Updated description for DAI MOJO deployment to MiNiFi

README.md

@@ -30,5 +30,5 @@ deployment templates.
    - These examples are based off of the README.txt that comes with the Python Scoring Pipeline and details the many ways it could be used. Here, each example is standalone and has step-by-step instructions for preparing your environment and testing that the setup with successful.
    - Available Examples:
       - [EC2 Ubuntu HTTP Server](./python-scoring-pipeline/http_ec2_ubuntu.md)
-- [Deploy Driverless AI MOJO to MiNiFi C++](./mojo-py-minificpp/README.md)
-   - This example will walk through how to use the custom MiNiFi Python processor to execute the Driverless AI MOJO Scoring Pipeline within a MiNiFi Data Flow to do batch scoring or real-time scoring.
+- [Deploy Driverless AI MOJO Scoring Pipeline in a MiNiFi C++ Data Flow with CEM](./mojo-py-minificpp/README.md)
+   - This example will walk through how to install Cloudera Edge Management, which includes Edge Flow Manager, NiFi Registry and one MiNiFi C++ Agent and Driverless AI MOJO2 Python Runtime on an EC2 instance. It will then go through how to use EFM to build a data flow with Driverless AI MOJO Scoring Pipeline for a MiNiFi C++ Agent and publish that data flow to that agent. With Cloudera Ege Management and Driverless AI MOJO Scoring Pipeline integration, pushing ML models to an edge device is much easier.