A Developer’s Guide to Vector Embeddings and Search In the age of AI, traditional keyword-based search often isn’t enough. To build truly intuitive search experiences, we need to move toward…

I've authored a blog for developers who are new to vector embeddings and semantic search - if that's you, hopefully you'll find it helpful!

#semanticsearch #vectordatabase #vectorembeddings #densevectors #sparsevectors #elasticsearch

LLM chunking & snippet extraction: Extract the best content for LLMs - Elasticsearch Labs Exploring chunking and snippet extraction for LLMs, showing how to use `chunk_rescorer` and ES|QL functions to identify the best content for models.

Here, I dive into some of the work we've done on this to date, including support for a chunk rescorer in our semantic reranking retriever, as well as some useful ES|QL primitives to get more visibility into chunks and snippets.

#elasticsearch #semanticreranking #snippets #chunks #chunking #esql

Elasticsearch semantic search: match, knn & sparse_vector support - Elasticsearch Labs Explore and learn how to use the changes that leveled up Elasticsearch's semantic search, including native match, knn, and sparse_vector support.

Some of the coolest work I did with Elasticsearch in 2025 involved leveling up semantic text - native support for match queries (www.elastic.co/search-labs/...) and configurable index options and chunking settings (www.elastic.co/search-labs/...) - looking forward to 2026 bringing more innovations!

Dec 5th, 2025: [EN] You know, for hybrid search If you’ve tried setting up a hybrid search experience, then you know there can be a steep learning curve. This is especially true when combining text search with semantic search results, because the s...

A little late, but linking to my Elastic Advent post on all the great work that's been done this year to simplify hybrid search in retrievers and ES|QL: discuss.elastic.co/t/dec-5th-20...

Introducing Elastic Agent Builder, designed to give your agents the best context and tools. Build precise agents fast, connect all your data where it already lives in Elasticsearch, and create custom tools for any use case.

Learn more: www.elastic.co/search-labs/...

👋 Welcome to Elastic Dev — your new go-to for hands-on demos, cheat sheets, concept explainers & more. Get the latest on search, data & GenAI straight from the source.

Expect:
- Practical demos & how-tos
- Posts & technical deep dives
- Open source updates
+ more

Ready, set, build. Hello, world.

Simplifying semantic search: native match, knn & sparse_vector support - Elasticsearch Labs Explore the changes that leveled up semantic search and learn how to use those features, including native match, knn, and sparse_vector support.

It's exciting to see semantic_text become more flexible to use for both general and expert use cases. And we're not done yet! #elasticsearch #vectorsearch #semanticsearch

Ensuring business rules work seamlessly with semantic search - Elasticsearch Labs Harness the power of query rules combined with semantic search and rerankers.

Closing out the year with a final blog on query rules as a retriever. This is a particularly exciting change because it ensures that your business rules as defined in query rules work seamlessly with reranking strategies such as semantic reranking and RRF. It's available in serverless and 8.17.0!