Evernote’s AI can already turn scattered notes into useful, organized information. While it’s not perfect, the potential for improvement is promising and could bring more practicality and personalization to users.
A common challenge for users who rely on Evernote as a repository is data overload on the same topic. When information is still in development, it’s easy to accumulate conflicting notes, making it hard to find reliable sources and compromising clarity.
A practical solution would be to allow customizable AI search profiles using varied criteria like tags, notebooks, stacks, and attachments. For instance, in “Profile 1,” a user might prioritize notes from Notebook X, consider those whidout taggeds as secondary, and exclude notes without attachments. “Profile 2” could focus solely on recent web clips with specific tags, while “Profile 3” might include all notes within a specific stack, regardless of tags or attachments. This approach filters out irrelevant or outdated content, creating a balanced, tailored database for each search. Tags, notebooks, and attachments could serve as valuable tools to further refine and balance these search configurations.
Additionally, it’s crucial that Evernote cites sources directly in responses, displaying them as in-line references, such as “The most common glomerulopathy worldwide is Berger’s disease [1][2][3].” Hovering or tapping on the link would open a pop-up showing the note at the exact referenced section, speeding up information verification and ensuring that each answer is grounded in easily accessible, context-rich data.
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Idea
Rafael B 38
Evernote’s AI can already turn scattered notes into useful, organized information. While it’s not perfect, the potential for improvement is promising and could bring more practicality and personalization to users.
A common challenge for users who rely on Evernote as a repository is data overload on the same topic. When information is still in development, it’s easy to accumulate conflicting notes, making it hard to find reliable sources and compromising clarity.
A practical solution would be to allow customizable AI search profiles using varied criteria like tags, notebooks, stacks, and attachments. For instance, in “Profile 1,” a user might prioritize notes from Notebook X, consider those whidout taggeds as secondary, and exclude notes without attachments. “Profile 2” could focus solely on recent web clips with specific tags, while “Profile 3” might include all notes within a specific stack, regardless of tags or attachments. This approach filters out irrelevant or outdated content, creating a balanced, tailored database for each search. Tags, notebooks, and attachments could serve as valuable tools to further refine and balance these search configurations.
Additionally, it’s crucial that Evernote cites sources directly in responses, displaying them as in-line references, such as “The most common glomerulopathy worldwide is Berger’s disease [1][2][3].” Hovering or tapping on the link would open a pop-up showing the note at the exact referenced section, speeding up information verification and ensuring that each answer is grounded in easily accessible, context-rich data.
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