Fusion Server combines the Apache Solr open-source search engine with the distributed power of Apache Spark for artificial intelligence. Highly scalable, Fusion Server indexes and stores data for real-time discovery.
Fusion AI applies machine learning at the moment of data ingest for: NLP, document classification, and topic detection. At query time, Fusion AI predicts the user’s intent and returns relevant, hyper-personalized results.
Fusion App Studio allows search engineers to rapidly develop rich applications. It combines an integrated development environment, powerful pre-fabricated components, and APIs for developing powerful search UIs.
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Fusion Server personalizes queries based on signals like user profile, behavior, natural language processing, or location. Features like autocomplete, query intent classifier, a rules engine, and our proprietary Semantic Knowledge Graph (SKG) help users express queries for their context. Fusion uses NLP parsing to determine user intent and calculate relevance scores in real-time.
Fusion AI ships with real-time recommendation algorithms to automatically generate content recommendations based on a user’s past interactions or interactions of similar users.
Continuous feedback loops help domain experts optimize machine learning results combined with manual rules curation.
Fusion App Studio lets you quickly create production-ready applications. Combine powerful pre-fabricated components and APIs for developing powerful search UIs.
Analytic insights lets you graphically analyze user behavior, run experiments (such as A/B testing), and inspect individual customer journeys.
Fusion employs NLP to detect phrases, topics and parts of speech for automatic classification and clustering of content in ways that make it easily accessible for search, browsing and predictive suggestions.
Fusion elevates documents which perform best for popular queries across most users and also clusters users by behavior. Models then boost documents with features most relevant to a given cluster.
Head/Tail Analysis and automatic synonym creation analyzes the head (most common) and tail (infrequent) queries in the system, then auto-generates synonyms.
Fusion determines what type of query is being executed (e.g. person, concept, document) to determine query parsing, query pipeline routing, and which words to show in autocomplete and type-ahead.
The Learning to Rank algorithm extracts tags such as product names, titles, and document categories to determine relevance scores in real-time.
Ready to create amazing AI-powered apps? Contact us today to learn how Fusion can help you and our team build search and data discovery that dazzle your customers and empower your employees.