Glossary
Hybrid search
Combining keyword and vector retrieval, because each fails where the other succeeds.
Keyword search handles exact identifiers, part numbers, product codes, names, precisely. Vector search handles paraphrase and intent. Used together with reranking, they cover each other's blind spots.
Nearly every production search system we build ends up hybrid.
The weighting between the two retrievers is worth tuning rather than defaulting. A parts catalogue leans heavily on keyword matching; a policy library leans semantic. The same code with two different weights behaves like two different products, and the only way to set it is against real queries from your own logs.
Commonly misunderstood: Semantic search is often deployed as a replacement for keyword search, which reliably makes exact-match queries worse.
Related terms, in context
The concepts you almost always meet alongside hybrid search.
- Vector database
- A store for embeddings that answers 'what is semantically closest to this?' quickly.
- Reranking
- A second-pass model that reorders retrieved candidates by actual relevance.
- RAG
- Retrieving relevant passages from your own documents and giving them to the model, so answers are grounded and citable.
Where this shows up in our work
Hybrid search is not an abstraction for us. It is a decision we make on live projects. It shows up most directly in ai search implementation, rag & knowledge retrieval, where getting it wrong has a cost someone can measure.
If you are evaluating a vendor on this, the useful question is not whether they can define the term. It is what they measure, what they would refuse to do, and what happens in their system when the assumption behind hybrid search stops holding.
Questions
What is Hybrid search?
Combining keyword and vector retrieval, because each fails where the other succeeds.
What do people get wrong about hybrid search?
Semantic search is often deployed as a replacement for keyword search, which reliably makes exact-match queries worse.
Does Orqent Labs build this?
Yes, AI Search Implementation and RAG & Knowledge Retrieval Systems. We work across India, covering all 19,238 PIN codes remotely.
Building something that involves hybrid search?
We will tell you honestly whether it is the right approach for your problem.
Or email bd@dtrasglobal.com · call +91 74118 77878