Sease Information Retrieval Applied
Sease mission is to make research in Information Retrieval more accessible to an industry audience, transforming the best research principles, ideas and implementations from academia into real-world products. We build Search solutions and AI integrations with cutting-edge Machine Learning such as Large Language Models (Retrieval Augmented Generation, Vector-Based Search and more) and Learning To Rank. Firmly believing Open Source is the way, Sease puts a strong effort into contributing code back to the community, supporting public mailing lists and evangelising R&D at world-class conferences. The focus of the company is to provide R&D project guidance and implementation, search consulting services, training and search solutions using open-source software such as Apache Lucene/Solr, Elasticsearch, OpenSearch and Vespa.
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Verified contacts
9
available on Kipplo
LinkedIn employees
8
1 to 10 range
Open roles
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no listings
Distinct roles
7
indexed titles
Tech stack
3
tools in use
Monthly traffic
740
organic / mo
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Decision-makers and verified team members
9 contacts with verified email or phone · masked until revealed.
- AR
Anna Ruggero
Software Engineer · Information Technology
EmailPhone - DA
Daniele Antuzi
R & d Software Engineer · Information Technology
EmailPhone - EP
Elia Porciani
R & d Software Engineer, Information Retrieval Expert · Other
EmailPhone - IP
Ilaria Petreti
Information Retrieval Machine Learning Consultant · Other
EmailPhone - LB
Lisa Biella
À - · Other
EmailPhone - NS
Nazerke Seidan
Ö Ö Á · Other
EmailPhone - NR
Nicolò Rinaldi
Junior Software Engineer Data Scientist · Other
EmailPhone
Showing 7 of 9 verified contacts
Top roles at Sease Information Retrieval Applied
7 distinct titles indexed · top 7 shown.
- 1information retrieval machine learning consultant
- 1junior software engineer data scientist
- 1r & d software engineer
- 1r & d software engineer, information retrieval expert
- 1software engineer
- 1à -
- 1ö ö á
Sign up to unlock all 9 contacts at Sease Information Retrieval Applied
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