What is semantic search? Explained with a librarian who understands you
Semantic search finds results by what you mean, not just the exact words you typed. Explained with a librarian who understands your question and brings back the right books.
- Author
Umair Mateen- Published
- Reading time
- 5 min
- Category
- AI
In one sentence: Semantic search is a way of searching that looks for what you mean, not just the exact words you typed, like a librarian who hears "something to keep my hands warm in the snow" and walks you to the books on winter gloves.
The everyday picture
Picture two ways to find a book in a library. The first is the old card catalogue. You look up a word, and it lists every book with that exact word in the title. Type "cheap" and you miss every book that says "budget" or "low-cost".
The second way is a good librarian. You explain what you need in your own words. The librarian understands the idea behind your question and brings back the books that fit, even if none of them use your words.
Semantic search is that librarian, built into software. Google Cloud describes it as a technique that focuses on the meaning and intent behind a search, rather than only matching keywords. The card catalogue is keyword search, which looks for exact word matches.
Your question goes to the librarian, the AI model that reads its meaning. The librarian goes to the shelves where similar meanings sit and brings back the closest books, best match first.
How it works, step by step
- Your question (what you say at the desk) is typed in everyday words, such as "how do I get my money back?"
- An AI model (the librarian listening) turns the question into an embedding: a list of numbers that describes its meaning. Elastic explains that semantic search uses language models and vector search to find results by meaning, not just keywords.
- The search index (the shelves) already holds an embedding for every document, made ahead of time by the same model. These are often kept in a vector database.
- The search (the librarian walking to the right shelf) finds the documents whose meaning is closest to the question. A page called "Refund policy" matches, even though it never says "money back".
- The results (the books handed to you) come back sorted, closest meaning first. Many systems also run a keyword search at the same time and merge the two lists. Microsoft calls this hybrid search.
Try it · Side by side
Card catalogue or librarian: which is better for the job?
Tap what matters to you (pick one or more) and see which option fits.
Keyword search (card catalogue)
- Strong. It looks for that exact text.
- Misses it unless the words match.
- Strong. Names are exact words.
- Struggles with long, chatty questions.
Semantic search (librarian)
- Weaker. Codes carry little meaning to match on.
- Finds pages with the same meaning.
- Can bring back loosely related names.
- Built for this: it reads the intent.
Pick what matters to you and the better fit lights up.
Where the picture stops
- A real librarian can ask you a follow-up question when you are vague. A semantic search engine usually cannot. It makes its best match from the words it was given.
- A librarian knows the books. The software does not understand the way a person does. It compares lists of numbers, and "closest in meaning" can still be wrong, out of date or only loosely related.
- A good librarian is also good with exact titles and names. Semantic search is often weaker there. Microsoft notes that product codes, specialised jargon, dates and people's names often work better with keyword search, which is why the two are combined.
Why it matters for your business
- Customers find things: shoppers and help-centre visitors describe what they want in their own words. Google Cloud gives online shopping and internal company search as common uses.
- Staff waste less time: people can find the right policy or past proposal without guessing the exact phrase the author used.
- Better AI answers: semantic search is usually the "look it up first" step in RAG, where an AI assistant reads your own documents before it answers.
- Lower risk with hybrid search: keeping keyword search alongside it means exact invoice numbers and product codes still turn up reliably.
Try it · Myth or fact
Semantic search: myth or fact?
Decide for yourself first, then tap each statement to check it.
0 of 3 checked
An example
Imagine a 15-person furniture shop with an online help centre. Customers type "my sofa came with a rip" but the right article is titled "Reporting damaged deliveries". Keyword search finds nothing, so they email support instead. The shop switches its help-centre search to hybrid search. Now that question brings up the damaged-deliveries article first, while a search for an order number still finds the exact order page. The team still checks which searches return nothing, and fills those gaps with new articles.
Frequently asked questions
What is the difference between semantic search and keyword search?
Keyword search looks for the exact words you typed. Semantic search looks for content with the same meaning, even when the words are different.
Is semantic search the same as vector search?
Not quite. Vector search is the usual way to build it: comparing embeddings to find the closest ones. Google Cloud describes semantic search as the broader idea of searching by meaning and intent.
Does semantic search replace keyword search?
Usually not. Many systems run both at once and merge the results, called hybrid search. Keyword search stays better for names, codes and exact phrases.
Is semantic search the same as asking a chatbot?
No. Semantic search hands back existing documents that match your meaning. A chatbot writes a new answer, and it often uses semantic search first to find what to read.
Related explainers
The DevDrift builds AI search that finds the right document and shows where each answer came from: see how.
Sources
Could you explain this to a colleague now?
Mark it and posts that mention it will show a tick. Saved in this browser only.