SEARCHData & productivity
Jev Knowledge Base
Nikolaj Sokolowski@Threeaio
2:16This project demonstrates Jev's capability in building a knowledge base, handling content ingestion, sorting, grouping, and creating connections between entries without relying on embeddings or expensive agentic search.
From the series: "Can Jev do that?"
Today: a knowledge base (aka second brain).
1.5 years ago, I launched my first larger AI project (Seio, some of you may remember).
I wanted a system where I could drop any kind of content as quickly as possible, from every device I use.
The system then handles sorting and grouping and creates connections between entries (all of this long before Karpathy).
I've now used that dataset (without tags and metadata, of course) to test what something like this would look like with Jev.
What can I say … it works.
The ingest part is obvious: Jev is primarily built to tag, categorize, etc.
But what about retrieval?
Here too, Jev shines, there's no other way to put it.
Without any embeddings and without expensive agentic search, Jev shows me the expected top hits.
Is it perfect? No. But then again, none of the approaches I've tried so far were (and the "perfect approach" probably doesn't exist in this field yet anyway).
For a live implementation, I'd probably still not do without embeddings, and I'd add an LLM here and there.
Used in the right places, though, Jev can significantly reduce retrieval time and noticeably improve answer quality.
Test for the use case "knowledge bases": clearly passed 🎓 ✅
The demo shows Jev-only ingestion AND retrieval.
No embeddings, no LLM.
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