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Webinar: Introducing Lucidworks Fusion 5.0

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Webinar: Introducing Lucidworks Fusion 5.0

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Lucidworks Fusion 5.0 is here! Fusion’s cloud-native architecture is optimized for deployment on Docker and Kubernetes and enables dynamic scaling of AI-powered search applications. Fusion 5.0 also introduces native Python support and integrates with the most popular machine learning frameworks, so you can seamlessly deliver powerful experiences to your customers and employees.

Join Lucidworks Chief Architect, Tim Potter and Director of Product Marketing, Alea Abed for a tour of what’s new and improved in the latest release of Fusion.

Presented by: Tim Potter, Chief Architect, Lucidworks and Alea Abed, Director of Product Marketing, Lucidworks

Lucidworks Fusion 5.0 is here! Fusion’s cloud-native architecture is optimized for deployment on Docker and Kubernetes and enables dynamic scaling of AI-powered search applications. Fusion 5.0 also introduces native Python support and integrates with the most popular machine learning frameworks, so you can seamlessly deliver powerful experiences to your customers and employees.

Join Lucidworks Chief Architect, Tim Potter and Director of Product Marketing, Alea Abed for a tour of what’s new and improved in the latest release of Fusion.

Presented by: Tim Potter, Chief Architect, Lucidworks and Alea Abed, Director of Product Marketing, Lucidworks

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Webinar: Introducing Lucidworks Fusion 5.0

  1. 1. S P E A K E R N A M E S P E A K E R T I T L E Introducing Lucidworks Fusion 5.0
  2. 2. Presenters T I M P O T T E R Chief Architect, Lucidworks A L E A A B E D Director, Product Marketing Lucidworks
  3. 3. Agenda Company and product overview What’s new in Fusion 5.0 Fusion 5.0 Deep Dive Q&A
  4. 4. Lucidworks helps the world’s largest organizations make their valuable data work for their customers and employees. 250+E M P L O Y E E S 400+E N G A G E M E N T S A C R O S S T H E G L O B A L F O R T U N E 2 0 0 0 S P O N S O R I N G C O M PA N Y
  5. 5. S A N F R A N C I S C O United States C A M B R I D G E United Kingdom B A N G A L O R E India H O N G K O N G China N O R T H C A R O L I N A United States
  6. 6. Personalization is expected I N D U S T RY T R E N D S AI is a priority
  7. 7. HYPER PERSONALIZATION Maximize the opportunities to tailor content that fits each and every employee’s wants and needs.
  8. 8. Better Outcomes Customer Care Research Fraud Detection ComplianceRecruiting
  9. 9. C A S E S T U D Y Better customer support Putting the right information in front of customers in fewer clicks Improved support calls Shorter wait times, and a more engaged support Reinvestment of savings 200%I N C R E A S E I N C T R 50KF E W E R S U P P O R T T I C K E T S 91%R E D U C T I O N I N T C O
  10. 10. HYPER PERSONALIZATION Tailor the shopping experience to match each shopper’s wants and needs.
  11. 11. Better Outcomes ATC Increased Add to Cart AOV Improved Average Order Value CTR Boosted Click Thru Rate
  12. 12. C A S E S T U D Y Uses Fusion to handle search across multiple B2B, B2C, SMB & private sites, across: 88 countries 36 languages 170%I N C R E A S E I N S E A R C H - B A S E D R E V E N U E 142%I N C R E A S E I N C T R Fortune 500 Computer & Electronics Retailer
  13. 13. Advanced connectors and AI enrichment, delivered by intuitive applications created with App Studio, deployed in the cloud or on-prem. D ATA Any format, any platform S O L U T I O N Personalized to meet needs of each unique user FUSION Server FUSION Search AI FUSION App Studio FUSION Data AI F U S I O N P L AT F O R M Human Generated System Generated Application Generated Digital Commerce Applications Digital Workplace Applications
  14. 14. 14 Fusion 5 Microservices Data Science Integration Predictive Merchandiser
  15. 15. What’s new in Fusion 5.0 • Cloud-native • Kubernetes deployments (Cloud or on-prem) • Autoscale capable • Easier deployment, upgrades and management • Native support for Python ML models
  16. 16. Data Science Toolkit Integration • Increased data science productivity • Faster time to value • Extend ML across entire experience w/ Python integration at index and query time
  17. 17. Lucidworks Predictive Merchandiser • Visual interface to create and manage rules • Enables merchandisers to be self-service • Eliminates tedious workflows
  18. 18. F US IO N 5 .0 FO R THE D IGITA L WO R K PLACE • More more apps, more data sources, faster • Reduced risk of downtime • Manage resources & costs • Higher relevancy, ML-powered results
  19. 19. 19 F US IO N 5 .0 FO R DIGITA L CO MME RCE • Scale resources for events like Black Friday • Reduce risk of downtime and lost revenue • Seamlessly improve product relevance • Give merchandisers more control over search & browse experience
  20. 20. 20 Fusion 5 Deep Dive
  21. 21. Cloud-native Architecture Flexible deployment Deploy on any private or public cloud infrastructure Microservices Orchestrated by Kubernetes Reduced TCO Easier management, Less DevOps specialization required Autoscaling policies Expand capacity where needed to adapt to changing business needs Continuous Delivery Reduced risk of downtime
  22. 22. Kubernetes: Beyond the Hype • Best practices for operating distributed systems baked into codified processes and tools • Better alignment with our customers’ goals of running in the cloud and leveraging microservices • K8s ecosystem is growing fast! • Installing + monitoring, scaling, complex, HA distributed apps has never been easier • Resource efficiency ~ less overhead running containers, balanced pod allocation across clusters
  23. 23. Install / Upgrade via Helm • Package manager and template framework for Kubernetes Apps • Fusion 5 comes well-configured out-of-the-box via a Helm Chart • Add the Artifactory Helm repository: helm repo add lucidworks https://charts.lucidworks.com helm repo update • Install Fusion cluster: helm install --values default_fusion_values.yaml -n f5 lucidworks/fusion • Upgrade Fusion cluster: helm upgrade --values default_fusion_values.yaml f5 lucidworks/fusion See: https://github.com/lucidworks/fusion-cloud-native
  24. 24. Operational Efficiency / Reduced TCO
  25. 25. Query Processing with Microservices
  26. 26. Workload Isolation
  27. 27. THANK YOU
  28. 28. 29 Resources Blog: Introducing Fusion 5 Fusion 5.0 Documentation https://github.com/lucidworks/fusion-cloud-native Webinar: Predictive Merchandiser Deep Dive (Oct 10)

Editor's Notes

  • Today’s presenters are Tim Potter and Alea Abed

    Tim is the Chief Architect here at Lucidworks, heading up our cloud engineering efforts. He is also an Apache Lucene/Solr committer. And Alea is the director of product marketing here at Lucidworks.
  • Thanks, Janessa.
    Today we are going to talk to you about our latest release of Lucidworks Fusion. First, I’ll share a brief overview of Lucidworks for those of you who aren’t familiar, then talk through some of the new features in Fusion 5, and then Tim will dive a bit deeper into the technical details.
  • Lucidworks is a search and AI company, and we help the world’s largest organizations make their most valuable data work for their customers and employees.

    We offer Lucidworks Fusion, a platform that hyper-personalizes digital experiences

    We have just over 250 employees and more than 400 customer engagements across the Fortune 2000.
  • We have a major global presence, with support operations that cover every time zone. We’re headquartered in San Francisco, California with another major U.S. office in North Carolina, as well as global offices in the United Kingdom, India and Hong Kong.
  • In our over 400 deployments across the fortune 200, we’ve seen some themes arise. These probably wont surprise you… personalization is expected, an AI is a priority. In digital workplace, we’re seeing that consumer-like experiences are expected, and in commerce we’re seeing that many retailers are differentiating from Amazon in omnichannel experience. AI is what powers those personalized experiences.

    So, we solve for that by providing hyper-personalized experiences to workers and shoppers.
  • We support these needs by hyper-personalizing employee and customer experiences. In the case of the digital workplace, Lucidworks Fusion uses AI and machine learning to give your customers, in the case of support portals, and employees – for enterprise search and discovery apps-- access to the information they need to take the next best action.
  • SCRIPT
    Those customers chose Lucidworks Fusion because the hyper-personalized workplace experiences that it creates make employees more engaged and effective as they care for customers, conduct research, recruit talent, ensure compliance or detect fraud.

  • SCRIPT:
    The open source Linux pioneer, Red Hat, uses Lucidworks for customer support.

    With Fusion, they have:
    Tripled their click-through rate,
    avoided about 50,000 support tickets and
    reduced their TCO by 91%, compared to their previous self-service portal.

    REFERENCES:
    Case Study: “How Red Hat Cut Costs and Improved Relevancy with Lucidworks Fusion” | http://programs.lucidworks.com/rs/579-JML-927/images/Lucidworks_Red_Hat_Case_Study.pdf
  • SCRIPT:
    What if you could tailor the shopping experience to match each shopper’s wants and needs?

    Lucidworks Fusion uses AI and machine learning to make online shopping experiences uniquely personal for each and every shopper.
  • These hyper-personalized shopping experiences improve KPIs like ,add-to-cart, average order value, and clickthrough rates.

    Fusion’s integrated machine learning takes on some of the tedious things that merchandisers don’t enjoy doing (such as maintaining thousands of business rules), freeing merchandisers to focud more attention on the areas where human intelligence and creativity should not be replaced by algorithsm.– we’ll cover more on this later.

  • Here’s an example of a Fortune 500 retailer who uses Fusion to handle search across multiple B2B, b2c, SMB and private sites globally. Before Fusion they experienced challenges around zero-results searches, click-through rates, and personalization. In just one year of using Fusion, they were able to attribute a 170% increase in search-based revenue and a 142% increase in click-through rates. They have improved those metrics even further as they have implemented signals and other machine learning tools within Fusion.
  • In order to hyper-personalize digital experiences and support improved metrics in commerce and workplace apps, Lucidworks Fusion incorporates AI and Machine Learning (ML) throughout the platform to intelligently ingest, explore, and curate the data.

    Fusion can ingest data of any type, from any data source – and uses AI on the ingest side to cluster, classify and organize content, then on the query side to understand intent and personalize results. App Studio is our application development framework that enables rapid development of front-end applications.




  • Lucidworks Fusion 5.0 lets customers easily deploy AI-powered data discovery and search applications in a
    modern, containerized architecture with built-in support for rapidly building interactive dashboards and modern enterprise
    applications. Customers can leverage existing models and workflows, or quickly create and deploy new ones using popular tools like Python ML, TensorFlow, scikit-learn, and spaCy.
  • Enables merchandisers to be self-service

    Eliminates the tedious workflows where merchandisers have to ask IT to create and manage rules

    Visual interface to create rules to pin, boost, bury, block and hide specific products for a search term or category page
  • Like I said, Tim will dig a bit deeper into microservices– but from a business standpoint, these are some of the benefits of Fusion 5’s microservices architecture and new features.
  • Scale resources efficiently and schedule capacity for events like Black Friday
    Reduce risk of downtime and lost revenue
    Seamlessly improve product relevance with custom ML models
    Give merchandisers more control over search & browse experience


  • Lucidworks Fusion 5.0 lets customers easily deploy AI-powered data discovery and search applications in a
    modern, containerized architecture with built-in support for rapidly building interactive dashboards and modern enterprise
    applications. Customers can leverage existing models and workflows, or quickly create and deploy new ones using popular tools like Python ML, TensorFlow, scikit-learn, and spaCy.
  • Microservices allow Lucidworks to roll out updates quickly
    Fusion 5  delivers consumer-like experiences to the digital workplace
    Architected with Kubernetes to follow modern cloud architecture best practices.
    Packaging via Helm and Spring Security and continuous zero-downtime upgrades.

    Flexible deployment: Deployable on GCP, Azure and AWS
    Fusion is the only platform which allows you to scale different search and index traffic without separate installations.
    Customers only need one overall deployment and they can scale resources based on traffic type
    Python models are supported natively


    Fusion is the only platform which allows you to scale different search and index traffic without separate installations.

    Data scientists can work within a familiar workflow – streamlining productivity.

    Definition: Microservices are a software development technique that
    structures an application as a collection of loosely coupled services, with these
    advantages:

    Resilience
    -
    a failure in the code affects no more than one service or function

    Scalability
    -
    scale up a single function or service without having to scale the entire
    application

    Flexibility
    -
    use the right tool for the right task, without getting tied down to one vendor

    Speed to market
    -
    make changes to a specific service, without rewriting the entire codebase

    Easier maintenance
    -
    smaller modules going through a CI process improves our ability to
    deliver error-free applications

    Reduced TCO
    -
    multiple teams work on independent services, enabling you to deploy more
    quickly

    Continuous delivery
    -
    code is continuously developed, tested and deployed, and you can use
    code from existing libraries instead of reinventing the wheel
    https://www.cio.com/article/3201193/7-reasons-to-switch-to-microservices-and-5-reasons-you-might-not-succeed.html
  • In previous versions of Fusion, ops teams had to consult Lucidworks on how to efficiently run Fusion in HA manner. Turn that problem on its head, now the Ops are baked in. Fusion engineering has already thought thru many of the scaling, resiliency concerns and baked those into the Fusion Helm chart

    Problems are only getting harder
    Bigger datasets
    More apps
    Faster churn
    Smarter insights, hyper-personalization
    Reduced friction, well-configured out-of-the-box
    Minimize risks associated with making changes
    Zero downtime for most updates

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