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
Our next training event, Relevance Cornucopia🦃, we'll add the missing piece to the manual tuning & learning to rank picture: Natural Language Search. Come learn to build relevance that can be both optimized by machine learning AND understands user's natural language.
Search systems struggle to balance diversifying the result set to match likely intents vs ranking against one well understood intent.
Hello LTR is a framework that lets you plugin your data to easily build and test Learning to Rank models in Solr or Elasticsearch. Try it Out!
Eric & Dan from OSC talk about OCR & Solr Payloads and Florian from Mimecast shows us how to index billions of log lines a day, and the usual Q&A and networking
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