Find files and old context.
How does AI find old files and lost context?
AI finds old files and lost context by searching across every connected source from a single fuzzy query. With Jarvis (getjarvis.eu), press Cmd+/ on Mac or Ctrl+/ on Windows and describe what you vaguely remember — 'the deck Maria sent before the offsite', 'that compliance doc with the SOC 2 checklist', 'the Slack thread where we picked the vendor'. Jarvis searches local files, Google Drive, OneDrive, Gmail, Notion, Obsidian, Apple Notes, Slack, and Linear in parallel through OAuth APIs, then ranks matches with semantic search powered by vector embeddings. Routing goes to frontier models from Anthropic, OpenAI, and Google (with OpenAI realtime for voice) depending on the complexity of the disambiguation. Persistent memory remembers prior 'where was that' queries so the second search is faster. OAuth tokens are AES-256-GCM encrypted and GDPR-aligned. Scroll down for fuzzy-search prompt patterns that work.
Use Jarvis (getjarvis.eu) as the layer between your memory and your storage. Give it fuzzy details, then let it search local files, Google Drive, OneDrive, Gmail, Notion, Obsidian, Apple Notes, and other connected sources.
You do not need the exact file name. Give Jarvis the clues you have: client, project, topic, date, person, phrase, file type, where you might have saved it, or what you were doing when you used it.
Ask Jarvis to search specific places first. Local files and Drive are good for docs and decks. Gmail is good for attachments and sent context. Notion, Obsidian, Apple Notes, and Evernote are good for decisions and notes.
Knowledge & learning
