6 min readJust now
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**Your search works. Technically. It just never finds what you’re actually looking for. **We’ve all been there. You search your own docs with exactly the right words in your head, and the system throws back… noise. Half-relevant stuff. You scroll, rephrase, try again. Still nothing useful.
Disclaimer: some parts of this article have been enhanced with the assistance of AI for clarity improvement purposes.
Here’s the thing: search used to be dead simple. Type “car troubleshooting” and the engine hunts for those exact letters in that exact order.
That works great. Until language does what language always does.
You write “car troubleshooting,” but the best doc in your system says “automobile diagnostic…
6 min readJust now
–
Press enter or click to view image in full size
**Your search works. Technically. It just never finds what you’re actually looking for. **We’ve all been there. You search your own docs with exactly the right words in your head, and the system throws back… noise. Half-relevant stuff. You scroll, rephrase, try again. Still nothing useful.
Disclaimer: some parts of this article have been enhanced with the assistance of AI for clarity improvement purposes.
Here’s the thing: search used to be dead simple. Type “car troubleshooting” and the engine hunts for those exact letters in that exact order.
That works great. Until language does what language always does.
You write “car troubleshooting,” but the best doc in your system says “automobile diagnostics.” A keyword engine? It walks right past it.
This is where vector search comes in. Instead of matching words, it retrieves documents based on meaning.
And honestly, that’s why it’s become the backbone of most modern AI applications — RAG chatbots, recommendation engines, you name it.
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