Smart Indexing for Brilliant Search
Enhancing Solr with AI-Powered
Apache Solr is at the heart of many innovative search-based applications. With Rosette’s advanced natural language processing (NLP) technology, you can power your existing Solr applications up with Artificial Intelligence.
● Document Tagging ●
Multi-Faceted index enrichment
for data discovery
Rosette enhances your database with AI-powered text analytics and metadata tagging to enable intelligent, faceted search. Rosette adds enhanced faceting in 21 languages and can be adapted in the field to domain-specific content for improved accuracy. Documents are tagged with their language(s), transliterated entity mentions, categories, and sentiment.
● Intelligent Name Search ●
Setting the standard for
Unlike keyword searches, names are uniquely variable and require complex queries to handle more than one type of fuzziness. Rosette features a patented, two-pass system for intelligent name matching, that balances speed with accuracy for industry-leading results. Connect related documents in your index to create a resolved profile of key players in your data. Rosette handles misspellings, nicknames, aliases, titles, phonetic spellings, cross-script variations, and translations.
● Multilingual Search Enhancement ●
High Quality Language Analyzers for
global search coverage
The challenges of accurate search are compounded as you add more languages to the queries and results. Rosette enriches your original text in its native language to link related words and normalize meaningless word variations, improving precision and recall in many languages. Core morphological building blocks—tokens, lemmas, parts of speech and more—are identified for specialized applications such as recommendation engines and resume matching engines.
Interested in learning more? Talk to us.
Yes, it’s the time to add AI into your arsenal. Learn how easy it is to integrate Rosette with your existing Solr application.
Don’t take our word for it
“If we misunderstand the language, and ship core functionality that reads as broken in a local language—it makes us look like a company that doesn’t understand the local customs and languages and makes it hard to build a community of local users.”
— Travis B., Group Product Manager of Search & Data Science