via the provided references.

What file formats and setup does it require?

Mobile captures originate on Android devices and the mobile app temporarily stores content in the cloud until the desktop client pulls and indexes it. Enhanced AI processing requires the desktop client running on Windows 10+ (x64) or macOS 13.0+, with optimizations for Apple Silicon. Users who operate only on mobile cannot access the local indexing and advanced query features until their desktop processes uploads.

Does it protect sensitive data and how are models chosen?

The tool prioritizes local processing: heavy tasks such as OCR and AI querying are executed on the user's desktop rather than remote servers. Indexing uses a RAG approach against locally stored captures, and a Bring-Your-Own-Key mode lets users route advanced queries through private API keys or alternative models. Running core processing on local hardware removes reliance on continuous cloud-based inference for the indexed knowledge base.

Best suited to users with regular desktop access who value local data control

The app is a pragmatic option for professionals and researchers who prioritize keeping captured material under local control, but its dependency on desktop processing constrains purely mobile workflows. Treat generated summaries as starting points and verify them against original recordings or documents before relying on them in critical decisions. Users who maintain a desktop index will find the most consistent retrieval performance from the tool.