What good is search if you can never find anything? We're pioneers in smarter search that "gets" users.
We're the relevance experts
Good search understands a user's intent, not just what they type.
We wrote Relevant Search, the definitive guide to building 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
Products and services for smarter search
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
Want to just understand why results are showing up in your search?
The blog and other happenings
Exploring a method of search relevance testing that doesnt suffer from drawbacks of clickstreams or expert user judgments
A guide on how to implement, test, and deploy a Normalized Discounted Cumulative Gain (NDCG) ranking quality scorer in Quepid.
We document some of the behaviors behind Solr's relatively new sow=false strategy for parsing queries and dealing with query-time synonyms
Learning to Rank (LTR) is now available for both Solr and Elasticsearch. Why is this such a hot topic? What does an organization need to leverage a Learning to Rank solution? Liz explains the LTR pipeline in terms of what is available as an off-the-shelf solution and what isn't. She discusses the challenges faced when implementing LTR and some open research areas moving forward.