We wrote the book
Good search understands a user's intent, not just what they type.
We wrote Relevant Search to help teams build smarter Elasticsearch and Solr applications.
One of the best and most engaging technical books I've ever read. — Trey Grainger, Lucidworks
Will help you solve real-world search relevance problems for Lucene-based search engines — Dimitrios Kouizes-Loukas, Bloomberg
Pioneers in machine learning
We built Elasticsearch Learning to Rank, which powers search at Yelp, Wikipedia, Snag, and others.
Since deploying learning to rank, we’ve seen a net 32% increase in conversion metrics across our historically lowest performing use-cases. — Jason Kowalewski, Sr Director of Engineering at Snag
Learning to rank can’t stay hidden away in obscure academic journals or multi-million dollar products. We’re making this stuff accessible to all search teams: opening up the black box for everyone to use”. — Doug Turnbull - OpenSource Connections CTO
We have the tools
We built Quepid, a search testing platform that takes the guesswork out of search relevancy.
Do NOT attempt a search project without it. — John Bickerstaff
Just want to understand why results are showing up in your search?
We support the community
We host a Slack Channel where practitioners support each other and share solutions.
The blog and other happenings
When people say they have 'synonyms' in their search engine, it can turn out to mean a lot of different things...
When considering improvements to search in a product or application it is necessary to have a vision of overall quality, which is a combination of three key areas: relevance, experience, and performance. This article explains all three at a high level and why they matter as a whole, and offers some tips to diagnose and attack a spectrum of common search quality issues.
We share our thoughts on the Lucidwork's Activate 2018 conference
Learn to improve search quality from the best experts in the field. From TFIDF, to Semantic Search, to Learning to Rank with Elasticsearch
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