Home Forums Kamanja Forums Use Cases & Samples Kamanja Use cases

This topic contains 3 replies, has 4 voices, and was last updated by  Greg Makowski 1 year, 4 months ago.

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  • #12860 Reply

    Mehul Parekh
    Member

    Kamanja – our open-source continuous decisioning engine has numerous use cases.

    Here are some example use cases where Kamanja can be used:
    – Fraud
    – Risk Analysis
    – Customer Contact
    – Cyber Crime
    – Telephony Interception
    – Security & Compliance
    – Audit & Governance
    – Customer churn/retention
    – Marketing
    – Real-time Offers

    How are you using Kamanja?

  • #19766 Reply

    Phoenix

    Can Kamanja also be used as a replacement to a Business Rule Engine (like Drools)?

    • #19768 Reply

      JP Creedon
      Member

      Hi Phoenix,

      Thanks for your question. I am not super familiar with Drools, but I spent a little time reading up on it so I hope my response is helpful.

      Kamanja’s ability to execute models would allow it to be used as a Business Rule Engine (like Drools). The note-able difference is models would have to be defined in Java/Scale or exported from one of the popular data science tools using PMML for consumption in Kamanja. In terms of replacing the rule functionality, Decision tree algorithms should fit the bill and then based on the graded output performing an action.

      Please feel free to reach out to me to discuss your proposed use-case further.

      jp@ligadata.com

  • #19831 Reply

    Greg Makowski
    Moderator

    There is PMML support for Rules, which may be manually or programatically generated.  Some data mining systems, like R, allow for Decision Trees (a data mining algorithm trained for optimal prediction), to be converted to rules.

    If you want a user interface to manually create rules, you can use the free KNIME system’s Rule Engine Node to edit rules.  Then they can be exported to PMML to be run into Kamanja.

    If you are interested in complex event processing, Kamanja is excellent for that functionality, scalable to many nodes of Kafka for data streaming and Kamanja for executing logic in Java, Scala, PMML and soon, Python.

    If you are interested in optimization or constraint satisfaction, see the many related packages in Java or Python, which could be executed in Kamanja in production.

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