Searching by meaning — PKM needs semantic search / local embeddings
Users with thousands of notes find keyword/tag search insufficient. They either buy/try Devonthink Pro or add plugins (Smart Connections) or experiment with local LLM embeddings. The clear desire is for reliable semantic search that runs locally or privately and surfaces relevant content.
Persona
“I might write something short... but if that sentence has a great poetic rhythm ... an app smart enough to analyze my notes and say 'hey this one matches your work' would be useful.”
view evidence on redditPain
“But if the note taking app is smart enough to analyze my notes and say “hey this one matches your work in this field.” Then this whole pkms become useful.”
view evidence on reddit“Devonthink... Built-in AI (in the Pro version) helps searching and finds connections between documents in your filesystem.”
view evidence on reddit+1 more evidence
“Smart Connections uses local embeddings and your Smart Environment to surface notes that are semantically related.”
view evidence on redditWorkaround
“You could try conversational search with an LLM and Logseq with this: conversational-search-on-logseq-with-local-llms”
view evidence on reddit“Smart Connections plugin (uses local embeddings) surfaces semantic matches.”
view evidence on reddit+1 more evidence
“I'm working on a notes app that uses local llms to generate embeddings for each block, and you can then find blocks that are semantically similar.”
view evidence on redditDesire
“If the note taking app is smart enough to analyze my notes and say “hey this one matches your work in this field.” Then this whole pkms become useful.”
view evidence on reddit