People frequently capture personal notes such as meeting summaries, ideas, decisions, and reflections. However, retrieving this information later is inefficient and unreliable.
Most note-taking tools rely on keyword-based search, which requires users to remember exact words or phrases used when writing the note. Over time, notes become fragmented, disconnected, and difficult to navigate. Important insights, decisions, and action items often remain buried and are effectively lost, even though they exist somewhere in the user’s notes.
This problem affects knowledge workers, students, and anyone who relies on notes to think, plan, or make decisions. The inability to easily retrieve previously written information reduces the long-term value of note-taking and leads to repeated work, forgotten decisions, and missed insights.
The proposed solution is a conversational note system that allows users to interact with their own private notes using natural language.
Instead of searching by keywords, users can ask questions such as “What did I decide about the API redesign?” or “What are my action items from recent meetings.” The application retrieves semantically relevant excerpts from the user’s notes and generates a synthesized answer based strictly on those sources.
To ensure trust and transparency, every response includes citations of the original notes that were used to generate the answer. The system does not rely on general knowledge or assumptions, but on retrieval-augmented generation grounded in the user’s own data.
By combining semantic search with a conversational interface, the application reduces the cognitive burden of information retrieval and enables users to rediscover and reuse their own knowledge more effectively.
https://www.figma.com/board/3iyCW7mtYGt8EO9Z20yx1u/CNS---User-Story-Map?node-id=0-1&t=RXOQhTUfYa9VOw9M-1
https://www.figma.com/board/OXaX36u8Cts5VYTf8HAZGk/CNS---Wireframe?node-id=0-1&t=WqtiuRUTdzgjlOv9-1