# Nixiesearch Projects at AI Tinkerers

> Canonical HTML: https://aitinkerers.org/technologies/nixiesearch
> Markdown URL: https://aitinkerers.org/technologies/nixiesearch.md
> Technology record last updated: 2026-02-25T10:19:40Z
> Generated: 2026-09-22T21:36:01Z

Nixiesearch is a cloud-native, open-source search engine: it runs Apache Lucene over S3-compatible storage, delivering stateless operations and integrated AI features (RAG, vector search).

This is a modern, 'batteries included' search engine built on battle-tested Apache Lucene, supporting 39 languages, facets, and advanced filters. Its core strength is operational simplicity: it decouples compute and storage, running stateless search nodes against immutable indexes on S3-compatible storage. This design eliminates cluster state headaches, enabling zero-downtime blue-green deployments and risk-free schema changes. Nixiesearch integrates AI out of the box, offering fully local embedding and LLM inference, plus first-class RAG API support, all within a single container.

- Official technology site: https://nixiesearch.ai
- Public AI Tinkerers demos and talks: 1
- Result page: 1 of 1

## Recent Public Talks and Demos

### [Nixiesearch: a new Lucene-based hybrid search engine which fine-tunes to your data](https://berlin.aitinkerers.org/talks/rsvp_jtED_DXuUG8)

Building a new search engine in 2024 sounds like a stupid idea: a new vector search startup is created every week, so how can you be different from so many competitors? But in practice, you can quickly discover that putting vectors into an HNSW index is not the most challenging part of building a search application that your customers would use and like. Relevance tuning, multi-field search, facets, filters, autocomplete suggestions - the RAG-vector search crowd is still discovering all these “novel” things. In this talk, we’re going to introduce Nixiesearch, an open-source hybrid search engine focused on solving typical search problems: * Based on Lucene. You get filters, facets, autocomplete, and complex queries out of the box with decent performance. * Cloud-native and serverless. Can use S3-compatible block storage for index persistence, being able to scale to zero. * Can fine-tune the underlying embedding model on your relevance labels (if you have them) or LLM-generated synthetic labels. Nixiesearch is still in an early development stage, so your opinion on “how to do a search engine right” is really important.

- Event context: AI Tinkerers Berlin - March 21 — 2024-03-21 — Berlin
- Public talk page: https://berlin.aitinkerers.org/talks/rsvp_jtED_DXuUG8

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