# Query Type: choose Lucene, vector, or hybrid retrieval

> Query Type selects keyword, semantic, or hybrid retrieval so the search strategy matches your content and the way users ask.

**Category:** Hybrid Search
**Author:** NeuralSeek Team · **Published:** June 9, 2026
**Canonical:** https://neuralseek.ai/ai-grounded/query-type
**Section index:** https://neuralseek.ai/ai-grounded

Query Type is one of NeuralSeek's Hybrid Search guardrails — part of the platform's 118 individually configurable, fully auditable controls. In regulated, high-volume AI, the difference between a system you can trust and one you merely hope works comes down to specific, tunable controls exactly like this one. Here is what Query Type does, why it matters to the business, and how to set it for your own environment.

## What it actually does

This selects the retrieval mode — keyword (Lucene), semantic (vector), or hybrid. Each suits a different kind of question and content.

## Why business teams care

Keyword search nails exact terms, vector search captures meaning, and hybrid combines both; the right choice depends on your content. Selecting the mode tunes retrieval to how your users actually ask.

## How to tune it in practice

Use hybrid as a strong default, lean keyword for precise term lookups, lean vector for natural-language variety. Test against representative queries.

## Common failure modes it prevents

Pure keyword search misses meaning and pure vector search misses exact terms; relying on either alone leaves answers weaker than they should be. Query Type closes that gap directly. By making the behavior an explicit, enforced control rather than something left to chance, it converts a latent risk into a managed, observable event — one that surfaces in the audit trail instead of in a customer complaint or a compliance finding.

## Where it fits in the stack

It governs the retrieval engine itself, blending sparse, dense, and re-sort strategies before grounding ever runs. Because it lives in NeuralSeek's governance layer rather than inside any single model, the control holds identically whether a request routes to OpenAI, Anthropic, Gemini, Llama, Mistral, IBM watsonx, or an in-house model.

## Retrieval tuned to your content

Because the search strategy is configurable, the same platform can serve precise keyword lookups and fuzzy semantic questions, each matched to the shape of your knowledge base.

> The right retrieval mode depends on how your users ask and how your content is written.

## The takeaway

Query Type selects keyword, semantic, or hybrid retrieval so the search strategy matches your content and the way users ask.

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From NeuralSeek's AI Grounded — practical, web-verified guidance on building governed, grounded enterprise AI. NeuralSeek is the model-agnostic, governed AI platform you own: any LLM (swap with no rebuild), your data in your own tenant (cloud or on-prem), 118 guardrails enforced before any action, one container that runs anywhere.