Mnemonic
react, typescript, ai, voice
A voice-first personal memory system that turns everyday notes into a structured, searchable knowledge base. Users can write or speak naturally, then ask questions about their notes and receive precise answers from their own stored information.
view projectChallenge
Replace scattered, difficult-to-recall personal notes with a system that makes previously captured information easy to find and query using natural language, without requiring users to remember where or how they recorded something.
Approach
Built a personal knowledge workflow around natural-language note capture and retrieval, combining structured notes with text- and voice-based querying. The interface presents notes as a living knowledge base and provides an “Ask your notes” experience for retrieving relevant information conversationally.
Outcome
Delivered a focused personal memory assistant that lets users capture information naturally and retrieve it through questions instead of manually searching through notes. The result is a searchable knowledge base designed to help users remember less while still being able to access what they previously recorded.
Highlights
- Voice-first note capture and natural-language interaction
- Searchable personal knowledge base built from user notes
- Ask-your-notes interface for conversational retrieval
- Designed around structured, persistent personal memory