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Lucidworks Fusion

Fusion transforms your siloed data into personalized insights unique to each user.

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Connected experiences for the world’s biggest organizations

What’s New in Fusion

Lucidworks Fusion lets customers easily deploy AI-powered data discovery and search applications in a modern, containerized, cloud-native architecture. Data scientists interact with those applications by leveraging existing machine learning models and workflows. Or they can quickly create and deploy new models using popular tools like Python ML, TensorFlow, scikit-learn, and spaCy.


Smooth Sailing With Kubernetes

Reduce the effort and risk of managing deployments of Fusion in the cloud. Lucidworks has modernized Fusion with a cloud-native microservices architecture orchestrated by Kubernetes. Fusion allows customers to dynamically manage application resources as utilization ebbs and flows, reduce the effort of deploying and upgrading Fusion, and avoid unscheduled downtime and performance degradation.


Machine Learning Everywhere

Fusion includes native support for Python machine learning models. Plug your custom ML models into Fusion and integrate with your existing data science infrastructure. Allow your data scientists and analysts to use Fusion with their existing toolkits to augment user’s human intelligence across the entire experience.

Product Discovery Solutions

Create Apps Quickly

Smart Answers

Smart Answers extends the functionality of chatbots and virtual assistants with deep learning. Businesses can better serve their customers and employees by giving them fast answers to their product and support questions.

Learn More About Smart Answers

Empower Your Merchandisers

Predictive Merchandiser

Predictive Merchandiser gives retailers AI-powered insights and recommendations for optimizing search results and product placement. Merchandisers can apply and manage rules, tune search relevancy, and analyze results through a visual interface without involving IT.

Learn More About Predictive Merchandiser

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Never Null

Never Null is a cloud service that uses semantic vector search to reduce zero results queries and increase conversions. Populate web pages with the perfect product assortment – and never ever return a zero results page.

Learn more about Never Null

Advanced Linguistics Package March2020

Advanced Linguistics Package

AI-powered search is challenging enough within the English language. The search engine must identify the language, normalize non-English characters, and improve content recall without losing precision. Non-English languages have distinct semantics, grammar and slang, not to mention the unique characters in Asian, European and Arabic base languages. Lucidworks offers an Advanced Linguistics Pack that provides tokenization in more than thirty non-English languages as well as advanced entity extraction for 19 languages.

Learn More About Fusion’s Advanced Linguistic Capabilities

Flexible Deployment Options March2020

Flexible Deployment Options

Cloud-native architectures allow precise management of a platform’s individual software components. Kubernetes orchestrates Fusion’s cloud-native architecture, and sustains the logical separation provided by microservices, the physical separation provided by containers, and the APIs that connect the components. As a result, the Fusion platform can evolve with the changing storage, compute and application ecosystem.

Learn More About Fusion’s Deployment Options

Contextual Insights, Delivered Instantly

Lucidworks Fusion is the data discovery platform that gives users contextual, personally relevant search results and proactive recommendations with artificial intelligence that augments their human intelligence. Millions of users can discover insights at the moment they have a question, without any training, and even across billions of documents or records.

The Lucidworks Fusion Platform

Data Ingest & Prep

Fusion applies machine learning at the moment of data ingest to add deeper understanding and context to every data set.

  • Natural language processing extracts meaning from speech, text, and unstructured data
  • Machine learning models classify and categorize data at index time
  • Classification algorithms to categorize data based upon provided training data or documents fields

more about Ingest & Prep

Storage & Search

Fusion combines the Apache Solr open-source search engine with the distributed power of Apache Spark for artificial intelligence. Highly scalable, the platform  indexes and stores data for real-time discovery.

  • Index billions of records of any type, from any data source
  • Process thousands of queries per second from thousands of concurrent users
  • Conduct full-text search using standard SQL capabilities and powerful analytics

more about Storage & Search

Intent Prediction

Fusion applies machine learning at query time, to predicts the user intent to return relevant, hyper-personalized results.

  • AI recommendations give every user a customized experience
  • Signal capture and user behavior analysis for relevant recommendations
  • Query intent detected for hyper-personalization


App Creation

Fusion’s application 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.

  • Prototype consumer and workplace search apps in hours, not weeks
  • Iterate and version apps with modular, pre-built components
  • Deliver search on content from 100 data sources in 500 data formats

more about Fusion’s application studio

Lucidworks Fusion Pricing

Lucidworks offers pricing across three product tiers, either self-hosted by your team or as a Lucidworks managed service in the cloud with list prices calibrated to expected usage levels.

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Insight Discovery With Personal Context

Uses machine learning to personalize queries, optimize results, and proactively guide users to discover their own insights.

Hyper-Personalized Results

Fusion 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 help users express queries for their context. Fusion uses NLP parsing to determine user intent and calculate relevance scores in real-time.

Guided Insight Discovery

Fusion 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.

Easy Application Development

Fusion’s application 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.

Artificial Intelligence for Constant Self-Tuning

Natural Language Processing (NLP)

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.


Signals Boosting

Fusion clusters users by behavior and elevates documents which perform best for each cluster’s favorite queries. Models then boost documents with features most relevant to a given cluster.


Head/Tail Query Rewriting

Head/Tail Analysis and automatic synonym detection analyzes the head (most common) and tail (infrequent) queries in the system, then auto-generates synonyms.


Query Intent Classification

Machine learning in Fusion uses training data on past searches and outcomes to predict the intent of each new query. Deep learning can use that intelligence for query parsing, query pipeline routing, autocomplete and type-ahead.


Learning to Rank

The Learning to Rank algorithm extracts tags such as product names, titles, and document categories to determine relevance scores in real-time.


Data Clustering and Classification

Fusion uses unsupervised machine learning to cluster similar content for pattern recognition. Classification, a supervised form of ML, teaches Fusion to classify new data to predetermined categories.


Let’s Talk

Contact us today to learn how Fusion can help you and your team put the power of machine learning and search to work to dazzle your customers and empower your employees.

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