# Application Search

## Application search that scales

Deliver relevant and fast results by combining vector, full-text, and keyword search in one runtime.

[Get a demo](https://meetings.hubspot.com/lukekim/talk-to-sales?uuid=836fd7be-a95e-4cee-b0cb-044fd8ea52a4&utm_campaign=22505145-Website+Demo+Requests&utm_source=homepageheader&utm_medium=website&utm_content=demo+request) [View the docs](https://spiceai.org/docs/features/search)

### Do more with your data

- **100x** up to 100x faster queries
- **80%** up to 80% cost savings on data lakehouse spend
- **2x** increase in data reliability for critical workloads

### Modern application search mandates a hybrid approach

Building great application search demands a blend of search methods: keyword for precision, full-text for context, and vector for semantic meaning. Most teams struggle to combine them effectively without standing up separate engines or ETL pipelines. The result is fragmented search logic, inconsistent results, and slower performance.

### Relevant and fast application search

Ship application search that combines multiple methods, predictable performance, and full data governance.

#### Hybrid search out-of-the-box

Blend results for keyword, full-text, and vector similarity using Reciprocal Rank Fusion (RRF). Add per-query weights, filters, and recency boosts so the most relevant and newest results appear first.

[Explore hybrid SQL search](/content/platform/hybrid-sql-search/index.html)

#### Natively integrated with AI

Add categorization, classification, and enrichment directly into your search results using Spice's SQL AI function. Leverage built-in LLM functions for labeling, summarizing, sentiment, and custom tasks.

[Explore SQL AI functions](https://spiceai.org/docs/reference/sql/ai)

#### Simple to build, easy to scale

Spice integrates with serverless S3 Vectors and scales with your data and traffic.

[Get started with Amazon S3 Vectors and Spice](/content/blog/getting-started-with-amazon-s3-vectors-and-spice/index.html)

#### Accelerate locally

Materialize hot data with DuckDB, SQLite or Spice Cayenne acceleration and offload vector loads to scalable object store indexes with Amazon S3 Vectors. Get predictable performance for common queries with index-only reads and filter pushdown.

[Explore Spice Cayenne Data Accelerator](/content/blog/introducing-spice-cayenne-data-accelerator/index.html)

### Unified search for real-time, data-driven apps

Spice provides SQL-first, unified hybrid search. No extra pipelines or duplicate storage.

- **SQL-First Hybrid Search**: Express all search functions in familiar SQL syntax.

- **Low-Latency Runtime**: Accelerate queries for sub-second responses under high concurrency.

- **Built-in Re-Ranking**: Blend multiple result sets with Reciprocal Rank Fusion for per-query weighting and tunable relevance.

- **Centralized Policy and Governance**: Apply enterprise-grade security, access controls, and audit capabilities to every query.

- **Single Data and AI Runtime**: Combine hybrid search, federated data access, and AI workflows to deliver an enterprise-grade search experience.

- **Deploy Anywhere**: Run Spice anywhere: as a sidecar, microservice, cluster, or on the managed Spice Cloud Platform.

### Deployed in production

Run data-intensive workloads on a high-performance engine trusted by teams building real-time systems at scale.

#### “Spice opened the door to take these critical control-plane datasets and move them next to our services in the runtime path.”  
**Peter Janovsky**  
*Software Architect, Twilio*

0x
Faster queries

#### “It just spins up and works, which is really nice. The responsiveness is amazing, which is a huge gain for the customer.”  
**Darin Douglass**  
*Principal Software Engineer, Barracuda*

#### “Partnering with Spice AI has transformed how NRC Health delivers AI-driven insights. By unifying siloed data across systems, we accelerated AI feature development, reducing time-to-market from months to weeks - and sometimes days. With predictable costs and faster innovation, Spice isn't just solving some of our data and AI challenges - it's helping us redefine personalized healthcare.”  
**Tim Ottersburg**  
*VP of Technology, NRC Health*

#### “Spice AI grounds AI in our actual data, using SQL queries across many data sources. This brings accuracy to probabilistic AI systems, which are very prone to hallucinations.”  
**Rachel Wong**  
*CTO, Basis Set*

### Build an application search engine that works

Guides and examples to learn more about introducing application search with Spice.

[Blog\n\n **True Hybrid Search: Vector, Full-Text, and SQL in One Runtime** \n\n TL;DR  Show Me the (Data)! It’s well established (and maybe even trite) to say that enterprises are going all-in on artificial intelligence, with more than $40 billion directed toward generative AI projects in recent years. The initial results have been underwhelming. A recent study from the Massachusetts Institute of Technology's NANDA initiative concluded that despite the enormous allocation of \[...,\n\n  
[Blog\n\n **Real-Time Hybrid Search Using RRF: A Hands-On Guide with Spice** \n\n Surfacing relevant answers to searches across datasets has historically meant navigating significant tradeoffs. Keyword (or lexical) search is fast, cheap, and commoditized, but limited by the constraints of exact matching. Vector (or semantic) search captures nuance and intent, but can be slower, harder to debug, and expensive to run at scale. Combining both usually entails standing up multiple engines \[...,\n\n  
[Blog\n\n **Making Object Storage Operational for Real-Time and AI Workloads** \n\n TLDR Introduction Although legacy systems and workflows remain common, many enterprises are re-evaluating their architectures to meet new demands – driven in part, but not exclusively, by AI – that require support for more data-intensive and real-time applications. The underlying storage needs for these novel workloads are generally outside the bounds of a traditional operational \[...,\n\n

### See Spice in action

Walk through your use case with an engineer and see how Spice handles federation, acceleration, and AI integration for production workloads.

[Talk to an engineer](https://meetings.hubspot.com/lukekim/talk-to-sales)